05 - EnsembleLearningBaseLearnerDamageClassesBalancedData.ipynb

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   "source": [
    "# Ensemble Learning - Base-Models with Balanced Training Data\n",
    "Build and optimize base models using balanced training data"
   ]
  },
  {
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   "source": [
    "%matplotlib inline"
   ]
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   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "import os\n",
    "import json\n",
    "\n",
    "import pickle\n",
    "\n",
    "from sklearn import metrics\n",
    "from sklearn.base import clone\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from sklearn.model_selection import train_test_split, StratifiedKFold, RandomizedSearchCV\n",
    "from sklearn.feature_selection import SequentialFeatureSelector\n",
    "from sklearn.ensemble import RandomForestClassifier, BaggingClassifier, HistGradientBoostingClassifier, AdaBoostClassifier\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "import xgboost as xgb\n",
    "\n",
    "from imblearn.under_sampling import RandomUnderSampler, EditedNearestNeighbours\n",
    "from imblearn.over_sampling import SMOTE\n",
    "from imblearn.combine import SMOTEENN\n",
    "from imblearn.ensemble import BalancedRandomForestClassifier, RUSBoostClassifier\n",
    "\n",
    "from collections import Counter\n",
    "\n",
    "pd.set_option(\"display.max_columns\", None)"
   ]
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   "source": [
    "## Data Import & Data Preparation"
   ]
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   "source": [
    "DATA_PATH = \"./data\"\n",
    "EXPORT_PATH = f\"{DATA_PATH}/BaseLearner/v5\"\n",
    "\n",
    "SPECIES_CODE = {\n",
    "    \"1\":\"Deciduous\",\n",
    "    \"2\":\"Conifer\",\n",
    "    \"1 2\":\"Mixed\"\n",
    "}\n",
    "\n",
    "SPECIES_CODE_INVERSE = {\n",
    "    \"Deciduous\": \"1\",\n",
    "    \"Conifer\": \"2\",\n",
    "    \"Mixed\": \"1 2\"\n",
    "}"
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       "      <td>-0.081468</td>\n",
       "      <td>1.680325</td>\n",
       "      <td>-0.857075</td>\n",
       "      <td>1.889191</td>\n",
       "      <td>0.691020</td>\n",
       "      <td>-0.369506</td>\n",
       "      <td>0.323830</td>\n",
       "      <td>0.515489</td>\n",
       "      <td>0.852785</td>\n",
       "      <td>-0.814671</td>\n",
       "      <td>0.897376</td>\n",
       "      <td>0.046127</td>\n",
       "      <td>-0.719613</td>\n",
       "      <td>-0.140728</td>\n",
       "      <td>0.69179</td>\n",
       "      <td>-0.815622</td>\n",
       "      <td>0.119561</td>\n",
       "      <td>-0.193376</td>\n",
       "      <td>-1.501934</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      location_cluster_0  location_cluster_1  location_cluster_2  \\\n",
       "0                      0                   1                   0   \n",
       "5188                   0                   0                   0   \n",
       "5187                   0                   0                   0   \n",
       "5186                   0                   0                   0   \n",
       "5185                   0                   0                   0   \n",
       "\n",
       "      location_cluster_3  location_cluster_4  location_cluster_5  \\\n",
       "0                      0                   0                   0   \n",
       "5188                   1                   0                   0   \n",
       "5187                   1                   0                   0   \n",
       "5186                   1                   0                   0   \n",
       "5185                   1                   0                   0   \n",
       "\n",
       "      location_cluster_6  location_cluster_7  location_cluster_8  \\\n",
       "0                      0                   0                   0   \n",
       "5188                   0                   0                   0   \n",
       "5187                   0                   0                   0   \n",
       "5186                   0                   0                   0   \n",
       "5185                   0                   0                   0   \n",
       "\n",
       "      location_cluster_9  location_cluster_10  location_cluster_11  \\\n",
       "0                      0                    0                    0   \n",
       "5188                   0                    0                    0   \n",
       "5187                   0                    0                    0   \n",
       "5186                   0                    0                    0   \n",
       "5185                   0                    0                    0   \n",
       "\n",
       "      location_cluster_12  location_cluster_13    tree_1      evi2    evi2-1  \\\n",
       "0                       0                    0 -0.780422  0.247127  0.134649   \n",
       "5188                    0                    0 -0.630696 -1.377409  0.134649   \n",
       "5187                    0                    0 -0.630696 -1.606661  0.134649   \n",
       "5186                    0                    0 -0.630696 -1.074025  0.134649   \n",
       "5185                    0                    0 -0.630696 -1.332807  0.134649   \n",
       "\n",
       "      evi2_diff  evi2_max_diff  evi2_raster  evi2_raster-1  evi2_raster_diff  \\\n",
       "0     -0.063166       0.558887    -1.965227       2.321263          2.190397   \n",
       "5188   1.210990       1.661654    -1.010216       0.702443          0.638921   \n",
       "5187   1.546983       1.771145    -1.010216       0.702443          0.372483   \n",
       "5186   0.871901       1.478956    -1.010216       0.702443          0.858797   \n",
       "5185   1.155192       1.658395    -1.010216       0.702443          0.678140   \n",
       "\n",
       "      evi2_vegetation_raster  evi2_vegetation_raster-1  \\\n",
       "0                  -1.591913                  1.467303   \n",
       "5188               -0.897612                  0.639956   \n",
       "5187               -0.897612                  0.639956   \n",
       "5186               -0.897612                  0.639956   \n",
       "5185               -0.897612                  0.639956   \n",
       "\n",
       "      evi2_vegetation_raster_diff      ndvi    ndvi-1  ndvi_diff  \\\n",
       "0                        2.389869  0.269184  0.155518  -0.056732   \n",
       "5188                     0.116478 -1.394638  0.155518   1.023457   \n",
       "5187                    -0.247533 -1.639614  0.155518   1.352077   \n",
       "5186                     0.449890 -1.072860  0.155518   0.711611   \n",
       "5185                     0.173522 -1.347134  0.155518   0.970864   \n",
       "\n",
       "      ndvi_max_diff  ndvi_raster  ndvi_raster-1  ndvi_raster_diff  \\\n",
       "0          0.396759    -2.000923       2.376153          4.699451   \n",
       "5188       1.773875    -1.020630       0.601524         -0.686361   \n",
       "5187       1.909480    -1.020630       0.601524         -1.216333   \n",
       "5186       1.542268    -1.020630       0.601524         -0.168402   \n",
       "5185       1.763622    -1.020630       0.601524         -0.600060   \n",
       "\n",
       "      ndvi_vegetation_raster  ndvi_vegetation_raster-1  \\\n",
       "0                  -1.625971                  1.476802   \n",
       "5188               -0.906359                  0.610358   \n",
       "5187               -0.906359                  0.610358   \n",
       "5186               -0.906359                  0.610358   \n",
       "5185               -0.906359                  0.610358   \n",
       "\n",
       "      ndvi_vegetation_raster_diff  autumn_humidity  autumn_rain_mm  \\\n",
       "0                        3.188868         2.349058       -0.032661   \n",
       "5188                    -1.136011         1.391816        0.207266   \n",
       "5187                    -1.472954         1.391816        0.207266   \n",
       "5186                    -0.695910         1.391816        0.207266   \n",
       "5185                    -1.071161         1.391816        0.207266   \n",
       "\n",
       "      autumn_sun_h  extreme_heat_day  frozen_day  heat_day  heavy_rain  \\\n",
       "0        -0.510027         -0.844847    0.729139  1.259041    0.020538   \n",
       "5188     -0.081468          1.680325   -0.857075  1.889191    0.691020   \n",
       "5187     -0.081468          1.680325   -0.857075  1.889191    0.691020   \n",
       "5186     -0.081468          1.680325   -0.857075  1.889191    0.691020   \n",
       "5185     -0.081468          1.680325   -0.857075  1.889191    0.691020   \n",
       "\n",
       "      spring_humidity  spring_rain_mm  spring_sun_h     storm  \\\n",
       "0            0.030137       -0.308301      0.671584 -1.489254   \n",
       "5188        -0.369506        0.323830      0.515489  0.852785   \n",
       "5187        -0.369506        0.323830      0.515489  0.852785   \n",
       "5186        -0.369506        0.323830      0.515489  0.852785   \n",
       "5185        -0.369506        0.323830      0.515489  0.852785   \n",
       "\n",
       "      summer_humidity  summer_longest_heat_wave  \\\n",
       "0            0.595120                  0.671331   \n",
       "5188        -0.814671                  0.897376   \n",
       "5187        -0.814671                  0.897376   \n",
       "5186        -0.814671                  0.897376   \n",
       "5185        -0.814671                  0.897376   \n",
       "\n",
       "      summer_periods_without_rain_summer  summer_rain_mm  summer_sun_h  \\\n",
       "0                               1.252978        0.111377     -0.265597   \n",
       "5188                            0.046127       -0.719613     -0.140728   \n",
       "5187                            0.046127       -0.719613     -0.140728   \n",
       "5186                            0.046127       -0.719613     -0.140728   \n",
       "5185                            0.046127       -0.719613     -0.140728   \n",
       "\n",
       "      winter_humidity  winter_longest_cold_wave  winter_rain_mm  \\\n",
       "0             1.79314                  0.343276       -1.081905   \n",
       "5188          0.69179                 -0.815622        0.119561   \n",
       "5187          0.69179                 -0.815622        0.119561   \n",
       "5186          0.69179                 -0.815622        0.119561   \n",
       "5185          0.69179                 -0.815622        0.119561   \n",
       "\n",
       "      winter_snow_cm  winter_sun_h  \n",
       "0           0.637993     -0.509518  \n",
       "5188       -0.193376     -1.501934  \n",
       "5187       -0.193376     -1.501934  \n",
       "5186       -0.193376     -1.501934  \n",
       "5185       -0.193376     -1.501934  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(f\"{DATA_PATH}/location_cluster.csv\")\n",
    "\n",
    "df = df.sort_values(by=\"year\")\n",
    "\n",
    "# -----\n",
    "\n",
    "def is_healthy(damage_class_group:str)->int:\n",
    "    if damage_class_group == \"healthy\":\n",
    "        return 1\n",
    "    else:\n",
    "        return 0\n",
    "    \n",
    "def is_damaged(damage_class_group:str)->int:\n",
    "    if damage_class_group == \"damaged\":\n",
    "        return 1\n",
    "    else:\n",
    "        return 0\n",
    "    \n",
    "def is_dead(damage_class_group:str)->int:\n",
    "    if damage_class_group == \"dead\":\n",
    "        return 1\n",
    "    else:\n",
    "        return 0\n",
    "    \n",
    "df[\"is_healthy\"] = df[\"damage_class_group\"].apply(lambda x: is_healthy(x))\n",
    "df[\"is_damaged\"] = df[\"damage_class_group\"].apply(lambda x: is_damaged(x))\n",
    "df[\"is_dead\"] = df[\"damage_class_group\"].apply(lambda x: is_dead(x))\n",
    "\n",
    "# -----\n",
    "\n",
    "static_cols = [\n",
    "    col for col in df.columns if \"location_cluster_\" in col\n",
    "]\n",
    "static_cols.append(\"tree_1\")\n",
    "\n",
    "vegetation_cols = [\n",
    "    col for col in df.columns if ((\"ndvi\" in col) or (\"evi2\" in col)) and not col.endswith('max')\n",
    "]\n",
    "\n",
    "weather_cols = [\n",
    "    'autumn_humidity',\n",
    "    'autumn_rain_mm',\n",
    "    'autumn_sun_h',\n",
    "    'extreme_heat_day',\n",
    "    'frozen_day',\n",
    "    'heat_day',\n",
    "    'heavy_rain',\n",
    "    'spring_humidity',\n",
    "    'spring_rain_mm',\n",
    "    'spring_sun_h',\n",
    "    'storm',\n",
    "    'summer_humidity',\n",
    "    'summer_longest_heat_wave',\n",
    "    'summer_periods_without_rain_summer',\n",
    "    'summer_rain_mm',\n",
    "    'summer_sun_h',\n",
    "    'winter_humidity',\n",
    "    'winter_longest_cold_wave',\n",
    "    'winter_rain_mm',\n",
    "    'winter_snow_cm',\n",
    "    'winter_sun_h',\n",
    "]\n",
    "\n",
    "all_features = static_cols + vegetation_cols + weather_cols\n",
    "\n",
    "df[all_features].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f664b83a-4a93-4ce0-bba9-b05786865d38",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### Definition of Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "135f63a2-1353-4e70-be22-16eaca8a809b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-16T11:03:18.410685Z",
     "iopub.status.busy": "2022-06-16T11:03:18.409686Z",
     "iopub.status.idle": "2022-06-16T11:03:18.450687Z",
     "shell.execute_reply": "2022-06-16T11:03:18.449687Z",
     "shell.execute_reply.started": "2022-06-16T11:03:18.410685Z"
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def train_test_split_by_observation(data_frame:pd.DataFrame, target:str, features:list):\n",
    "    data_frame[\"key\"] = data_frame[\"observation_id\"] + \":\" + data_frame[\"year\"].astype(str)\n",
    "    \n",
    "    # group by observation_id and year to get unique observations by year only to prevent overfitting\n",
    "    df_group = data_frame.groupby([\"observation_id\", \"year\"]).agg({\"damage_class_group\": lambda x: x.value_counts().index[0], target: lambda x: x.value_counts().index[0], \"aoi\": \"first\"}).reset_index()\n",
    "    # remove all damaged classes that are not in BF\n",
    "    #df_group = df_group.loc[~((df_group.damage_class_group == \"damaged\") & (df_group.aoi != \"blackforest\"))]\n",
    "    y_observation_id = df_group.pop(target)\n",
    "    X_observation_id = df_group\n",
    "\n",
    "    # key to identify splitted data\n",
    "    X_observation_id[\"key\"] = X_observation_id[\"observation_id\"] + \":\" + X_observation_id[\"year\"].astype(str)\n",
    "    # train test split\n",
    "    X_train_observation_id, X_test_observation_id, y_train_observation_id, y_test_observation_id = train_test_split(X_observation_id, y_observation_id, train_size=0.8, stratify=y_observation_id, random_state=2022)\n",
    "\n",
    "    # filter for train test samples based on observation:year\n",
    "    _X_train = data_frame.loc[data_frame.key.isin(list(X_train_observation_id.key))][features]\n",
    "    _X_test = data_frame.loc[data_frame.key.isin(list(X_test_observation_id.key))][features]\n",
    "\n",
    "    return _X_train, _X_test\n",
    "\n",
    "def define_class_weight(y:np.array)->dict:\n",
    "    class_weights = dict()\n",
    "\n",
    "    for _class, count in Counter(y).items():\n",
    "        weight = len(y) / (len(Counter(y)) * count)\n",
    "        class_weights[_class] = weight\n",
    "    return class_weights\n",
    "\n",
    "def define_pos_scale(y:np.array)->float:\n",
    "    return dict(Counter(y))[0] / dict(Counter(y))[1]\n",
    "    \n",
    "# https://www.analyticsvidhya.com/blog/2016/03/complete-guide-parameter-tuning-xgboost-with-codes-python/\n",
    "def parameter_tuning(_model=None, _params=None, _scoring=None, _X=None, _y=None):\n",
    "    sk_fold = StratifiedKFold(n_splits=3, shuffle=True, random_state=2022)\n",
    "\n",
    "    randomized_clf_param_tuning = RandomizedSearchCV(estimator=_model, param_distributions=_params, scoring=_scoring, cv=sk_fold, n_jobs=58, n_iter=100, verbose=0)\n",
    "\n",
    "    randomized_clf_param_tuning.fit(_X, _y)\n",
    "    return randomized_clf_param_tuning.best_params_\n",
    "\n",
    "def apply_prediction(pos_probs, threshold):\n",
    "     return (pos_probs >= threshold).astype('int')\n",
    "    \n",
    "def get_model_params(_model: str, _target: str, _species:str)->dict:\n",
    "    base_model = clone(pickle.load(open(f\"{DATA_PATH}/BaseLearner/tmp/{_model}_{_species}_{_target}.sav\", 'rb')))\n",
    "    return base_model.get_params()\n",
    "\n",
    "def roc_auc(actual, pred_proba, axes):\n",
    "    fpr, tpr, thresholds = metrics.roc_curve(actual, pred_proba)\n",
    "    # calculate the g-mean for each threshold\n",
    "    gmeans = np.sqrt(tpr * (1-fpr))\n",
    "    # locate the index of the largest g-mean\n",
    "    ix = np.argmax(gmeans)\n",
    "    if axes:\n",
    "        # plot the roc curve for the model\n",
    "        sns.lineplot([0,1], [0,1], linestyle='--', label='No Skill', color=\"tab:gray\", ax=axes, err_style=None)\n",
    "        sns.lineplot(fpr, tpr, label='Model', color=\"black\", ax=axes, err_style=None)\n",
    "        sns.scatterplot([fpr[ix]], [tpr[ix]], marker='^', color='tab:red', label=f'Optimal threshold @ {thresholds[ix]:.3f}', s=150, zorder=2, ax=axes)\n",
    "    \n",
    "    return thresholds[ix], gmeans[ix]\n",
    "\n",
    "def prc_rc(actual, pred_proba, axes):\n",
    "    precision, recall, thresholds = metrics.precision_recall_curve(actual, pred_proba)\n",
    "    fscore = (2 * precision * recall) / (precision + recall)\n",
    "    # locate the index of the largest f score\n",
    "    ix = np.argmax(fscore)\n",
    "    # plot the roc curve for the model\n",
    "    no_skill = len(actual[actual==1]) / len(actual)\n",
    "    if axes:\n",
    "        sns.lineplot([0,1], [no_skill,no_skill], linestyle='--', label='No Skill', color=\"tab:gray\", ax=axes, err_style=None)\n",
    "        sns.lineplot(recall, precision, label='Model', color=\"black\", ax=axes, err_style=None)\n",
    "        sns.scatterplot([recall[ix]], [precision[ix]], marker='^', color='tab:red', label=f'Optimal threshold @ {thresholds[ix]:.3f}', s=150, zorder=2, ax=axes)\n",
    "\n",
    "    return thresholds[ix], fscore[ix]\n",
    "    \n",
    "def tune_threshold(actual, pred_proba, axes):\n",
    "    # Array for finding the optimal threshold\n",
    "    thresholds = np.arange(0.0, 1.0, 0.001)\n",
    "    fscore = np.zeros(shape=(len(thresholds)))\n",
    "    # Fit the model\n",
    "    def to_labels(pos_probs, threshold):\n",
    "         return (pos_probs >= threshold).astype('int')\n",
    "    fscore = [metrics.f1_score(actual, to_labels(pred_proba, t)) for t in thresholds]\n",
    "        \n",
    "    # Find the optimal threshold\n",
    "    ix = np.argmax(fscore)\n",
    "    if axes:\n",
    "        sns.lineplot(thresholds, fscore, color=\"black\", ax=axes, err_style=None)\n",
    "        sns.scatterplot([thresholds[ix]], [fscore[ix]], marker='^', color='tab:red', label=f'Optimal threshold @ {thresholds[ix]:.3f}', s=150, zorder=2, ax=axes)\n",
    "\n",
    "    return thresholds[ix], fscore[ix]\n",
    "\n",
    "\n",
    "def parse_results(data_frame:pd.DataFrame):\n",
    "    param_cols = [col for col in data_frame.columns if col.startswith(\"params\")]\n",
    "    metric_cols = [col for col in data_frame.columns if col.startswith(\"metrics\")]\n",
    "    feat_permutation_cols = [col for col in data_frame.columns if col.startswith(\"feature_permutaion_importance\")]\n",
    "\n",
    "    param_cols.extend([\"model\", \"target\", \"species\"])\n",
    "    metric_cols.extend([\"model\", \"target\", \"species\"])\n",
    "    feat_permutation_cols.extend([\"model\", \"target\", \"species\"])\n",
    "    \n",
    "    metric_groups = [\"roc\", \"prc\", \"tuning\"]\n",
    "    actual_metrics = [\"threshold\", \"cohen_kappa\", \"f1\", \"recall\", \"precision\", \"tn\", \"fp\", \"fn\", \"tp\"]\n",
    "\n",
    "    metrics_values = []\n",
    "    for metric_group in metric_groups:\n",
    "        for _i, _r in data_frame.iterrows():\n",
    "            vals = {\"group\": metric_group, \"model\": _r[\"model\"], \"target\": _r[\"target\"], \"species\": _r[\"species\"], \"auc\": _r[\"metrics.auc\"]}\n",
    "            for col in metric_cols:\n",
    "                for _m in actual_metrics:\n",
    "                    if _m in col and metric_group in col:\n",
    "                        vals[_m] = _r[col]\n",
    "\n",
    "            metrics_values.append(vals)\n",
    "\n",
    "    df_metrics = pd.json_normalize(metrics_values)\n",
    "    df_metrics = df_metrics.sort_values(by=\"f1\", ascending=False)\n",
    "    #print(f\"model results -> {df_metrics.shape[0]} x {list(df_metrics.columns)}\")\n",
    "\n",
    "    best_model_selection = list()\n",
    "    for _i, _r in df_metrics.groupby([\"target\", \"species\", \"model\"]).size().reset_index().iterrows():\n",
    "        df_filter = df_metrics.loc[(df_metrics.target == _r.target) & (df_metrics.species == _r.species) & (df_metrics.model == _r.model)].sort_values(by=\"threshold\", ascending=False)\n",
    "        best_model_selection.append(df_filter.loc[df_filter.cohen_kappa == df_filter.cohen_kappa.max()].iloc[0][[\"target\", \"species\", \"model\", \"group\"]].values)\n",
    "\n",
    "    df_model_selection = pd.DataFrame(data=best_model_selection, columns=[\"target\", \"species\", \"model\", \"group\"])\n",
    "    df_best_metrics = df_metrics.merge(df_model_selection, on=[\"target\", \"species\", \"model\", \"group\"], how=\"inner\").drop_duplicates()\n",
    "    #print(f\"best model results -> {df_best_metrics.shape[0]} x {list(df_best_metrics.columns)}\")\n",
    "\n",
    "    df_parameter = data_frame[param_cols].melt(id_vars=param_cols[-3:], var_name=\"param\", value_name=\"val\")\n",
    "    df_parameter[\"param\"] = df_parameter[\"param\"].apply(lambda x: x.replace(\"params.\", \"\"))\n",
    "    df_parameter = df_parameter.dropna()\n",
    "    #print(f\"model params -> {df_parameter.shape[0]} x {list(df_parameter.columns)}\")\n",
    "\n",
    "    df_feature_importance = data_frame[feat_permutation_cols].melt(id_vars=feat_permutation_cols[-3:], var_name=\"feature\", value_name=\"feature_importance\")\n",
    "    df_feature_importance[\"feature\"] = df_feature_importance[\"feature\"].apply(lambda x: x.replace(\"feature_permutaion_importance.\", \"\"))\n",
    "    df_feature_importance = df_feature_importance.sort_values(by=\"feature_importance\", ascending=False)\n",
    "    #print(f\"features -> {df_feature_importance.shape[0]} x {list(df_feature_importance.columns)}\")\n",
    "    \n",
    "    return df_metrics, df_best_metrics, df_parameter, df_feature_importance"
   ]
  },
  {
   "cell_type": "markdown",
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   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### Model Parameters"
   ]
  },
  {
   "cell_type": "code",
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   "id": "94416e65-6138-4550-877d-24e9430559d4",
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   "source": [
    "PARAMS_RF = {\n",
    "    'max_depth': np.arange(16, 256, 16),\n",
    "    'max_features': [\"sqrt\"],\n",
    "    'min_samples_leaf': np.arange(2, 16, 2),\n",
    "    'min_samples_split': np.arange(2, 16, 2),\n",
    "    'n_estimators': np.arange(32, 512, 16),\n",
    "    'n_jobs': [58],\n",
    "    'warm_start': [True, False],\n",
    "    'random_state': [2022],\n",
    "}\n",
    "PARAMS_XGB = {\n",
    "    'max_depth': np.arange(3, 8, 1),\n",
    "    'learning_rate': np.arange(0.001, 0.01, 0.002),\n",
    "    'n_estimators': np.arange(50, 500, 15),\n",
    "    'colsample_bytree': np.arange(0.5, 1, 0.05),\n",
    "    'subsample': np.arange(0.5, 1, 0.05),\n",
    "    'eval_metric': [\"aucpr\", \"auc\"],\n",
    "    'objective': ['binary:logistic'],\n",
    "    'gamma': np.arange(0, 1, 0.05),\n",
    "    'lambda': np.arange(0, 1, 0.1),\n",
    "    'seed': [2022],\n",
    "    'n_jobs': [58],\n",
    "}\n",
    "PARAMS_KN = {\n",
    "    'n_neighbors': np.arange(2, 18, 1),\n",
    "    'weights': [\"distance\", \"uniform\"],\n",
    "    'algorithm': ['ball_tree', 'kd_tree', 'brute'],\n",
    "    'leaf_size': np.arange(10, 50, 2),\n",
    "    'p': [1, 2],\n",
    "    'n_jobs': [58],\n",
    "    'metric': ['euclidean', 'manhattan', 'chebyshev', 'minkowski', 'wminkowski', 'seuclidean', 'mahalanobis']\n",
    "}\n",
    "PARAMS_DT = {\n",
    "    'criterion': [\"gini\", \"entropy\"],\n",
    "    'splitter': [\"random\", \"best\"],\n",
    "    'max_depth': np.arange(2, 32, 1),\n",
    "    'min_samples_split': np.arange(2, 32, 2),\n",
    "    'min_samples_leaf': np.arange(1, 16, 1),\n",
    "    'max_features': [\"sqrt\", \"log2\"],\n",
    "    'random_state': [2022],\n",
    "    'min_weight_fraction_leaf': np.arange(0.0, 1.0, 0.05),\n",
    "    'max_leaf_nodes': np.arange(1, 2048, 32),\n",
    "    'min_impurity_decrease': np.arange(0.0, 1.0, 0.05),\n",
    "    'ccp_alpha': np.arange(0, 1, 1),\n",
    "}\n",
    "PARAMS_HGB = {\n",
    "    'loss': ['binary_crossentropy'],\n",
    "    'learning_rate': np.arange(0.01, 0.05, 0.0005),\n",
    "    'max_iter': np.arange(25, 500, 25),\n",
    "    'max_leaf_nodes': np.arange(1, 128, 7),\n",
    "    'max_depth': np.arange(1, 128, 7),\n",
    "    'min_samples_leaf': np.arange(2, 32, 1),\n",
    "    'l2_regularization': np.arange(0.0, 1.0, 0.05),\n",
    "    #'warm_start': [True, False],\n",
    "    'scoring': [\"f1\", \"roc_auc\"],\n",
    "    #'tol': np.arange(1e-7, 9e-7, 1e-8),\n",
    "    'random_state': [2022],\n",
    "}\n",
    "PARAMS_BRF = {\n",
    "    'max_depth': np.arange(16, 256, 16),\n",
    "    'max_features': [\"sqrt\"],\n",
    "    'min_samples_leaf': np.arange(2, 24, 2),\n",
    "    'min_samples_split': np.arange(2, 24, 2),\n",
    "    'n_estimators': np.arange(32, 512, 16),\n",
    "    'n_jobs': [58],\n",
    "    'warm_start': [True, False],\n",
    "    'random_state': [2022],\n",
    "    #'class_weight': [define_class_weight(_y.values)]\n",
    "}\n",
    "PARAMS_RUS = {\n",
    "    'replacement': [True, False],\n",
    "    'learning_rate': np.arange(0.001, 0.1, 0.002),\n",
    "    'n_estimators': np.arange(50, 500, 15),\n",
    "    'algorithm': [\"SAMME\", \"SAMME.R\"],\n",
    "    'random_state': [2022],\n",
    "}\n",
    "PARAMS_ADA = {\n",
    "    'learning_rate': np.arange(0.05, 0.5, 0.025),\n",
    "    'n_estimators': np.arange(50, 500, 15),\n",
    "    'algorithm': [\"SAMME\", \"SAMME.R\"],\n",
    "    'random_state': [2022],\n",
    "}\n",
    "PARAMS_SVM = {\n",
    "    'gamma': np.arange(0.001, 1, 0.005),\n",
    "    'C': np.arange(0.1, 10, 0.25),\n",
    "    'shrinking': [False, True],\n",
    "    'kernel': ['rbf', 'poly', 'sigmoid'],\n",
    "    'probability': [True],\n",
    "    'tol': np.arange(0.001, 0.01, 0.001),\n",
    "    'decision_function_shape': ['ovo'],\n",
    "    'random_state': [2022],\n",
    "}"
   ]
  },
  {
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   "id": "aac86763-d9ea-4b1e-af45-afec23378f35",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### Define Hold-Out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "fad2da88-2efb-4c15-9295-46db2bc22760",
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    "execution": {
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     "name": "#%%\n"
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    "tags": []
   },
   "outputs": [],
   "source": [
    "np.random.seed(2022)\n",
    "\n",
    "binned_data = dict()\n",
    "for species in [\"1\", \"2\", \"1 2\"]:\n",
    "    _binned = df.copy()\n",
    "\n",
    "    _binned = _binned.loc[_binned.list_tree_sp_cat_ids == species]\n",
    "\n",
    "    for col in all_features:\n",
    "        _binned[col] = pd.qcut(_binned[col].rank(method='first'), 10) # _binned[col]\n",
    "        _binned[col] =_binned[col].cat.codes\n",
    "\n",
    "    min_max_scaler = MinMaxScaler()\n",
    "    _binned[all_features] = min_max_scaler.fit_transform(_binned[all_features])\n",
    "\n",
    "    validation_observation_ids = np.random.choice(_binned.loc[_binned.aoi == \"blackforest\"].observation_id.unique(), size=2)\n",
    "    _validation = _binned.loc[_binned.observation_id.isin(validation_observation_ids)]\n",
    "    \n",
    "    _train, _test = train_test_split_by_observation(data_frame=_binned.loc[~_binned.observation_id.isin(validation_observation_ids)], target=\"damage_class_group\", features=_binned.columns)\n",
    "    _test = pd.concat([_test, _validation])\n",
    "    \n",
    "    splitted_data = {\n",
    "        'train': _train,\n",
    "        'test': _test,\n",
    "        'validation': _validation\n",
    "    }\n",
    "    \n",
    "    binned_data[species] = splitted_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72f31da5-4f1b-4a1a-a4b3-a56bdddce006",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Base Learner\n",
    "The following steps are performed for all damage classes:\n",
    "1) Balancing the training data with SMOTE-ENN.\n",
    "2) Backward Feature Elemination to identify the 50% most relevant features.\n",
    "3) Perform parameter optimization of the base models\n",
    "4) Bagging ensemble\n",
    "5) Perform Feature Permutation Importance to calculate the relevance of the features used.\n",
    "6) Evaluate estimates including determination of decision boundary as well as metrics\n",
    "7) Export the results\n",
    "\n",
    "### Damaged Vegetation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "95c6f9d9-0d62-462c-82c6-e01f6bdec4af",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-04-07T06:47:01.911531Z",
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     "shell.execute_reply": "2022-04-08T04:27:29.285994Z",
     "shell.execute_reply.started": "2022-04-07T06:47:01.911531Z"
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "----------------------------------------------------------------------------------------------------\n",
      "RandomForestClassifier -> Deciduous@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "BalancedRandomForestClassifier -> Deciduous@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "DecisionTreeClassifier -> Deciduous@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "KNeighborsClassifier -> Deciduous@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "SVM -> Deciduous@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "RUSBoostClassifier -> Deciduous@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "AdaBoostClassifier -> Deciduous@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "XGBClassifier -> Deciduous@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "HistGradientBoostingClassifier -> Deciduous@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "RandomForestClassifier -> Conifer@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "BalancedRandomForestClassifier -> Conifer@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "DecisionTreeClassifier -> Conifer@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "KNeighborsClassifier -> Conifer@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "SVM -> Conifer@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "RUSBoostClassifier -> Conifer@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "AdaBoostClassifier -> Conifer@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "XGBClassifier -> Conifer@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "HistGradientBoostingClassifier -> Conifer@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "RandomForestClassifier -> Mixed@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "BalancedRandomForestClassifier -> Mixed@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "DecisionTreeClassifier -> Mixed@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "KNeighborsClassifier -> Mixed@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "SVM -> Mixed@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "RUSBoostClassifier -> Mixed@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "AdaBoostClassifier -> Mixed@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "XGBClassifier -> Mixed@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "HistGradientBoostingClassifier -> Mixed@is_damaged\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "---------------------------------------------------------------------------\n",
      "EXPORTING OVERALL RESULTS TO ./results/optimization/v5/modelling_pipeline_results.csv\n",
      "---------------------------------------------------------------------------\n"
     ]
    },
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>species</th>\n",
       "      <th>model</th>\n",
       "      <th>target</th>\n",
       "      <th>relevant_features</th>\n",
       "      <th>params.warm_start</th>\n",
       "      <th>params.random_state</th>\n",
       "      <th>params.n_jobs</th>\n",
       "      <th>params.n_estimators</th>\n",
       "      <th>params.min_samples_split</th>\n",
       "      <th>params.min_samples_leaf</th>\n",
       "      <th>params.max_features</th>\n",
       "      <th>params.max_depth</th>\n",
       "      <th>params.class_weight.1</th>\n",
       "      <th>params.class_weight.0</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_0</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_1</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_2</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_3</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_4</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_5</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_6</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_7</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_8</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_9</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_10</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_11</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_12</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_13</th>\n",
       "      <th>feature_permutaion_importance.tree_1</th>\n",
       "      <th>feature_permutaion_importance.evi2</th>\n",
       "      <th>feature_permutaion_importance.evi2-1</th>\n",
       "      <th>feature_permutaion_importance.evi2_diff</th>\n",
       "      <th>feature_permutaion_importance.evi2_max_diff</th>\n",
       "      <th>feature_permutaion_importance.evi2_raster</th>\n",
       "      <th>feature_permutaion_importance.evi2_raster-1</th>\n",
       "      <th>feature_permutaion_importance.evi2_raster_diff</th>\n",
       "      <th>feature_permutaion_importance.evi2_vegetation_raster</th>\n",
       "      <th>feature_permutaion_importance.evi2_vegetation_raster-1</th>\n",
       "      <th>feature_permutaion_importance.evi2_vegetation_raster_diff</th>\n",
       "      <th>feature_permutaion_importance.ndvi</th>\n",
       "      <th>feature_permutaion_importance.ndvi-1</th>\n",
       "      <th>feature_permutaion_importance.ndvi_diff</th>\n",
       "      <th>metrics.auc</th>\n",
       "      <th>metrics.roc.threshold</th>\n",
       "      <th>metrics.roc.cohen_kappa</th>\n",
       "      <th>metrics.roc.f1</th>\n",
       "      <th>metrics.roc.recall</th>\n",
       "      <th>metrics.roc.precision</th>\n",
       "      <th>metrics.roc.tn</th>\n",
       "      <th>metrics.roc.fp</th>\n",
       "      <th>metrics.roc.fn</th>\n",
       "      <th>metrics.roc.tp</th>\n",
       "      <th>metrics.prc.threshold</th>\n",
       "      <th>metrics.prc.cohen_kappa</th>\n",
       "      <th>metrics.prc.f1</th>\n",
       "      <th>metrics.prc.recall</th>\n",
       "      <th>metrics.prc.precision</th>\n",
       "      <th>metrics.prc.tn</th>\n",
       "      <th>metrics.prc.fp</th>\n",
       "      <th>metrics.prc.fn</th>\n",
       "      <th>metrics.prc.tp</th>\n",
       "      <th>metrics.tuning.threshold</th>\n",
       "      <th>metrics.tuning.cohen_kappa</th>\n",
       "      <th>metrics.tuning.f1</th>\n",
       "      <th>metrics.tuning.recall</th>\n",
       "      <th>metrics.tuning.precision</th>\n",
       "      <th>metrics.tuning.tn</th>\n",
       "      <th>metrics.tuning.fp</th>\n",
       "      <th>metrics.tuning.fn</th>\n",
       "      <th>metrics.tuning.tp</th>\n",
       "      <th>params.splitter</th>\n",
       "      <th>params.min_weight_fraction_leaf</th>\n",
       "      <th>params.min_impurity_decrease</th>\n",
       "      <th>params.max_leaf_nodes</th>\n",
       "      <th>params.criterion</th>\n",
       "      <th>params.ccp_alpha</th>\n",
       "      <th>params.weights</th>\n",
       "      <th>params.p</th>\n",
       "      <th>params.n_neighbors</th>\n",
       "      <th>params.metric</th>\n",
       "      <th>params.leaf_size</th>\n",
       "      <th>params.algorithm</th>\n",
       "      <th>params.tol</th>\n",
       "      <th>params.shrinking</th>\n",
       "      <th>params.probability</th>\n",
       "      <th>params.kernel</th>\n",
       "      <th>params.gamma</th>\n",
       "      <th>params.decision_function_shape</th>\n",
       "      <th>params.C</th>\n",
       "      <th>params.replacement</th>\n",
       "      <th>params.learning_rate</th>\n",
       "      <th>params.subsample</th>\n",
       "      <th>params.seed</th>\n",
       "      <th>params.scale_pos_weight</th>\n",
       "      <th>params.objective</th>\n",
       "      <th>params.lambda</th>\n",
       "      <th>params.eval_metric</th>\n",
       "      <th>params.colsample_bytree</th>\n",
       "      <th>params.scoring</th>\n",
       "      <th>params.max_iter</th>\n",
       "      <th>params.loss</th>\n",
       "      <th>params.l2_regularization</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>RandomForestClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_2, location_cluster_3, locat...</td>\n",
       "      <td>False</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>160.0</td>\n",
       "      <td>1.593548</td>\n",
       "      <td>0.728614</td>\n",
       "      <td>0.009460</td>\n",
       "      <td>0.008265</td>\n",
       "      <td>0.029235</td>\n",
       "      <td>0.003486</td>\n",
       "      <td>-0.003369</td>\n",
       "      <td>0.002145</td>\n",
       "      <td>0.088365</td>\n",
       "      <td>0.001087</td>\n",
       "      <td>-0.001318</td>\n",
       "      <td>0.011893</td>\n",
       "      <td>0.010797</td>\n",
       "      <td>0.008939</td>\n",
       "      <td>0.009473</td>\n",
       "      <td>0.004997</td>\n",
       "      <td>-0.000839</td>\n",
       "      <td>0.018223</td>\n",
       "      <td>0.001142</td>\n",
       "      <td>0.011244</td>\n",
       "      <td>0.001901</td>\n",
       "      <td>0.001286</td>\n",
       "      <td>-0.003597</td>\n",
       "      <td>-0.001993</td>\n",
       "      <td>0.037384</td>\n",
       "      <td>0.011231</td>\n",
       "      <td>0.012514</td>\n",
       "      <td>-0.000894</td>\n",
       "      <td>0.012851</td>\n",
       "      <td>0.005714</td>\n",
       "      <td>0.690244</td>\n",
       "      <td>0.467516</td>\n",
       "      <td>0.305956</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>0.880126</td>\n",
       "      <td>0.920792</td>\n",
       "      <td>63</td>\n",
       "      <td>72</td>\n",
       "      <td>114</td>\n",
       "      <td>837</td>\n",
       "      <td>0.747734</td>\n",
       "      <td>-0.001843</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>134</td>\n",
       "      <td>1</td>\n",
       "      <td>951</td>\n",
       "      <td>0</td>\n",
       "      <td>0.201</td>\n",
       "      <td>0.097081</td>\n",
       "      <td>0.936884</td>\n",
       "      <td>0.998948</td>\n",
       "      <td>0.882080</td>\n",
       "      <td>8</td>\n",
       "      <td>127</td>\n",
       "      <td>1</td>\n",
       "      <td>950</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>BalancedRandomForestClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_0, location_cluster_1, locat...</td>\n",
       "      <td>False</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>336.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>240.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.003626</td>\n",
       "      <td>-0.013554</td>\n",
       "      <td>-0.002099</td>\n",
       "      <td>0.021695</td>\n",
       "      <td>-0.001104</td>\n",
       "      <td>0.019306</td>\n",
       "      <td>0.003039</td>\n",
       "      <td>-0.003837</td>\n",
       "      <td>0.001084</td>\n",
       "      <td>-0.002472</td>\n",
       "      <td>0.001365</td>\n",
       "      <td>0.001476</td>\n",
       "      <td>0.001208</td>\n",
       "      <td>0.005625</td>\n",
       "      <td>-0.001809</td>\n",
       "      <td>0.000134</td>\n",
       "      <td>-0.001613</td>\n",
       "      <td>-0.001695</td>\n",
       "      <td>-0.013254</td>\n",
       "      <td>0.001712</td>\n",
       "      <td>-0.007799</td>\n",
       "      <td>-0.000499</td>\n",
       "      <td>0.001673</td>\n",
       "      <td>-0.001437</td>\n",
       "      <td>-0.000738</td>\n",
       "      <td>-0.002202</td>\n",
       "      <td>0.001486</td>\n",
       "      <td>-0.009569</td>\n",
       "      <td>0.690408</td>\n",
       "      <td>0.553150</td>\n",
       "      <td>0.276460</td>\n",
       "      <td>0.878587</td>\n",
       "      <td>0.837014</td>\n",
       "      <td>0.924506</td>\n",
       "      <td>70</td>\n",
       "      <td>65</td>\n",
       "      <td>155</td>\n",
       "      <td>796</td>\n",
       "      <td>0.398322</td>\n",
       "      <td>0.234950</td>\n",
       "      <td>0.935807</td>\n",
       "      <td>0.981073</td>\n",
       "      <td>0.894535</td>\n",
       "      <td>25</td>\n",
       "      <td>110</td>\n",
       "      <td>18</td>\n",
       "      <td>933</td>\n",
       "      <td>0.396</td>\n",
       "      <td>0.234950</td>\n",
       "      <td>0.935807</td>\n",
       "      <td>0.981073</td>\n",
       "      <td>0.894535</td>\n",
       "      <td>25</td>\n",
       "      <td>110</td>\n",
       "      <td>18</td>\n",
       "      <td>933</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>DecisionTreeClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_13, tree_1, evi2, evi2_diff,...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>log2</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.593548</td>\n",
       "      <td>0.728614</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.022008</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.010937</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.006422</td>\n",
       "      <td>0.003467</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.000761</td>\n",
       "      <td>-0.001658</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.004509</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004536</td>\n",
       "      <td>-0.004337</td>\n",
       "      <td>0.004458</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.584819</td>\n",
       "      <td>0.531989</td>\n",
       "      <td>0.065295</td>\n",
       "      <td>0.541387</td>\n",
       "      <td>0.381703</td>\n",
       "      <td>0.930769</td>\n",
       "      <td>108</td>\n",
       "      <td>27</td>\n",
       "      <td>588</td>\n",
       "      <td>363</td>\n",
       "      <td>0.449369</td>\n",
       "      <td>0.178185</td>\n",
       "      <td>0.936847</td>\n",
       "      <td>0.990536</td>\n",
       "      <td>0.888679</td>\n",
       "      <td>17</td>\n",
       "      <td>118</td>\n",
       "      <td>9</td>\n",
       "      <td>942</td>\n",
       "      <td>0.445</td>\n",
       "      <td>0.178185</td>\n",
       "      <td>0.936847</td>\n",
       "      <td>0.990536</td>\n",
       "      <td>0.888679</td>\n",
       "      <td>17</td>\n",
       "      <td>118</td>\n",
       "      <td>9</td>\n",
       "      <td>942</td>\n",
       "      <td>best</td>\n",
       "      <td>0.45</td>\n",
       "      <td>0.00</td>\n",
       "      <td>97.0</td>\n",
       "      <td>gini</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>KNeighborsClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_0, location_cluster_1, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.011434</td>\n",
       "      <td>0.010601</td>\n",
       "      <td>0.035132</td>\n",
       "      <td>-0.049829</td>\n",
       "      <td>0.004990</td>\n",
       "      <td>0.000826</td>\n",
       "      <td>0.008849</td>\n",
       "      <td>0.004184</td>\n",
       "      <td>0.005672</td>\n",
       "      <td>0.016174</td>\n",
       "      <td>-0.003821</td>\n",
       "      <td>0.007294</td>\n",
       "      <td>-0.005414</td>\n",
       "      <td>-0.003932</td>\n",
       "      <td>-0.004766</td>\n",
       "      <td>0.000967</td>\n",
       "      <td>0.000827</td>\n",
       "      <td>0.004385</td>\n",
       "      <td>0.004153</td>\n",
       "      <td>0.027839</td>\n",
       "      <td>0.000540</td>\n",
       "      <td>0.021086</td>\n",
       "      <td>-0.013395</td>\n",
       "      <td>0.012266</td>\n",
       "      <td>-0.015339</td>\n",
       "      <td>-0.003157</td>\n",
       "      <td>0.006501</td>\n",
       "      <td>-0.007430</td>\n",
       "      <td>0.567251</td>\n",
       "      <td>0.381755</td>\n",
       "      <td>0.099720</td>\n",
       "      <td>0.707175</td>\n",
       "      <td>0.575184</td>\n",
       "      <td>0.917785</td>\n",
       "      <td>86</td>\n",
       "      <td>49</td>\n",
       "      <td>404</td>\n",
       "      <td>547</td>\n",
       "      <td>0.060915</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.933726</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.875691</td>\n",
       "      <td>0</td>\n",
       "      <td>135</td>\n",
       "      <td>0</td>\n",
       "      <td>951</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.933726</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.875691</td>\n",
       "      <td>0</td>\n",
       "      <td>135</td>\n",
       "      <td>0</td>\n",
       "      <td>951</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>distance</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>manhattan</td>\n",
       "      <td>44.0</td>\n",
       "      <td>brute</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>SVM</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_0, location_cluster_1, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.593548</td>\n",
       "      <td>0.728614</td>\n",
       "      <td>-0.012784</td>\n",
       "      <td>-0.006916</td>\n",
       "      <td>0.006494</td>\n",
       "      <td>-0.025448</td>\n",
       "      <td>0.021316</td>\n",
       "      <td>-0.023937</td>\n",
       "      <td>-0.030311</td>\n",
       "      <td>-0.019667</td>\n",
       "      <td>-0.012161</td>\n",
       "      <td>-0.023627</td>\n",
       "      <td>-0.023179</td>\n",
       "      <td>-0.004984</td>\n",
       "      <td>-0.015227</td>\n",
       "      <td>-0.033112</td>\n",
       "      <td>-0.011806</td>\n",
       "      <td>-0.019818</td>\n",
       "      <td>-0.011077</td>\n",
       "      <td>-0.022573</td>\n",
       "      <td>-0.023932</td>\n",
       "      <td>0.015720</td>\n",
       "      <td>-0.010409</td>\n",
       "      <td>-0.014905</td>\n",
       "      <td>-0.007121</td>\n",
       "      <td>0.003145</td>\n",
       "      <td>-0.019670</td>\n",
       "      <td>-0.011970</td>\n",
       "      <td>-0.008887</td>\n",
       "      <td>-0.005802</td>\n",
       "      <td>0.652872</td>\n",
       "      <td>0.431184</td>\n",
       "      <td>0.170072</td>\n",
       "      <td>0.830080</td>\n",
       "      <td>0.760252</td>\n",
       "      <td>0.914033</td>\n",
       "      <td>67</td>\n",
       "      <td>68</td>\n",
       "      <td>228</td>\n",
       "      <td>723</td>\n",
       "      <td>0.095497</td>\n",
       "      <td>0.025661</td>\n",
       "      <td>0.934644</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.877306</td>\n",
       "      <td>2</td>\n",
       "      <td>133</td>\n",
       "      <td>0</td>\n",
       "      <td>951</td>\n",
       "      <td>0.081</td>\n",
       "      <td>0.025661</td>\n",
       "      <td>0.934644</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.877306</td>\n",
       "      <td>2</td>\n",
       "      <td>133</td>\n",
       "      <td>0</td>\n",
       "      <td>951</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.006</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>rbf</td>\n",
       "      <td>0.811</td>\n",
       "      <td>ovo</td>\n",
       "      <td>2.85</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>RUSBoostClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_0, location_cluster_1, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>470.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.000487</td>\n",
       "      <td>-0.002657</td>\n",
       "      <td>0.024363</td>\n",
       "      <td>0.012437</td>\n",
       "      <td>0.029213</td>\n",
       "      <td>-0.003944</td>\n",
       "      <td>-0.000759</td>\n",
       "      <td>0.006040</td>\n",
       "      <td>0.004672</td>\n",
       "      <td>-0.000280</td>\n",
       "      <td>-0.000062</td>\n",
       "      <td>0.004921</td>\n",
       "      <td>0.011451</td>\n",
       "      <td>0.003604</td>\n",
       "      <td>0.002243</td>\n",
       "      <td>-0.001348</td>\n",
       "      <td>0.011709</td>\n",
       "      <td>-0.015896</td>\n",
       "      <td>-0.007951</td>\n",
       "      <td>0.010957</td>\n",
       "      <td>0.000346</td>\n",
       "      <td>0.012503</td>\n",
       "      <td>0.004125</td>\n",
       "      <td>0.008712</td>\n",
       "      <td>-0.000463</td>\n",
       "      <td>-0.015372</td>\n",
       "      <td>0.017436</td>\n",
       "      <td>-0.001926</td>\n",
       "      <td>0.665693</td>\n",
       "      <td>0.496916</td>\n",
       "      <td>0.283560</td>\n",
       "      <td>0.892258</td>\n",
       "      <td>0.866456</td>\n",
       "      <td>0.919643</td>\n",
       "      <td>63</td>\n",
       "      <td>72</td>\n",
       "      <td>127</td>\n",
       "      <td>824</td>\n",
       "      <td>0.471729</td>\n",
       "      <td>0.292451</td>\n",
       "      <td>0.944167</td>\n",
       "      <td>0.995794</td>\n",
       "      <td>0.897630</td>\n",
       "      <td>27</td>\n",
       "      <td>108</td>\n",
       "      <td>4</td>\n",
       "      <td>947</td>\n",
       "      <td>0.471</td>\n",
       "      <td>0.292451</td>\n",
       "      <td>0.944167</td>\n",
       "      <td>0.995794</td>\n",
       "      <td>0.897630</td>\n",
       "      <td>27</td>\n",
       "      <td>108</td>\n",
       "      <td>4</td>\n",
       "      <td>947</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAMME.R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>0.0930</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>AdaBoostClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_0, location_cluster_1, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>380.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.003410</td>\n",
       "      <td>0.005938</td>\n",
       "      <td>0.001683</td>\n",
       "      <td>-0.004812</td>\n",
       "      <td>0.021041</td>\n",
       "      <td>-0.003338</td>\n",
       "      <td>0.008629</td>\n",
       "      <td>0.007617</td>\n",
       "      <td>-0.002306</td>\n",
       "      <td>0.001477</td>\n",
       "      <td>0.002381</td>\n",
       "      <td>-0.004790</td>\n",
       "      <td>0.001432</td>\n",
       "      <td>0.004133</td>\n",
       "      <td>0.004810</td>\n",
       "      <td>0.004133</td>\n",
       "      <td>-0.005509</td>\n",
       "      <td>-0.007961</td>\n",
       "      <td>0.001783</td>\n",
       "      <td>-0.031217</td>\n",
       "      <td>-0.011863</td>\n",
       "      <td>-0.001284</td>\n",
       "      <td>0.006566</td>\n",
       "      <td>-0.022133</td>\n",
       "      <td>-0.033335</td>\n",
       "      <td>-0.021963</td>\n",
       "      <td>0.010151</td>\n",
       "      <td>-0.001908</td>\n",
       "      <td>0.702559</td>\n",
       "      <td>0.503444</td>\n",
       "      <td>0.155997</td>\n",
       "      <td>0.712975</td>\n",
       "      <td>0.572029</td>\n",
       "      <td>0.946087</td>\n",
       "      <td>104</td>\n",
       "      <td>31</td>\n",
       "      <td>407</td>\n",
       "      <td>544</td>\n",
       "      <td>0.491952</td>\n",
       "      <td>0.434160</td>\n",
       "      <td>0.945547</td>\n",
       "      <td>0.976866</td>\n",
       "      <td>0.916174</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>22</td>\n",
       "      <td>929</td>\n",
       "      <td>0.491</td>\n",
       "      <td>0.412532</td>\n",
       "      <td>0.945233</td>\n",
       "      <td>0.980021</td>\n",
       "      <td>0.912831</td>\n",
       "      <td>46</td>\n",
       "      <td>89</td>\n",
       "      <td>19</td>\n",
       "      <td>932</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAMME.R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.4000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>XGBClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_1, location_cluster_2, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>335.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.004427</td>\n",
       "      <td>0.005848</td>\n",
       "      <td>0.011533</td>\n",
       "      <td>0.014200</td>\n",
       "      <td>0.016922</td>\n",
       "      <td>-0.000201</td>\n",
       "      <td>0.019756</td>\n",
       "      <td>0.015057</td>\n",
       "      <td>0.001397</td>\n",
       "      <td>0.003132</td>\n",
       "      <td>0.081817</td>\n",
       "      <td>0.002327</td>\n",
       "      <td>0.000075</td>\n",
       "      <td>0.012967</td>\n",
       "      <td>0.004429</td>\n",
       "      <td>0.001601</td>\n",
       "      <td>0.011393</td>\n",
       "      <td>0.009522</td>\n",
       "      <td>0.002994</td>\n",
       "      <td>-0.000140</td>\n",
       "      <td>-0.000605</td>\n",
       "      <td>0.000636</td>\n",
       "      <td>0.004293</td>\n",
       "      <td>0.003269</td>\n",
       "      <td>0.011106</td>\n",
       "      <td>0.018105</td>\n",
       "      <td>0.017290</td>\n",
       "      <td>0.025867</td>\n",
       "      <td>0.783900</td>\n",
       "      <td>0.541763</td>\n",
       "      <td>0.296770</td>\n",
       "      <td>0.860240</td>\n",
       "      <td>0.792850</td>\n",
       "      <td>0.940150</td>\n",
       "      <td>87</td>\n",
       "      <td>48</td>\n",
       "      <td>197</td>\n",
       "      <td>754</td>\n",
       "      <td>0.212362</td>\n",
       "      <td>0.305085</td>\n",
       "      <td>0.945165</td>\n",
       "      <td>0.996845</td>\n",
       "      <td>0.898578</td>\n",
       "      <td>28</td>\n",
       "      <td>107</td>\n",
       "      <td>3</td>\n",
       "      <td>948</td>\n",
       "      <td>0.212</td>\n",
       "      <td>0.305085</td>\n",
       "      <td>0.945165</td>\n",
       "      <td>0.996845</td>\n",
       "      <td>0.898578</td>\n",
       "      <td>28</td>\n",
       "      <td>107</td>\n",
       "      <td>3</td>\n",
       "      <td>948</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.650</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0090</td>\n",
       "      <td>0.95</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>2.187097</td>\n",
       "      <td>binary:logistic</td>\n",
       "      <td>0.6</td>\n",
       "      <td>auc</td>\n",
       "      <td>0.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>HistGradientBoostingClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_0, location_cluster_1, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>78.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.016143</td>\n",
       "      <td>0.009234</td>\n",
       "      <td>0.023351</td>\n",
       "      <td>0.026779</td>\n",
       "      <td>0.092038</td>\n",
       "      <td>-0.002569</td>\n",
       "      <td>0.001619</td>\n",
       "      <td>0.010727</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>-0.001888</td>\n",
       "      <td>0.001758</td>\n",
       "      <td>0.002429</td>\n",
       "      <td>0.016045</td>\n",
       "      <td>0.013583</td>\n",
       "      <td>-0.001758</td>\n",
       "      <td>0.002998</td>\n",
       "      <td>0.013846</td>\n",
       "      <td>0.003334</td>\n",
       "      <td>0.003562</td>\n",
       "      <td>0.005522</td>\n",
       "      <td>-0.003582</td>\n",
       "      <td>0.031415</td>\n",
       "      <td>0.000268</td>\n",
       "      <td>0.011137</td>\n",
       "      <td>0.011338</td>\n",
       "      <td>-0.002023</td>\n",
       "      <td>0.000405</td>\n",
       "      <td>0.013332</td>\n",
       "      <td>0.662881</td>\n",
       "      <td>0.421783</td>\n",
       "      <td>0.371241</td>\n",
       "      <td>0.914803</td>\n",
       "      <td>0.903260</td>\n",
       "      <td>0.926645</td>\n",
       "      <td>67</td>\n",
       "      <td>68</td>\n",
       "      <td>92</td>\n",
       "      <td>859</td>\n",
       "      <td>0.116349</td>\n",
       "      <td>0.327367</td>\n",
       "      <td>0.945527</td>\n",
       "      <td>0.994742</td>\n",
       "      <td>0.900952</td>\n",
       "      <td>31</td>\n",
       "      <td>104</td>\n",
       "      <td>5</td>\n",
       "      <td>946</td>\n",
       "      <td>0.115</td>\n",
       "      <td>0.327367</td>\n",
       "      <td>0.945527</td>\n",
       "      <td>0.994742</td>\n",
       "      <td>0.900952</td>\n",
       "      <td>31</td>\n",
       "      <td>104</td>\n",
       "      <td>5</td>\n",
       "      <td>946</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>106.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0365</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>roc_auc</td>\n",
       "      <td>350.0</td>\n",
       "      <td>binary_crossentropy</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>RandomForestClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_1, location_cluster_2, locat...</td>\n",
       "      <td>True</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>192.0</td>\n",
       "      <td>1.699173</td>\n",
       "      <td>0.708477</td>\n",
       "      <td>-0.003764</td>\n",
       "      <td>0.002226</td>\n",
       "      <td>0.017508</td>\n",
       "      <td>0.017346</td>\n",
       "      <td>0.005245</td>\n",
       "      <td>0.008114</td>\n",
       "      <td>0.006452</td>\n",
       "      <td>0.006280</td>\n",
       "      <td>0.005139</td>\n",
       "      <td>0.025841</td>\n",
       "      <td>0.000659</td>\n",
       "      <td>0.002543</td>\n",
       "      <td>-0.003963</td>\n",
       "      <td>0.002949</td>\n",
       "      <td>-0.004935</td>\n",
       "      <td>-0.012632</td>\n",
       "      <td>0.004803</td>\n",
       "      <td>0.004411</td>\n",
       "      <td>0.000079</td>\n",
       "      <td>-0.009609</td>\n",
       "      <td>-0.001341</td>\n",
       "      <td>-0.016142</td>\n",
       "      <td>0.053487</td>\n",
       "      <td>-0.000466</td>\n",
       "      <td>-0.007563</td>\n",
       "      <td>-0.001486</td>\n",
       "      <td>0.004112</td>\n",
       "      <td>0.005183</td>\n",
       "      <td>0.758450</td>\n",
       "      <td>0.438095</td>\n",
       "      <td>0.444266</td>\n",
       "      <td>0.921466</td>\n",
       "      <td>0.914661</td>\n",
       "      <td>0.928373</td>\n",
       "      <td>156</td>\n",
       "      <td>129</td>\n",
       "      <td>156</td>\n",
       "      <td>1672</td>\n",
       "      <td>0.339557</td>\n",
       "      <td>0.515887</td>\n",
       "      <td>0.949618</td>\n",
       "      <td>0.984683</td>\n",
       "      <td>0.916964</td>\n",
       "      <td>122</td>\n",
       "      <td>163</td>\n",
       "      <td>28</td>\n",
       "      <td>1800</td>\n",
       "      <td>0.339</td>\n",
       "      <td>0.515887</td>\n",
       "      <td>0.949618</td>\n",
       "      <td>0.984683</td>\n",
       "      <td>0.916964</td>\n",
       "      <td>122</td>\n",
       "      <td>163</td>\n",
       "      <td>28</td>\n",
       "      <td>1800</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>BalancedRandomForestClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_0, location_cluster_1, locat...</td>\n",
       "      <td>False</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>464.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>144.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.004779</td>\n",
       "      <td>0.004870</td>\n",
       "      <td>0.001050</td>\n",
       "      <td>0.009145</td>\n",
       "      <td>0.032036</td>\n",
       "      <td>-0.001695</td>\n",
       "      <td>-0.002828</td>\n",
       "      <td>0.005287</td>\n",
       "      <td>0.001274</td>\n",
       "      <td>0.005010</td>\n",
       "      <td>0.001978</td>\n",
       "      <td>0.004352</td>\n",
       "      <td>0.001401</td>\n",
       "      <td>0.000654</td>\n",
       "      <td>0.000889</td>\n",
       "      <td>-0.000248</td>\n",
       "      <td>0.014010</td>\n",
       "      <td>0.014017</td>\n",
       "      <td>0.002659</td>\n",
       "      <td>-0.002226</td>\n",
       "      <td>-0.001270</td>\n",
       "      <td>-0.004219</td>\n",
       "      <td>0.003065</td>\n",
       "      <td>0.018624</td>\n",
       "      <td>0.002761</td>\n",
       "      <td>-0.003868</td>\n",
       "      <td>0.000560</td>\n",
       "      <td>-0.002154</td>\n",
       "      <td>0.725305</td>\n",
       "      <td>0.524421</td>\n",
       "      <td>0.314680</td>\n",
       "      <td>0.886750</td>\n",
       "      <td>0.856674</td>\n",
       "      <td>0.919014</td>\n",
       "      <td>147</td>\n",
       "      <td>138</td>\n",
       "      <td>262</td>\n",
       "      <td>1566</td>\n",
       "      <td>0.313176</td>\n",
       "      <td>0.295998</td>\n",
       "      <td>0.940206</td>\n",
       "      <td>0.997812</td>\n",
       "      <td>0.888889</td>\n",
       "      <td>57</td>\n",
       "      <td>228</td>\n",
       "      <td>4</td>\n",
       "      <td>1824</td>\n",
       "      <td>0.311</td>\n",
       "      <td>0.295998</td>\n",
       "      <td>0.940206</td>\n",
       "      <td>0.997812</td>\n",
       "      <td>0.888889</td>\n",
       "      <td>57</td>\n",
       "      <td>228</td>\n",
       "      <td>4</td>\n",
       "      <td>1824</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>DecisionTreeClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_1, location_cluster_2, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.699173</td>\n",
       "      <td>0.708477</td>\n",
       "      <td>0.023772</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.033987</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.011386</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.569515</td>\n",
       "      <td>0.515043</td>\n",
       "      <td>0.093012</td>\n",
       "      <td>0.790641</td>\n",
       "      <td>0.711707</td>\n",
       "      <td>0.889269</td>\n",
       "      <td>123</td>\n",
       "      <td>162</td>\n",
       "      <td>527</td>\n",
       "      <td>1301</td>\n",
       "      <td>0.370111</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.927683</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.865121</td>\n",
       "      <td>0</td>\n",
       "      <td>285</td>\n",
       "      <td>0</td>\n",
       "      <td>1828</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.927683</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.865121</td>\n",
       "      <td>0</td>\n",
       "      <td>285</td>\n",
       "      <td>0</td>\n",
       "      <td>1828</td>\n",
       "      <td>best</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.05</td>\n",
       "      <td>1249.0</td>\n",
       "      <td>gini</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>KNeighborsClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_2, location_cluster_4, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.004681</td>\n",
       "      <td>0.015648</td>\n",
       "      <td>0.030691</td>\n",
       "      <td>0.003218</td>\n",
       "      <td>0.003916</td>\n",
       "      <td>0.002426</td>\n",
       "      <td>0.013638</td>\n",
       "      <td>0.004032</td>\n",
       "      <td>0.011037</td>\n",
       "      <td>0.032031</td>\n",
       "      <td>0.005326</td>\n",
       "      <td>0.001924</td>\n",
       "      <td>0.009202</td>\n",
       "      <td>0.012475</td>\n",
       "      <td>0.000635</td>\n",
       "      <td>-0.005101</td>\n",
       "      <td>0.002956</td>\n",
       "      <td>-0.005027</td>\n",
       "      <td>-0.014088</td>\n",
       "      <td>0.007074</td>\n",
       "      <td>0.006476</td>\n",
       "      <td>0.002143</td>\n",
       "      <td>-0.000709</td>\n",
       "      <td>0.007467</td>\n",
       "      <td>0.007517</td>\n",
       "      <td>0.004170</td>\n",
       "      <td>0.001273</td>\n",
       "      <td>0.027289</td>\n",
       "      <td>0.679513</td>\n",
       "      <td>0.516775</td>\n",
       "      <td>0.170691</td>\n",
       "      <td>0.781270</td>\n",
       "      <td>0.679978</td>\n",
       "      <td>0.918021</td>\n",
       "      <td>174</td>\n",
       "      <td>111</td>\n",
       "      <td>585</td>\n",
       "      <td>1243</td>\n",
       "      <td>0.126562</td>\n",
       "      <td>0.318603</td>\n",
       "      <td>0.939103</td>\n",
       "      <td>0.991247</td>\n",
       "      <td>0.892171</td>\n",
       "      <td>66</td>\n",
       "      <td>219</td>\n",
       "      <td>16</td>\n",
       "      <td>1812</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.318603</td>\n",
       "      <td>0.939103</td>\n",
       "      <td>0.991247</td>\n",
       "      <td>0.892171</td>\n",
       "      <td>66</td>\n",
       "      <td>219</td>\n",
       "      <td>16</td>\n",
       "      <td>1812</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>distance</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>manhattan</td>\n",
       "      <td>30.0</td>\n",
       "      <td>kd_tree</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>SVM</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_4, location_cluster_5, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.699173</td>\n",
       "      <td>0.708477</td>\n",
       "      <td>0.011658</td>\n",
       "      <td>0.018860</td>\n",
       "      <td>0.004188</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.005520</td>\n",
       "      <td>-0.002057</td>\n",
       "      <td>0.005065</td>\n",
       "      <td>-0.002901</td>\n",
       "      <td>0.005624</td>\n",
       "      <td>-0.002568</td>\n",
       "      <td>0.005196</td>\n",
       "      <td>0.001105</td>\n",
       "      <td>0.007064</td>\n",
       "      <td>0.006913</td>\n",
       "      <td>0.004687</td>\n",
       "      <td>-0.003721</td>\n",
       "      <td>-0.003876</td>\n",
       "      <td>0.000973</td>\n",
       "      <td>0.004677</td>\n",
       "      <td>0.013943</td>\n",
       "      <td>0.033446</td>\n",
       "      <td>-0.006984</td>\n",
       "      <td>-0.003680</td>\n",
       "      <td>0.003769</td>\n",
       "      <td>0.003971</td>\n",
       "      <td>-0.001314</td>\n",
       "      <td>-0.006187</td>\n",
       "      <td>-0.003115</td>\n",
       "      <td>0.728485</td>\n",
       "      <td>0.362802</td>\n",
       "      <td>0.347280</td>\n",
       "      <td>0.899329</td>\n",
       "      <td>0.879650</td>\n",
       "      <td>0.919908</td>\n",
       "      <td>145</td>\n",
       "      <td>140</td>\n",
       "      <td>220</td>\n",
       "      <td>1608</td>\n",
       "      <td>0.198932</td>\n",
       "      <td>0.291811</td>\n",
       "      <td>0.938807</td>\n",
       "      <td>0.994530</td>\n",
       "      <td>0.888998</td>\n",
       "      <td>58</td>\n",
       "      <td>227</td>\n",
       "      <td>10</td>\n",
       "      <td>1818</td>\n",
       "      <td>0.197</td>\n",
       "      <td>0.287268</td>\n",
       "      <td>0.938565</td>\n",
       "      <td>0.994530</td>\n",
       "      <td>0.888563</td>\n",
       "      <td>57</td>\n",
       "      <td>228</td>\n",
       "      <td>10</td>\n",
       "      <td>1818</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.007</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>rbf</td>\n",
       "      <td>0.816</td>\n",
       "      <td>ovo</td>\n",
       "      <td>4.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>RUSBoostClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_1, location_cluster_4, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>440.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.004852</td>\n",
       "      <td>-0.000213</td>\n",
       "      <td>0.020012</td>\n",
       "      <td>0.001645</td>\n",
       "      <td>-0.000099</td>\n",
       "      <td>-0.003129</td>\n",
       "      <td>0.005734</td>\n",
       "      <td>-0.006499</td>\n",
       "      <td>0.004405</td>\n",
       "      <td>0.002659</td>\n",
       "      <td>-0.002168</td>\n",
       "      <td>-0.004200</td>\n",
       "      <td>-0.000236</td>\n",
       "      <td>0.007986</td>\n",
       "      <td>-0.002892</td>\n",
       "      <td>-0.000850</td>\n",
       "      <td>0.004435</td>\n",
       "      <td>-0.004612</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>-0.004260</td>\n",
       "      <td>-0.004340</td>\n",
       "      <td>-0.002815</td>\n",
       "      <td>-0.009306</td>\n",
       "      <td>0.003159</td>\n",
       "      <td>0.008444</td>\n",
       "      <td>0.007191</td>\n",
       "      <td>0.005143</td>\n",
       "      <td>-0.000260</td>\n",
       "      <td>0.748870</td>\n",
       "      <td>0.495588</td>\n",
       "      <td>0.328321</td>\n",
       "      <td>0.888322</td>\n",
       "      <td>0.857221</td>\n",
       "      <td>0.921765</td>\n",
       "      <td>152</td>\n",
       "      <td>133</td>\n",
       "      <td>261</td>\n",
       "      <td>1567</td>\n",
       "      <td>0.486012</td>\n",
       "      <td>0.365151</td>\n",
       "      <td>0.939734</td>\n",
       "      <td>0.985230</td>\n",
       "      <td>0.898254</td>\n",
       "      <td>81</td>\n",
       "      <td>204</td>\n",
       "      <td>27</td>\n",
       "      <td>1801</td>\n",
       "      <td>0.486</td>\n",
       "      <td>0.365151</td>\n",
       "      <td>0.939734</td>\n",
       "      <td>0.985230</td>\n",
       "      <td>0.898254</td>\n",
       "      <td>81</td>\n",
       "      <td>204</td>\n",
       "      <td>27</td>\n",
       "      <td>1801</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAMME.R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>0.0810</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>AdaBoostClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_1, location_cluster_4, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>455.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.010999</td>\n",
       "      <td>-0.005769</td>\n",
       "      <td>0.005227</td>\n",
       "      <td>-0.008347</td>\n",
       "      <td>0.004845</td>\n",
       "      <td>-0.003998</td>\n",
       "      <td>-0.004382</td>\n",
       "      <td>-0.011932</td>\n",
       "      <td>-0.000569</td>\n",
       "      <td>-0.001937</td>\n",
       "      <td>0.009068</td>\n",
       "      <td>0.001392</td>\n",
       "      <td>0.003139</td>\n",
       "      <td>0.012200</td>\n",
       "      <td>0.003412</td>\n",
       "      <td>-0.001516</td>\n",
       "      <td>-0.004001</td>\n",
       "      <td>-0.003510</td>\n",
       "      <td>-0.005062</td>\n",
       "      <td>0.000411</td>\n",
       "      <td>0.033237</td>\n",
       "      <td>0.000382</td>\n",
       "      <td>-0.000464</td>\n",
       "      <td>-0.006981</td>\n",
       "      <td>0.001861</td>\n",
       "      <td>-0.004327</td>\n",
       "      <td>0.005809</td>\n",
       "      <td>0.004101</td>\n",
       "      <td>0.748238</td>\n",
       "      <td>0.498755</td>\n",
       "      <td>0.248933</td>\n",
       "      <td>0.840191</td>\n",
       "      <td>0.770788</td>\n",
       "      <td>0.923329</td>\n",
       "      <td>168</td>\n",
       "      <td>117</td>\n",
       "      <td>419</td>\n",
       "      <td>1409</td>\n",
       "      <td>0.490823</td>\n",
       "      <td>0.169130</td>\n",
       "      <td>0.934799</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.877580</td>\n",
       "      <td>30</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>1828</td>\n",
       "      <td>0.491</td>\n",
       "      <td>0.166579</td>\n",
       "      <td>0.934254</td>\n",
       "      <td>0.998906</td>\n",
       "      <td>0.877463</td>\n",
       "      <td>30</td>\n",
       "      <td>255</td>\n",
       "      <td>2</td>\n",
       "      <td>1826</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAMME.R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.4500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>XGBClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_2, location_cluster_4, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>470.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.004411</td>\n",
       "      <td>0.048451</td>\n",
       "      <td>0.013515</td>\n",
       "      <td>0.010802</td>\n",
       "      <td>0.006152</td>\n",
       "      <td>0.004793</td>\n",
       "      <td>0.007565</td>\n",
       "      <td>0.051413</td>\n",
       "      <td>-0.006609</td>\n",
       "      <td>-0.002993</td>\n",
       "      <td>-0.004954</td>\n",
       "      <td>0.001051</td>\n",
       "      <td>0.003312</td>\n",
       "      <td>-0.001944</td>\n",
       "      <td>-0.007586</td>\n",
       "      <td>0.003994</td>\n",
       "      <td>-0.009274</td>\n",
       "      <td>0.011098</td>\n",
       "      <td>0.014770</td>\n",
       "      <td>-0.008823</td>\n",
       "      <td>-0.003584</td>\n",
       "      <td>-0.009323</td>\n",
       "      <td>0.003365</td>\n",
       "      <td>-0.006693</td>\n",
       "      <td>-0.007375</td>\n",
       "      <td>0.011562</td>\n",
       "      <td>-0.001395</td>\n",
       "      <td>-0.001475</td>\n",
       "      <td>0.725240</td>\n",
       "      <td>0.565510</td>\n",
       "      <td>0.234021</td>\n",
       "      <td>0.822742</td>\n",
       "      <td>0.740153</td>\n",
       "      <td>0.926078</td>\n",
       "      <td>177</td>\n",
       "      <td>108</td>\n",
       "      <td>475</td>\n",
       "      <td>1353</td>\n",
       "      <td>0.134792</td>\n",
       "      <td>0.228249</td>\n",
       "      <td>0.936553</td>\n",
       "      <td>0.997265</td>\n",
       "      <td>0.882809</td>\n",
       "      <td>43</td>\n",
       "      <td>242</td>\n",
       "      <td>5</td>\n",
       "      <td>1823</td>\n",
       "      <td>0.132</td>\n",
       "      <td>0.223353</td>\n",
       "      <td>0.936312</td>\n",
       "      <td>0.997265</td>\n",
       "      <td>0.882381</td>\n",
       "      <td>42</td>\n",
       "      <td>243</td>\n",
       "      <td>5</td>\n",
       "      <td>1823</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.050</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0090</td>\n",
       "      <td>0.90</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>2.398345</td>\n",
       "      <td>binary:logistic</td>\n",
       "      <td>0.1</td>\n",
       "      <td>aucpr</td>\n",
       "      <td>0.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>HistGradientBoostingClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_4, location_cluster_5, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.046188</td>\n",
       "      <td>0.024217</td>\n",
       "      <td>0.004743</td>\n",
       "      <td>0.013470</td>\n",
       "      <td>0.002039</td>\n",
       "      <td>0.006671</td>\n",
       "      <td>0.045956</td>\n",
       "      <td>-0.001327</td>\n",
       "      <td>0.010694</td>\n",
       "      <td>-0.001346</td>\n",
       "      <td>0.001775</td>\n",
       "      <td>0.000891</td>\n",
       "      <td>0.011050</td>\n",
       "      <td>-0.001558</td>\n",
       "      <td>0.012080</td>\n",
       "      <td>-0.005178</td>\n",
       "      <td>-0.007328</td>\n",
       "      <td>-0.000634</td>\n",
       "      <td>0.005701</td>\n",
       "      <td>0.047457</td>\n",
       "      <td>-0.013846</td>\n",
       "      <td>-0.007643</td>\n",
       "      <td>0.001899</td>\n",
       "      <td>-0.018024</td>\n",
       "      <td>-0.007645</td>\n",
       "      <td>0.002013</td>\n",
       "      <td>0.005677</td>\n",
       "      <td>0.019817</td>\n",
       "      <td>0.745651</td>\n",
       "      <td>0.450929</td>\n",
       "      <td>0.320051</td>\n",
       "      <td>0.868982</td>\n",
       "      <td>0.814551</td>\n",
       "      <td>0.931207</td>\n",
       "      <td>175</td>\n",
       "      <td>110</td>\n",
       "      <td>339</td>\n",
       "      <td>1489</td>\n",
       "      <td>0.131199</td>\n",
       "      <td>0.395456</td>\n",
       "      <td>0.943779</td>\n",
       "      <td>0.991794</td>\n",
       "      <td>0.900199</td>\n",
       "      <td>84</td>\n",
       "      <td>201</td>\n",
       "      <td>15</td>\n",
       "      <td>1813</td>\n",
       "      <td>0.131</td>\n",
       "      <td>0.395456</td>\n",
       "      <td>0.943779</td>\n",
       "      <td>0.991794</td>\n",
       "      <td>0.900199</td>\n",
       "      <td>84</td>\n",
       "      <td>201</td>\n",
       "      <td>15</td>\n",
       "      <td>1813</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>99.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0160</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>roc_auc</td>\n",
       "      <td>400.0</td>\n",
       "      <td>binary_crossentropy</td>\n",
       "      <td>0.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>RandomForestClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_0, location_cluster_2, locat...</td>\n",
       "      <td>False</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>384.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.569873</td>\n",
       "      <td>0.733673</td>\n",
       "      <td>-0.008851</td>\n",
       "      <td>-0.003619</td>\n",
       "      <td>-0.004068</td>\n",
       "      <td>-0.018754</td>\n",
       "      <td>-0.012120</td>\n",
       "      <td>-0.004277</td>\n",
       "      <td>-0.003043</td>\n",
       "      <td>-0.017451</td>\n",
       "      <td>-0.008825</td>\n",
       "      <td>-0.000182</td>\n",
       "      <td>0.011630</td>\n",
       "      <td>-0.005726</td>\n",
       "      <td>-0.000294</td>\n",
       "      <td>-0.003884</td>\n",
       "      <td>-0.003208</td>\n",
       "      <td>-0.000756</td>\n",
       "      <td>-0.007505</td>\n",
       "      <td>-0.004863</td>\n",
       "      <td>-0.009545</td>\n",
       "      <td>0.004537</td>\n",
       "      <td>-0.006118</td>\n",
       "      <td>0.000758</td>\n",
       "      <td>0.003678</td>\n",
       "      <td>-0.005409</td>\n",
       "      <td>0.000954</td>\n",
       "      <td>0.001473</td>\n",
       "      <td>-0.001018</td>\n",
       "      <td>0.006035</td>\n",
       "      <td>0.738243</td>\n",
       "      <td>0.577855</td>\n",
       "      <td>0.158175</td>\n",
       "      <td>0.757078</td>\n",
       "      <td>0.627080</td>\n",
       "      <td>0.955069</td>\n",
       "      <td>112</td>\n",
       "      <td>39</td>\n",
       "      <td>493</td>\n",
       "      <td>829</td>\n",
       "      <td>0.294460</td>\n",
       "      <td>0.191548</td>\n",
       "      <td>0.948625</td>\n",
       "      <td>0.991679</td>\n",
       "      <td>0.909154</td>\n",
       "      <td>20</td>\n",
       "      <td>131</td>\n",
       "      <td>11</td>\n",
       "      <td>1311</td>\n",
       "      <td>0.290</td>\n",
       "      <td>0.191548</td>\n",
       "      <td>0.948625</td>\n",
       "      <td>0.991679</td>\n",
       "      <td>0.909154</td>\n",
       "      <td>20</td>\n",
       "      <td>131</td>\n",
       "      <td>11</td>\n",
       "      <td>1311</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>BalancedRandomForestClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_0, location_cluster_3, locat...</td>\n",
       "      <td>True</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>480.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>240.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.002511</td>\n",
       "      <td>-0.001865</td>\n",
       "      <td>0.021229</td>\n",
       "      <td>0.005843</td>\n",
       "      <td>-0.004439</td>\n",
       "      <td>-0.008059</td>\n",
       "      <td>0.021605</td>\n",
       "      <td>-0.000503</td>\n",
       "      <td>0.003406</td>\n",
       "      <td>-0.001937</td>\n",
       "      <td>0.000421</td>\n",
       "      <td>-0.005009</td>\n",
       "      <td>-0.002649</td>\n",
       "      <td>-0.000711</td>\n",
       "      <td>0.008895</td>\n",
       "      <td>0.002375</td>\n",
       "      <td>0.004684</td>\n",
       "      <td>0.000475</td>\n",
       "      <td>-0.000960</td>\n",
       "      <td>0.008051</td>\n",
       "      <td>0.010768</td>\n",
       "      <td>0.006956</td>\n",
       "      <td>0.004643</td>\n",
       "      <td>0.002086</td>\n",
       "      <td>0.009242</td>\n",
       "      <td>0.004648</td>\n",
       "      <td>0.002317</td>\n",
       "      <td>0.007836</td>\n",
       "      <td>0.780190</td>\n",
       "      <td>0.584454</td>\n",
       "      <td>0.333833</td>\n",
       "      <td>0.891401</td>\n",
       "      <td>0.835098</td>\n",
       "      <td>0.955844</td>\n",
       "      <td>100</td>\n",
       "      <td>51</td>\n",
       "      <td>218</td>\n",
       "      <td>1104</td>\n",
       "      <td>0.290201</td>\n",
       "      <td>0.053125</td>\n",
       "      <td>0.946537</td>\n",
       "      <td>0.997731</td>\n",
       "      <td>0.900341</td>\n",
       "      <td>5</td>\n",
       "      <td>146</td>\n",
       "      <td>3</td>\n",
       "      <td>1319</td>\n",
       "      <td>0.281</td>\n",
       "      <td>0.053125</td>\n",
       "      <td>0.946537</td>\n",
       "      <td>0.997731</td>\n",
       "      <td>0.900341</td>\n",
       "      <td>5</td>\n",
       "      <td>146</td>\n",
       "      <td>3</td>\n",
       "      <td>1319</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>DecisionTreeClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[tree_1, evi2_raster, evi2_raster_diff, evi2_v...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>15.0</td>\n",
       "      <td>1.569873</td>\n",
       "      <td>0.733673</td>\n",
       "      <td>0.037741</td>\n",
       "      <td>-0.018487</td>\n",
       "      <td>-0.019603</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.002973</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.000280</td>\n",
       "      <td>0.008864</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000735</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.015599</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.628162</td>\n",
       "      <td>0.492373</td>\n",
       "      <td>0.129225</td>\n",
       "      <td>0.825503</td>\n",
       "      <td>0.744327</td>\n",
       "      <td>0.926554</td>\n",
       "      <td>73</td>\n",
       "      <td>78</td>\n",
       "      <td>338</td>\n",
       "      <td>984</td>\n",
       "      <td>0.350013</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.945975</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.897488</td>\n",
       "      <td>0</td>\n",
       "      <td>151</td>\n",
       "      <td>0</td>\n",
       "      <td>1322</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.945975</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.897488</td>\n",
       "      <td>0</td>\n",
       "      <td>151</td>\n",
       "      <td>0</td>\n",
       "      <td>1322</td>\n",
       "      <td>best</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.05</td>\n",
       "      <td>1153.0</td>\n",
       "      <td>gini</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>KNeighborsClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_2, location_cluster_3, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.009790</td>\n",
       "      <td>0.014440</td>\n",
       "      <td>0.018346</td>\n",
       "      <td>0.026817</td>\n",
       "      <td>0.014345</td>\n",
       "      <td>0.005117</td>\n",
       "      <td>-0.003270</td>\n",
       "      <td>0.006762</td>\n",
       "      <td>0.009368</td>\n",
       "      <td>0.019020</td>\n",
       "      <td>0.025486</td>\n",
       "      <td>0.029626</td>\n",
       "      <td>0.029973</td>\n",
       "      <td>0.010011</td>\n",
       "      <td>0.010783</td>\n",
       "      <td>-0.009130</td>\n",
       "      <td>0.018758</td>\n",
       "      <td>0.006483</td>\n",
       "      <td>0.019007</td>\n",
       "      <td>0.004021</td>\n",
       "      <td>0.032019</td>\n",
       "      <td>0.012914</td>\n",
       "      <td>0.018681</td>\n",
       "      <td>-0.007308</td>\n",
       "      <td>0.007629</td>\n",
       "      <td>0.013031</td>\n",
       "      <td>0.017537</td>\n",
       "      <td>-0.000255</td>\n",
       "      <td>0.681480</td>\n",
       "      <td>0.420519</td>\n",
       "      <td>0.211176</td>\n",
       "      <td>0.817474</td>\n",
       "      <td>0.714826</td>\n",
       "      <td>0.954545</td>\n",
       "      <td>106</td>\n",
       "      <td>45</td>\n",
       "      <td>377</td>\n",
       "      <td>945</td>\n",
       "      <td>0.052058</td>\n",
       "      <td>0.046568</td>\n",
       "      <td>0.947331</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.899932</td>\n",
       "      <td>4</td>\n",
       "      <td>147</td>\n",
       "      <td>0</td>\n",
       "      <td>1322</td>\n",
       "      <td>0.037</td>\n",
       "      <td>0.046568</td>\n",
       "      <td>0.947331</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.899932</td>\n",
       "      <td>4</td>\n",
       "      <td>147</td>\n",
       "      <td>0</td>\n",
       "      <td>1322</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>distance</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>manhattan</td>\n",
       "      <td>44.0</td>\n",
       "      <td>kd_tree</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>SVM</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_3, location_cluster_4, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.569873</td>\n",
       "      <td>0.733673</td>\n",
       "      <td>-0.000691</td>\n",
       "      <td>0.022131</td>\n",
       "      <td>0.057146</td>\n",
       "      <td>-0.002933</td>\n",
       "      <td>0.001023</td>\n",
       "      <td>0.021444</td>\n",
       "      <td>0.012072</td>\n",
       "      <td>0.021395</td>\n",
       "      <td>0.002254</td>\n",
       "      <td>0.005159</td>\n",
       "      <td>0.016807</td>\n",
       "      <td>0.014652</td>\n",
       "      <td>-0.002224</td>\n",
       "      <td>0.001350</td>\n",
       "      <td>0.004869</td>\n",
       "      <td>0.012595</td>\n",
       "      <td>0.004990</td>\n",
       "      <td>0.008031</td>\n",
       "      <td>0.004050</td>\n",
       "      <td>0.014240</td>\n",
       "      <td>0.005430</td>\n",
       "      <td>0.015764</td>\n",
       "      <td>0.008147</td>\n",
       "      <td>0.016527</td>\n",
       "      <td>0.000924</td>\n",
       "      <td>-0.002675</td>\n",
       "      <td>0.013247</td>\n",
       "      <td>0.001222</td>\n",
       "      <td>0.743180</td>\n",
       "      <td>0.509078</td>\n",
       "      <td>0.267377</td>\n",
       "      <td>0.853188</td>\n",
       "      <td>0.769289</td>\n",
       "      <td>0.957627</td>\n",
       "      <td>106</td>\n",
       "      <td>45</td>\n",
       "      <td>305</td>\n",
       "      <td>1017</td>\n",
       "      <td>0.064208</td>\n",
       "      <td>0.033596</td>\n",
       "      <td>0.946614</td>\n",
       "      <td>0.999244</td>\n",
       "      <td>0.899251</td>\n",
       "      <td>3</td>\n",
       "      <td>148</td>\n",
       "      <td>1</td>\n",
       "      <td>1321</td>\n",
       "      <td>0.064</td>\n",
       "      <td>0.033596</td>\n",
       "      <td>0.946614</td>\n",
       "      <td>0.999244</td>\n",
       "      <td>0.899251</td>\n",
       "      <td>3</td>\n",
       "      <td>148</td>\n",
       "      <td>1</td>\n",
       "      <td>1321</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.004</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>rbf</td>\n",
       "      <td>0.846</td>\n",
       "      <td>ovo</td>\n",
       "      <td>8.60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>RUSBoostClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_1, location_cluster_2, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>440.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.013933</td>\n",
       "      <td>-0.012698</td>\n",
       "      <td>-0.022936</td>\n",
       "      <td>-0.003728</td>\n",
       "      <td>-0.005095</td>\n",
       "      <td>-0.009577</td>\n",
       "      <td>-0.014259</td>\n",
       "      <td>-0.001362</td>\n",
       "      <td>0.001999</td>\n",
       "      <td>-0.017070</td>\n",
       "      <td>0.013099</td>\n",
       "      <td>-0.004067</td>\n",
       "      <td>-0.005935</td>\n",
       "      <td>-0.017562</td>\n",
       "      <td>-0.004253</td>\n",
       "      <td>0.006622</td>\n",
       "      <td>0.000383</td>\n",
       "      <td>-0.001508</td>\n",
       "      <td>-0.001725</td>\n",
       "      <td>-0.008823</td>\n",
       "      <td>-0.006709</td>\n",
       "      <td>-0.003928</td>\n",
       "      <td>-0.006950</td>\n",
       "      <td>-0.003922</td>\n",
       "      <td>-0.004058</td>\n",
       "      <td>0.002966</td>\n",
       "      <td>-0.009742</td>\n",
       "      <td>-0.001496</td>\n",
       "      <td>0.718753</td>\n",
       "      <td>0.502827</td>\n",
       "      <td>0.239104</td>\n",
       "      <td>0.841438</td>\n",
       "      <td>0.752648</td>\n",
       "      <td>0.953979</td>\n",
       "      <td>103</td>\n",
       "      <td>48</td>\n",
       "      <td>327</td>\n",
       "      <td>995</td>\n",
       "      <td>0.466251</td>\n",
       "      <td>0.035107</td>\n",
       "      <td>0.946991</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.899320</td>\n",
       "      <td>3</td>\n",
       "      <td>148</td>\n",
       "      <td>0</td>\n",
       "      <td>1322</td>\n",
       "      <td>0.466</td>\n",
       "      <td>0.035107</td>\n",
       "      <td>0.946991</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.899320</td>\n",
       "      <td>3</td>\n",
       "      <td>148</td>\n",
       "      <td>0</td>\n",
       "      <td>1322</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAMME.R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>0.0670</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>AdaBoostClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_1, location_cluster_4, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>455.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.004606</td>\n",
       "      <td>0.000124</td>\n",
       "      <td>-0.008952</td>\n",
       "      <td>-0.012644</td>\n",
       "      <td>-0.004750</td>\n",
       "      <td>0.020374</td>\n",
       "      <td>0.000526</td>\n",
       "      <td>-0.004413</td>\n",
       "      <td>-0.014078</td>\n",
       "      <td>0.007292</td>\n",
       "      <td>-0.002685</td>\n",
       "      <td>-0.011336</td>\n",
       "      <td>0.006988</td>\n",
       "      <td>0.001903</td>\n",
       "      <td>-0.005564</td>\n",
       "      <td>-0.003057</td>\n",
       "      <td>0.001985</td>\n",
       "      <td>-0.003312</td>\n",
       "      <td>-0.000463</td>\n",
       "      <td>-0.001375</td>\n",
       "      <td>-0.004894</td>\n",
       "      <td>-0.004336</td>\n",
       "      <td>0.002736</td>\n",
       "      <td>-0.015887</td>\n",
       "      <td>0.010716</td>\n",
       "      <td>-0.006547</td>\n",
       "      <td>-0.008110</td>\n",
       "      <td>-0.000721</td>\n",
       "      <td>0.768337</td>\n",
       "      <td>0.500146</td>\n",
       "      <td>0.203669</td>\n",
       "      <td>0.793961</td>\n",
       "      <td>0.676248</td>\n",
       "      <td>0.961290</td>\n",
       "      <td>115</td>\n",
       "      <td>36</td>\n",
       "      <td>428</td>\n",
       "      <td>894</td>\n",
       "      <td>0.492732</td>\n",
       "      <td>0.207995</td>\n",
       "      <td>0.948932</td>\n",
       "      <td>0.990923</td>\n",
       "      <td>0.910354</td>\n",
       "      <td>22</td>\n",
       "      <td>129</td>\n",
       "      <td>12</td>\n",
       "      <td>1310</td>\n",
       "      <td>0.493</td>\n",
       "      <td>0.229014</td>\n",
       "      <td>0.947636</td>\n",
       "      <td>0.985628</td>\n",
       "      <td>0.912465</td>\n",
       "      <td>26</td>\n",
       "      <td>125</td>\n",
       "      <td>19</td>\n",
       "      <td>1303</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAMME.R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.4500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>XGBClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_0, location_cluster_2, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>470.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.001581</td>\n",
       "      <td>-0.002681</td>\n",
       "      <td>-0.004120</td>\n",
       "      <td>0.033295</td>\n",
       "      <td>-0.006459</td>\n",
       "      <td>0.002924</td>\n",
       "      <td>-0.007361</td>\n",
       "      <td>-0.005366</td>\n",
       "      <td>0.000540</td>\n",
       "      <td>0.064791</td>\n",
       "      <td>0.005121</td>\n",
       "      <td>0.006874</td>\n",
       "      <td>0.018917</td>\n",
       "      <td>-0.002651</td>\n",
       "      <td>0.006512</td>\n",
       "      <td>-0.002181</td>\n",
       "      <td>-0.003419</td>\n",
       "      <td>0.005784</td>\n",
       "      <td>-0.004212</td>\n",
       "      <td>-0.002224</td>\n",
       "      <td>0.003556</td>\n",
       "      <td>0.003247</td>\n",
       "      <td>-0.005159</td>\n",
       "      <td>0.012891</td>\n",
       "      <td>-0.000449</td>\n",
       "      <td>-0.002465</td>\n",
       "      <td>0.013523</td>\n",
       "      <td>0.009262</td>\n",
       "      <td>0.794206</td>\n",
       "      <td>0.587655</td>\n",
       "      <td>0.338453</td>\n",
       "      <td>0.873181</td>\n",
       "      <td>0.794251</td>\n",
       "      <td>0.969529</td>\n",
       "      <td>118</td>\n",
       "      <td>33</td>\n",
       "      <td>272</td>\n",
       "      <td>1050</td>\n",
       "      <td>0.233375</td>\n",
       "      <td>0.215006</td>\n",
       "      <td>0.948895</td>\n",
       "      <td>0.990166</td>\n",
       "      <td>0.910926</td>\n",
       "      <td>23</td>\n",
       "      <td>128</td>\n",
       "      <td>13</td>\n",
       "      <td>1309</td>\n",
       "      <td>0.228</td>\n",
       "      <td>0.215006</td>\n",
       "      <td>0.948895</td>\n",
       "      <td>0.990166</td>\n",
       "      <td>0.910926</td>\n",
       "      <td>23</td>\n",
       "      <td>128</td>\n",
       "      <td>13</td>\n",
       "      <td>1309</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.400</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.90</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>2.139746</td>\n",
       "      <td>binary:logistic</td>\n",
       "      <td>0.1</td>\n",
       "      <td>aucpr</td>\n",
       "      <td>0.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>HistGradientBoostingClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>[location_cluster_0, location_cluster_3, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>78.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.006436</td>\n",
       "      <td>0.001419</td>\n",
       "      <td>-0.001935</td>\n",
       "      <td>0.024756</td>\n",
       "      <td>0.003211</td>\n",
       "      <td>0.003024</td>\n",
       "      <td>0.000493</td>\n",
       "      <td>-0.000522</td>\n",
       "      <td>-0.000739</td>\n",
       "      <td>0.004404</td>\n",
       "      <td>0.032536</td>\n",
       "      <td>-0.001095</td>\n",
       "      <td>0.005268</td>\n",
       "      <td>0.009805</td>\n",
       "      <td>0.001011</td>\n",
       "      <td>-0.003193</td>\n",
       "      <td>0.002630</td>\n",
       "      <td>-0.002718</td>\n",
       "      <td>0.006230</td>\n",
       "      <td>0.007075</td>\n",
       "      <td>-0.005943</td>\n",
       "      <td>-0.001716</td>\n",
       "      <td>-0.000706</td>\n",
       "      <td>-0.005403</td>\n",
       "      <td>0.024173</td>\n",
       "      <td>0.008020</td>\n",
       "      <td>0.005681</td>\n",
       "      <td>-0.004164</td>\n",
       "      <td>0.788438</td>\n",
       "      <td>0.624263</td>\n",
       "      <td>0.229135</td>\n",
       "      <td>0.799466</td>\n",
       "      <td>0.680030</td>\n",
       "      <td>0.969795</td>\n",
       "      <td>123</td>\n",
       "      <td>28</td>\n",
       "      <td>423</td>\n",
       "      <td>899</td>\n",
       "      <td>0.118878</td>\n",
       "      <td>0.206779</td>\n",
       "      <td>0.947368</td>\n",
       "      <td>0.987141</td>\n",
       "      <td>0.910677</td>\n",
       "      <td>23</td>\n",
       "      <td>128</td>\n",
       "      <td>17</td>\n",
       "      <td>1305</td>\n",
       "      <td>0.148</td>\n",
       "      <td>0.272373</td>\n",
       "      <td>0.947368</td>\n",
       "      <td>0.980333</td>\n",
       "      <td>0.916549</td>\n",
       "      <td>33</td>\n",
       "      <td>118</td>\n",
       "      <td>26</td>\n",
       "      <td>1296</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>106.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0490</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f1</td>\n",
       "      <td>275.0</td>\n",
       "      <td>binary_crossentropy</td>\n",
       "      <td>0.15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      species                           model      target  \\\n",
       "0   Deciduous          RandomForestClassifier  is_damaged   \n",
       "1   Deciduous  BalancedRandomForestClassifier  is_damaged   \n",
       "2   Deciduous          DecisionTreeClassifier  is_damaged   \n",
       "3   Deciduous            KNeighborsClassifier  is_damaged   \n",
       "4   Deciduous                             SVM  is_damaged   \n",
       "5   Deciduous              RUSBoostClassifier  is_damaged   \n",
       "6   Deciduous              AdaBoostClassifier  is_damaged   \n",
       "7   Deciduous                   XGBClassifier  is_damaged   \n",
       "8   Deciduous  HistGradientBoostingClassifier  is_damaged   \n",
       "9     Conifer          RandomForestClassifier  is_damaged   \n",
       "10    Conifer  BalancedRandomForestClassifier  is_damaged   \n",
       "11    Conifer          DecisionTreeClassifier  is_damaged   \n",
       "12    Conifer            KNeighborsClassifier  is_damaged   \n",
       "13    Conifer                             SVM  is_damaged   \n",
       "14    Conifer              RUSBoostClassifier  is_damaged   \n",
       "15    Conifer              AdaBoostClassifier  is_damaged   \n",
       "16    Conifer                   XGBClassifier  is_damaged   \n",
       "17    Conifer  HistGradientBoostingClassifier  is_damaged   \n",
       "18      Mixed          RandomForestClassifier  is_damaged   \n",
       "19      Mixed  BalancedRandomForestClassifier  is_damaged   \n",
       "20      Mixed          DecisionTreeClassifier  is_damaged   \n",
       "21      Mixed            KNeighborsClassifier  is_damaged   \n",
       "22      Mixed                             SVM  is_damaged   \n",
       "23      Mixed              RUSBoostClassifier  is_damaged   \n",
       "24      Mixed              AdaBoostClassifier  is_damaged   \n",
       "25      Mixed                   XGBClassifier  is_damaged   \n",
       "26      Mixed  HistGradientBoostingClassifier  is_damaged   \n",
       "\n",
       "                                    relevant_features params.warm_start  \\\n",
       "0   [location_cluster_2, location_cluster_3, locat...             False   \n",
       "1   [location_cluster_0, location_cluster_1, locat...             False   \n",
       "2   [location_cluster_13, tree_1, evi2, evi2_diff,...               NaN   \n",
       "3   [location_cluster_0, location_cluster_1, locat...               NaN   \n",
       "4   [location_cluster_0, location_cluster_1, locat...               NaN   \n",
       "5   [location_cluster_0, location_cluster_1, locat...               NaN   \n",
       "6   [location_cluster_0, location_cluster_1, locat...               NaN   \n",
       "7   [location_cluster_1, location_cluster_2, locat...               NaN   \n",
       "8   [location_cluster_0, location_cluster_1, locat...               NaN   \n",
       "9   [location_cluster_1, location_cluster_2, locat...              True   \n",
       "10  [location_cluster_0, location_cluster_1, locat...             False   \n",
       "11  [location_cluster_1, location_cluster_2, locat...               NaN   \n",
       "12  [location_cluster_2, location_cluster_4, locat...               NaN   \n",
       "13  [location_cluster_4, location_cluster_5, locat...               NaN   \n",
       "14  [location_cluster_1, location_cluster_4, locat...               NaN   \n",
       "15  [location_cluster_1, location_cluster_4, locat...               NaN   \n",
       "16  [location_cluster_2, location_cluster_4, locat...               NaN   \n",
       "17  [location_cluster_4, location_cluster_5, locat...               NaN   \n",
       "18  [location_cluster_0, location_cluster_2, locat...             False   \n",
       "19  [location_cluster_0, location_cluster_3, locat...              True   \n",
       "20  [tree_1, evi2_raster, evi2_raster_diff, evi2_v...               NaN   \n",
       "21  [location_cluster_2, location_cluster_3, locat...               NaN   \n",
       "22  [location_cluster_3, location_cluster_4, locat...               NaN   \n",
       "23  [location_cluster_1, location_cluster_2, locat...               NaN   \n",
       "24  [location_cluster_1, location_cluster_4, locat...               NaN   \n",
       "25  [location_cluster_0, location_cluster_2, locat...               NaN   \n",
       "26  [location_cluster_0, location_cluster_3, locat...               NaN   \n",
       "\n",
       "    params.random_state  params.n_jobs  params.n_estimators  \\\n",
       "0                2022.0           58.0                160.0   \n",
       "1                2022.0           58.0                336.0   \n",
       "2                2022.0            NaN                  NaN   \n",
       "3                   NaN           58.0                  NaN   \n",
       "4                2022.0            NaN                  NaN   \n",
       "5                2022.0            NaN                470.0   \n",
       "6                2022.0            NaN                380.0   \n",
       "7                   NaN           58.0                335.0   \n",
       "8                2022.0            NaN                  NaN   \n",
       "9                2022.0           58.0                 80.0   \n",
       "10               2022.0           58.0                464.0   \n",
       "11               2022.0            NaN                  NaN   \n",
       "12                  NaN           58.0                  NaN   \n",
       "13               2022.0            NaN                  NaN   \n",
       "14               2022.0            NaN                440.0   \n",
       "15               2022.0            NaN                455.0   \n",
       "16                  NaN           58.0                470.0   \n",
       "17               2022.0            NaN                  NaN   \n",
       "18               2022.0           58.0                384.0   \n",
       "19               2022.0           58.0                480.0   \n",
       "20               2022.0            NaN                  NaN   \n",
       "21                  NaN           58.0                  NaN   \n",
       "22               2022.0            NaN                  NaN   \n",
       "23               2022.0            NaN                440.0   \n",
       "24               2022.0            NaN                455.0   \n",
       "25                  NaN           58.0                470.0   \n",
       "26               2022.0            NaN                  NaN   \n",
       "\n",
       "    params.min_samples_split  params.min_samples_leaf params.max_features  \\\n",
       "0                        6.0                      2.0                sqrt   \n",
       "1                        6.0                      2.0                sqrt   \n",
       "2                       26.0                      3.0                log2   \n",
       "3                        NaN                      NaN                 NaN   \n",
       "4                        NaN                      NaN                 NaN   \n",
       "5                        NaN                      NaN                 NaN   \n",
       "6                        NaN                      NaN                 NaN   \n",
       "7                        NaN                      NaN                 NaN   \n",
       "8                        NaN                     23.0                 NaN   \n",
       "9                        4.0                      2.0                sqrt   \n",
       "10                       2.0                      2.0                sqrt   \n",
       "11                       4.0                      5.0                sqrt   \n",
       "12                       NaN                      NaN                 NaN   \n",
       "13                       NaN                      NaN                 NaN   \n",
       "14                       NaN                      NaN                 NaN   \n",
       "15                       NaN                      NaN                 NaN   \n",
       "16                       NaN                      NaN                 NaN   \n",
       "17                       NaN                     10.0                 NaN   \n",
       "18                       2.0                      2.0                sqrt   \n",
       "19                       4.0                      2.0                sqrt   \n",
       "20                      12.0                     15.0                sqrt   \n",
       "21                       NaN                      NaN                 NaN   \n",
       "22                       NaN                      NaN                 NaN   \n",
       "23                       NaN                      NaN                 NaN   \n",
       "24                       NaN                      NaN                 NaN   \n",
       "25                       NaN                      NaN                 NaN   \n",
       "26                       NaN                     19.0                 NaN   \n",
       "\n",
       "    params.max_depth  params.class_weight.1  params.class_weight.0  \\\n",
       "0              160.0               1.593548               0.728614   \n",
       "1              240.0                    NaN                    NaN   \n",
       "2                7.0               1.593548               0.728614   \n",
       "3                NaN                    NaN                    NaN   \n",
       "4                NaN               1.593548               0.728614   \n",
       "5                NaN                    NaN                    NaN   \n",
       "6                NaN                    NaN                    NaN   \n",
       "7                7.0                    NaN                    NaN   \n",
       "8               78.0                    NaN                    NaN   \n",
       "9              192.0               1.699173               0.708477   \n",
       "10             144.0                    NaN                    NaN   \n",
       "11               6.0               1.699173               0.708477   \n",
       "12               NaN                    NaN                    NaN   \n",
       "13               NaN               1.699173               0.708477   \n",
       "14               NaN                    NaN                    NaN   \n",
       "15               NaN                    NaN                    NaN   \n",
       "16               6.0                    NaN                    NaN   \n",
       "17               8.0                    NaN                    NaN   \n",
       "18              16.0               1.569873               0.733673   \n",
       "19             240.0                    NaN                    NaN   \n",
       "20              15.0               1.569873               0.733673   \n",
       "21               NaN                    NaN                    NaN   \n",
       "22               NaN               1.569873               0.733673   \n",
       "23               NaN                    NaN                    NaN   \n",
       "24               NaN                    NaN                    NaN   \n",
       "25               6.0                    NaN                    NaN   \n",
       "26              78.0                    NaN                    NaN   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_0  \\\n",
       "0                                           0.009460   \n",
       "1                                           0.003626   \n",
       "2                                           0.000000   \n",
       "3                                          -0.011434   \n",
       "4                                          -0.012784   \n",
       "5                                          -0.000487   \n",
       "6                                          -0.003410   \n",
       "7                                           0.004427   \n",
       "8                                           0.016143   \n",
       "9                                          -0.003764   \n",
       "10                                         -0.004779   \n",
       "11                                          0.023772   \n",
       "12                                          0.004681   \n",
       "13                                          0.011658   \n",
       "14                                         -0.004852   \n",
       "15                                         -0.010999   \n",
       "16                                          0.004411   \n",
       "17                                          0.046188   \n",
       "18                                         -0.008851   \n",
       "19                                         -0.002511   \n",
       "20                                          0.037741   \n",
       "21                                          0.009790   \n",
       "22                                         -0.000691   \n",
       "23                                         -0.013933   \n",
       "24                                         -0.004606   \n",
       "25                                         -0.001581   \n",
       "26                                          0.006436   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_1  \\\n",
       "0                                           0.008265   \n",
       "1                                          -0.013554   \n",
       "2                                           0.022008   \n",
       "3                                           0.010601   \n",
       "4                                          -0.006916   \n",
       "5                                          -0.002657   \n",
       "6                                           0.005938   \n",
       "7                                           0.005848   \n",
       "8                                           0.009234   \n",
       "9                                           0.002226   \n",
       "10                                          0.004870   \n",
       "11                                          0.000000   \n",
       "12                                          0.015648   \n",
       "13                                          0.018860   \n",
       "14                                         -0.000213   \n",
       "15                                         -0.005769   \n",
       "16                                          0.048451   \n",
       "17                                          0.024217   \n",
       "18                                         -0.003619   \n",
       "19                                         -0.001865   \n",
       "20                                         -0.018487   \n",
       "21                                          0.014440   \n",
       "22                                          0.022131   \n",
       "23                                         -0.012698   \n",
       "24                                          0.000124   \n",
       "25                                         -0.002681   \n",
       "26                                          0.001419   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_2  \\\n",
       "0                                           0.029235   \n",
       "1                                          -0.002099   \n",
       "2                                           0.000000   \n",
       "3                                           0.035132   \n",
       "4                                           0.006494   \n",
       "5                                           0.024363   \n",
       "6                                           0.001683   \n",
       "7                                           0.011533   \n",
       "8                                           0.023351   \n",
       "9                                           0.017508   \n",
       "10                                          0.001050   \n",
       "11                                          0.033987   \n",
       "12                                          0.030691   \n",
       "13                                          0.004188   \n",
       "14                                          0.020012   \n",
       "15                                          0.005227   \n",
       "16                                          0.013515   \n",
       "17                                          0.004743   \n",
       "18                                         -0.004068   \n",
       "19                                          0.021229   \n",
       "20                                         -0.019603   \n",
       "21                                          0.018346   \n",
       "22                                          0.057146   \n",
       "23                                         -0.022936   \n",
       "24                                         -0.008952   \n",
       "25                                         -0.004120   \n",
       "26                                         -0.001935   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_3  \\\n",
       "0                                           0.003486   \n",
       "1                                           0.021695   \n",
       "2                                           0.000000   \n",
       "3                                          -0.049829   \n",
       "4                                          -0.025448   \n",
       "5                                           0.012437   \n",
       "6                                          -0.004812   \n",
       "7                                           0.014200   \n",
       "8                                           0.026779   \n",
       "9                                           0.017346   \n",
       "10                                          0.009145   \n",
       "11                                          0.000000   \n",
       "12                                          0.003218   \n",
       "13                                          0.015152   \n",
       "14                                          0.001645   \n",
       "15                                         -0.008347   \n",
       "16                                          0.010802   \n",
       "17                                          0.013470   \n",
       "18                                         -0.018754   \n",
       "19                                          0.005843   \n",
       "20                                          0.000000   \n",
       "21                                          0.026817   \n",
       "22                                         -0.002933   \n",
       "23                                         -0.003728   \n",
       "24                                         -0.012644   \n",
       "25                                          0.033295   \n",
       "26                                          0.024756   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_4  \\\n",
       "0                                          -0.003369   \n",
       "1                                          -0.001104   \n",
       "2                                           0.000000   \n",
       "3                                           0.004990   \n",
       "4                                           0.021316   \n",
       "5                                           0.029213   \n",
       "6                                           0.021041   \n",
       "7                                           0.016922   \n",
       "8                                           0.092038   \n",
       "9                                           0.005245   \n",
       "10                                          0.032036   \n",
       "11                                          0.000000   \n",
       "12                                          0.003916   \n",
       "13                                          0.005520   \n",
       "14                                         -0.000099   \n",
       "15                                          0.004845   \n",
       "16                                          0.006152   \n",
       "17                                          0.002039   \n",
       "18                                         -0.012120   \n",
       "19                                         -0.004439   \n",
       "20                                          0.000000   \n",
       "21                                          0.014345   \n",
       "22                                          0.001023   \n",
       "23                                         -0.005095   \n",
       "24                                         -0.004750   \n",
       "25                                         -0.006459   \n",
       "26                                          0.003211   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_5  \\\n",
       "0                                           0.002145   \n",
       "1                                           0.019306   \n",
       "2                                           0.000000   \n",
       "3                                           0.000826   \n",
       "4                                          -0.023937   \n",
       "5                                          -0.003944   \n",
       "6                                          -0.003338   \n",
       "7                                          -0.000201   \n",
       "8                                          -0.002569   \n",
       "9                                           0.008114   \n",
       "10                                         -0.001695   \n",
       "11                                          0.000000   \n",
       "12                                          0.002426   \n",
       "13                                         -0.002057   \n",
       "14                                         -0.003129   \n",
       "15                                         -0.003998   \n",
       "16                                          0.004793   \n",
       "17                                          0.006671   \n",
       "18                                         -0.004277   \n",
       "19                                         -0.008059   \n",
       "20                                          0.002973   \n",
       "21                                          0.005117   \n",
       "22                                          0.021444   \n",
       "23                                         -0.009577   \n",
       "24                                          0.020374   \n",
       "25                                          0.002924   \n",
       "26                                          0.003024   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_6  \\\n",
       "0                                           0.088365   \n",
       "1                                           0.003039   \n",
       "2                                           0.010937   \n",
       "3                                           0.008849   \n",
       "4                                          -0.030311   \n",
       "5                                          -0.000759   \n",
       "6                                           0.008629   \n",
       "7                                           0.019756   \n",
       "8                                           0.001619   \n",
       "9                                           0.006452   \n",
       "10                                         -0.002828   \n",
       "11                                          0.000000   \n",
       "12                                          0.013638   \n",
       "13                                          0.005065   \n",
       "14                                          0.005734   \n",
       "15                                         -0.004382   \n",
       "16                                          0.007565   \n",
       "17                                          0.045956   \n",
       "18                                         -0.003043   \n",
       "19                                          0.021605   \n",
       "20                                          0.000000   \n",
       "21                                         -0.003270   \n",
       "22                                          0.012072   \n",
       "23                                         -0.014259   \n",
       "24                                          0.000526   \n",
       "25                                         -0.007361   \n",
       "26                                          0.000493   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_7  \\\n",
       "0                                           0.001087   \n",
       "1                                          -0.003837   \n",
       "2                                           0.000000   \n",
       "3                                           0.004184   \n",
       "4                                          -0.019667   \n",
       "5                                           0.006040   \n",
       "6                                           0.007617   \n",
       "7                                           0.015057   \n",
       "8                                           0.010727   \n",
       "9                                           0.006280   \n",
       "10                                          0.005287   \n",
       "11                                          0.000000   \n",
       "12                                          0.004032   \n",
       "13                                         -0.002901   \n",
       "14                                         -0.006499   \n",
       "15                                         -0.011932   \n",
       "16                                          0.051413   \n",
       "17                                         -0.001327   \n",
       "18                                         -0.017451   \n",
       "19                                         -0.000503   \n",
       "20                                         -0.000280   \n",
       "21                                          0.006762   \n",
       "22                                          0.021395   \n",
       "23                                         -0.001362   \n",
       "24                                         -0.004413   \n",
       "25                                         -0.005366   \n",
       "26                                         -0.000522   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_8  \\\n",
       "0                                          -0.001318   \n",
       "1                                           0.001084   \n",
       "2                                           0.000000   \n",
       "3                                           0.005672   \n",
       "4                                          -0.012161   \n",
       "5                                           0.004672   \n",
       "6                                          -0.002306   \n",
       "7                                           0.001397   \n",
       "8                                           0.002771   \n",
       "9                                           0.005139   \n",
       "10                                          0.001274   \n",
       "11                                          0.000000   \n",
       "12                                          0.011037   \n",
       "13                                          0.005624   \n",
       "14                                          0.004405   \n",
       "15                                         -0.000569   \n",
       "16                                         -0.006609   \n",
       "17                                          0.010694   \n",
       "18                                         -0.008825   \n",
       "19                                          0.003406   \n",
       "20                                          0.008864   \n",
       "21                                          0.009368   \n",
       "22                                          0.002254   \n",
       "23                                          0.001999   \n",
       "24                                         -0.014078   \n",
       "25                                          0.000540   \n",
       "26                                         -0.000739   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_9  \\\n",
       "0                                           0.011893   \n",
       "1                                          -0.002472   \n",
       "2                                           0.006422   \n",
       "3                                           0.016174   \n",
       "4                                          -0.023627   \n",
       "5                                          -0.000280   \n",
       "6                                           0.001477   \n",
       "7                                           0.003132   \n",
       "8                                          -0.001888   \n",
       "9                                           0.025841   \n",
       "10                                          0.005010   \n",
       "11                                          0.011386   \n",
       "12                                          0.032031   \n",
       "13                                         -0.002568   \n",
       "14                                          0.002659   \n",
       "15                                         -0.001937   \n",
       "16                                         -0.002993   \n",
       "17                                         -0.001346   \n",
       "18                                         -0.000182   \n",
       "19                                         -0.001937   \n",
       "20                                          0.000000   \n",
       "21                                          0.019020   \n",
       "22                                          0.005159   \n",
       "23                                         -0.017070   \n",
       "24                                          0.007292   \n",
       "25                                          0.064791   \n",
       "26                                          0.004404   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_10  \\\n",
       "0                                            0.010797   \n",
       "1                                            0.001365   \n",
       "2                                            0.003467   \n",
       "3                                           -0.003821   \n",
       "4                                           -0.023179   \n",
       "5                                           -0.000062   \n",
       "6                                            0.002381   \n",
       "7                                            0.081817   \n",
       "8                                            0.001758   \n",
       "9                                            0.000659   \n",
       "10                                           0.001978   \n",
       "11                                           0.000000   \n",
       "12                                           0.005326   \n",
       "13                                           0.005196   \n",
       "14                                          -0.002168   \n",
       "15                                           0.009068   \n",
       "16                                          -0.004954   \n",
       "17                                           0.001775   \n",
       "18                                           0.011630   \n",
       "19                                           0.000421   \n",
       "20                                           0.000000   \n",
       "21                                           0.025486   \n",
       "22                                           0.016807   \n",
       "23                                           0.013099   \n",
       "24                                          -0.002685   \n",
       "25                                           0.005121   \n",
       "26                                           0.032536   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_11  \\\n",
       "0                                            0.008939   \n",
       "1                                            0.001476   \n",
       "2                                            0.000000   \n",
       "3                                            0.007294   \n",
       "4                                           -0.004984   \n",
       "5                                            0.004921   \n",
       "6                                           -0.004790   \n",
       "7                                            0.002327   \n",
       "8                                            0.002429   \n",
       "9                                            0.002543   \n",
       "10                                           0.004352   \n",
       "11                                           0.000000   \n",
       "12                                           0.001924   \n",
       "13                                           0.001105   \n",
       "14                                          -0.004200   \n",
       "15                                           0.001392   \n",
       "16                                           0.001051   \n",
       "17                                           0.000891   \n",
       "18                                          -0.005726   \n",
       "19                                          -0.005009   \n",
       "20                                           0.000000   \n",
       "21                                           0.029626   \n",
       "22                                           0.014652   \n",
       "23                                          -0.004067   \n",
       "24                                          -0.011336   \n",
       "25                                           0.006874   \n",
       "26                                          -0.001095   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_12  \\\n",
       "0                                            0.009473   \n",
       "1                                            0.001208   \n",
       "2                                            0.000000   \n",
       "3                                           -0.005414   \n",
       "4                                           -0.015227   \n",
       "5                                            0.011451   \n",
       "6                                            0.001432   \n",
       "7                                            0.000075   \n",
       "8                                            0.016045   \n",
       "9                                           -0.003963   \n",
       "10                                           0.001401   \n",
       "11                                           0.000000   \n",
       "12                                           0.009202   \n",
       "13                                           0.007064   \n",
       "14                                          -0.000236   \n",
       "15                                           0.003139   \n",
       "16                                           0.003312   \n",
       "17                                           0.011050   \n",
       "18                                          -0.000294   \n",
       "19                                          -0.002649   \n",
       "20                                           0.000000   \n",
       "21                                           0.029973   \n",
       "22                                          -0.002224   \n",
       "23                                          -0.005935   \n",
       "24                                           0.006988   \n",
       "25                                           0.018917   \n",
       "26                                           0.005268   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_13  \\\n",
       "0                                            0.004997   \n",
       "1                                            0.005625   \n",
       "2                                            0.000000   \n",
       "3                                           -0.003932   \n",
       "4                                           -0.033112   \n",
       "5                                            0.003604   \n",
       "6                                            0.004133   \n",
       "7                                            0.012967   \n",
       "8                                            0.013583   \n",
       "9                                            0.002949   \n",
       "10                                           0.000654   \n",
       "11                                           0.000000   \n",
       "12                                           0.012475   \n",
       "13                                           0.006913   \n",
       "14                                           0.007986   \n",
       "15                                           0.012200   \n",
       "16                                          -0.001944   \n",
       "17                                          -0.001558   \n",
       "18                                          -0.003884   \n",
       "19                                          -0.000711   \n",
       "20                                           0.000000   \n",
       "21                                           0.010011   \n",
       "22                                           0.001350   \n",
       "23                                          -0.017562   \n",
       "24                                           0.001903   \n",
       "25                                          -0.002651   \n",
       "26                                           0.009805   \n",
       "\n",
       "    feature_permutaion_importance.tree_1  feature_permutaion_importance.evi2  \\\n",
       "0                              -0.000839                            0.018223   \n",
       "1                              -0.001809                            0.000134   \n",
       "2                               0.000000                            0.000000   \n",
       "3                              -0.004766                            0.000967   \n",
       "4                              -0.011806                           -0.019818   \n",
       "5                               0.002243                           -0.001348   \n",
       "6                               0.004810                            0.004133   \n",
       "7                               0.004429                            0.001601   \n",
       "8                              -0.001758                            0.002998   \n",
       "9                              -0.004935                           -0.012632   \n",
       "10                              0.000889                           -0.000248   \n",
       "11                              0.000000                            0.000000   \n",
       "12                              0.000635                           -0.005101   \n",
       "13                              0.004687                           -0.003721   \n",
       "14                             -0.002892                           -0.000850   \n",
       "15                              0.003412                           -0.001516   \n",
       "16                             -0.007586                            0.003994   \n",
       "17                              0.012080                           -0.005178   \n",
       "18                             -0.003208                           -0.000756   \n",
       "19                              0.008895                            0.002375   \n",
       "20                              0.000000                            0.000000   \n",
       "21                              0.010783                           -0.009130   \n",
       "22                              0.004869                            0.012595   \n",
       "23                             -0.004253                            0.006622   \n",
       "24                             -0.005564                           -0.003057   \n",
       "25                              0.006512                           -0.002181   \n",
       "26                              0.001011                           -0.003193   \n",
       "\n",
       "    feature_permutaion_importance.evi2-1  \\\n",
       "0                               0.001142   \n",
       "1                              -0.001613   \n",
       "2                              -0.000761   \n",
       "3                               0.000827   \n",
       "4                              -0.011077   \n",
       "5                               0.011709   \n",
       "6                              -0.005509   \n",
       "7                               0.011393   \n",
       "8                               0.013846   \n",
       "9                               0.004803   \n",
       "10                              0.014010   \n",
       "11                              0.000000   \n",
       "12                              0.002956   \n",
       "13                             -0.003876   \n",
       "14                              0.004435   \n",
       "15                             -0.004001   \n",
       "16                             -0.009274   \n",
       "17                             -0.007328   \n",
       "18                             -0.007505   \n",
       "19                              0.004684   \n",
       "20                              0.000000   \n",
       "21                              0.018758   \n",
       "22                              0.004990   \n",
       "23                              0.000383   \n",
       "24                              0.001985   \n",
       "25                             -0.003419   \n",
       "26                              0.002630   \n",
       "\n",
       "    feature_permutaion_importance.evi2_diff  \\\n",
       "0                                  0.011244   \n",
       "1                                 -0.001695   \n",
       "2                                 -0.001658   \n",
       "3                                  0.004385   \n",
       "4                                 -0.022573   \n",
       "5                                 -0.015896   \n",
       "6                                 -0.007961   \n",
       "7                                  0.009522   \n",
       "8                                  0.003334   \n",
       "9                                  0.004411   \n",
       "10                                 0.014017   \n",
       "11                                 0.000000   \n",
       "12                                -0.005027   \n",
       "13                                 0.000973   \n",
       "14                                -0.004612   \n",
       "15                                -0.003510   \n",
       "16                                 0.011098   \n",
       "17                                -0.000634   \n",
       "18                                -0.004863   \n",
       "19                                 0.000475   \n",
       "20                                 0.000000   \n",
       "21                                 0.006483   \n",
       "22                                 0.008031   \n",
       "23                                -0.001508   \n",
       "24                                -0.003312   \n",
       "25                                 0.005784   \n",
       "26                                -0.002718   \n",
       "\n",
       "    feature_permutaion_importance.evi2_max_diff  \\\n",
       "0                                      0.001901   \n",
       "1                                     -0.013254   \n",
       "2                                      0.000000   \n",
       "3                                      0.004153   \n",
       "4                                     -0.023932   \n",
       "5                                     -0.007951   \n",
       "6                                      0.001783   \n",
       "7                                      0.002994   \n",
       "8                                      0.003562   \n",
       "9                                      0.000079   \n",
       "10                                     0.002659   \n",
       "11                                     0.000000   \n",
       "12                                    -0.014088   \n",
       "13                                     0.004677   \n",
       "14                                     0.015152   \n",
       "15                                    -0.005062   \n",
       "16                                     0.014770   \n",
       "17                                     0.005701   \n",
       "18                                    -0.009545   \n",
       "19                                    -0.000960   \n",
       "20                                     0.000000   \n",
       "21                                     0.019007   \n",
       "22                                     0.004050   \n",
       "23                                    -0.001725   \n",
       "24                                    -0.000463   \n",
       "25                                    -0.004212   \n",
       "26                                     0.006230   \n",
       "\n",
       "    feature_permutaion_importance.evi2_raster  \\\n",
       "0                                    0.001286   \n",
       "1                                    0.001712   \n",
       "2                                    0.000000   \n",
       "3                                    0.027839   \n",
       "4                                    0.015720   \n",
       "5                                    0.010957   \n",
       "6                                   -0.031217   \n",
       "7                                   -0.000140   \n",
       "8                                    0.005522   \n",
       "9                                   -0.009609   \n",
       "10                                  -0.002226   \n",
       "11                                   0.000000   \n",
       "12                                   0.007074   \n",
       "13                                   0.013943   \n",
       "14                                  -0.004260   \n",
       "15                                   0.000411   \n",
       "16                                  -0.008823   \n",
       "17                                   0.047457   \n",
       "18                                   0.004537   \n",
       "19                                   0.008051   \n",
       "20                                   0.000735   \n",
       "21                                   0.004021   \n",
       "22                                   0.014240   \n",
       "23                                  -0.008823   \n",
       "24                                  -0.001375   \n",
       "25                                  -0.002224   \n",
       "26                                   0.007075   \n",
       "\n",
       "    feature_permutaion_importance.evi2_raster-1  \\\n",
       "0                                     -0.003597   \n",
       "1                                     -0.007799   \n",
       "2                                     -0.004509   \n",
       "3                                      0.000540   \n",
       "4                                     -0.010409   \n",
       "5                                      0.000346   \n",
       "6                                     -0.011863   \n",
       "7                                     -0.000605   \n",
       "8                                     -0.003582   \n",
       "9                                     -0.001341   \n",
       "10                                    -0.001270   \n",
       "11                                     0.000000   \n",
       "12                                     0.006476   \n",
       "13                                     0.033446   \n",
       "14                                    -0.004340   \n",
       "15                                     0.033237   \n",
       "16                                    -0.003584   \n",
       "17                                    -0.013846   \n",
       "18                                    -0.006118   \n",
       "19                                     0.010768   \n",
       "20                                     0.000000   \n",
       "21                                     0.032019   \n",
       "22                                     0.005430   \n",
       "23                                    -0.006709   \n",
       "24                                    -0.004894   \n",
       "25                                     0.003556   \n",
       "26                                    -0.005943   \n",
       "\n",
       "    feature_permutaion_importance.evi2_raster_diff  \\\n",
       "0                                        -0.001993   \n",
       "1                                        -0.000499   \n",
       "2                                         0.000000   \n",
       "3                                         0.021086   \n",
       "4                                        -0.014905   \n",
       "5                                         0.012503   \n",
       "6                                        -0.001284   \n",
       "7                                         0.000636   \n",
       "8                                         0.031415   \n",
       "9                                        -0.016142   \n",
       "10                                       -0.004219   \n",
       "11                                        0.000000   \n",
       "12                                        0.002143   \n",
       "13                                       -0.006984   \n",
       "14                                       -0.002815   \n",
       "15                                        0.000382   \n",
       "16                                       -0.009323   \n",
       "17                                       -0.007643   \n",
       "18                                        0.000758   \n",
       "19                                        0.006956   \n",
       "20                                        0.000000   \n",
       "21                                        0.012914   \n",
       "22                                        0.015764   \n",
       "23                                       -0.003928   \n",
       "24                                       -0.004336   \n",
       "25                                        0.003247   \n",
       "26                                       -0.001716   \n",
       "\n",
       "    feature_permutaion_importance.evi2_vegetation_raster  \\\n",
       "0                                            0.037384      \n",
       "1                                            0.001673      \n",
       "2                                            0.000000      \n",
       "3                                           -0.013395      \n",
       "4                                           -0.007121      \n",
       "5                                            0.004125      \n",
       "6                                            0.006566      \n",
       "7                                            0.004293      \n",
       "8                                            0.000268      \n",
       "9                                            0.053487      \n",
       "10                                           0.003065      \n",
       "11                                           0.000000      \n",
       "12                                          -0.000709      \n",
       "13                                          -0.003680      \n",
       "14                                          -0.009306      \n",
       "15                                          -0.000464      \n",
       "16                                           0.003365      \n",
       "17                                           0.001899      \n",
       "18                                           0.003678      \n",
       "19                                           0.004643      \n",
       "20                                           0.000000      \n",
       "21                                           0.018681      \n",
       "22                                           0.008147      \n",
       "23                                          -0.006950      \n",
       "24                                           0.002736      \n",
       "25                                          -0.005159      \n",
       "26                                          -0.000706      \n",
       "\n",
       "    feature_permutaion_importance.evi2_vegetation_raster-1  \\\n",
       "0                                            0.011231        \n",
       "1                                           -0.001437        \n",
       "2                                            0.000000        \n",
       "3                                            0.012266        \n",
       "4                                            0.003145        \n",
       "5                                            0.008712        \n",
       "6                                           -0.022133        \n",
       "7                                            0.003269        \n",
       "8                                            0.011137        \n",
       "9                                           -0.000466        \n",
       "10                                           0.018624        \n",
       "11                                           0.000000        \n",
       "12                                           0.007467        \n",
       "13                                           0.003769        \n",
       "14                                           0.003159        \n",
       "15                                          -0.006981        \n",
       "16                                          -0.006693        \n",
       "17                                          -0.018024        \n",
       "18                                          -0.005409        \n",
       "19                                           0.002086        \n",
       "20                                           0.000000        \n",
       "21                                          -0.007308        \n",
       "22                                           0.016527        \n",
       "23                                          -0.003922        \n",
       "24                                          -0.015887        \n",
       "25                                           0.012891        \n",
       "26                                          -0.005403        \n",
       "\n",
       "    feature_permutaion_importance.evi2_vegetation_raster_diff  \\\n",
       "0                                            0.012514           \n",
       "1                                           -0.000738           \n",
       "2                                            0.004536           \n",
       "3                                           -0.015339           \n",
       "4                                           -0.019670           \n",
       "5                                           -0.000463           \n",
       "6                                           -0.033335           \n",
       "7                                            0.011106           \n",
       "8                                            0.011338           \n",
       "9                                           -0.007563           \n",
       "10                                           0.002761           \n",
       "11                                           0.000000           \n",
       "12                                           0.007517           \n",
       "13                                           0.003971           \n",
       "14                                           0.008444           \n",
       "15                                           0.001861           \n",
       "16                                          -0.007375           \n",
       "17                                          -0.007645           \n",
       "18                                           0.000954           \n",
       "19                                           0.009242           \n",
       "20                                           0.015599           \n",
       "21                                           0.007629           \n",
       "22                                           0.000924           \n",
       "23                                          -0.004058           \n",
       "24                                           0.010716           \n",
       "25                                          -0.000449           \n",
       "26                                           0.024173           \n",
       "\n",
       "    feature_permutaion_importance.ndvi  feature_permutaion_importance.ndvi-1  \\\n",
       "0                            -0.000894                              0.012851   \n",
       "1                            -0.002202                              0.001486   \n",
       "2                            -0.004337                              0.004458   \n",
       "3                            -0.003157                              0.006501   \n",
       "4                            -0.011970                             -0.008887   \n",
       "5                            -0.015372                              0.017436   \n",
       "6                            -0.021963                              0.010151   \n",
       "7                             0.018105                              0.017290   \n",
       "8                            -0.002023                              0.000405   \n",
       "9                            -0.001486                              0.004112   \n",
       "10                           -0.003868                              0.000560   \n",
       "11                            0.000000                              0.000000   \n",
       "12                            0.004170                              0.001273   \n",
       "13                           -0.001314                             -0.006187   \n",
       "14                            0.007191                              0.005143   \n",
       "15                           -0.004327                              0.005809   \n",
       "16                            0.011562                             -0.001395   \n",
       "17                            0.002013                              0.005677   \n",
       "18                            0.001473                             -0.001018   \n",
       "19                            0.004648                              0.002317   \n",
       "20                            0.000000                              0.000000   \n",
       "21                            0.013031                              0.017537   \n",
       "22                           -0.002675                              0.013247   \n",
       "23                            0.002966                             -0.009742   \n",
       "24                           -0.006547                             -0.008110   \n",
       "25                           -0.002465                              0.013523   \n",
       "26                            0.008020                              0.005681   \n",
       "\n",
       "    feature_permutaion_importance.ndvi_diff  metrics.auc  \\\n",
       "0                                  0.005714     0.690244   \n",
       "1                                 -0.009569     0.690408   \n",
       "2                                  0.000000     0.584819   \n",
       "3                                 -0.007430     0.567251   \n",
       "4                                 -0.005802     0.652872   \n",
       "5                                 -0.001926     0.665693   \n",
       "6                                 -0.001908     0.702559   \n",
       "7                                  0.025867     0.783900   \n",
       "8                                  0.013332     0.662881   \n",
       "9                                  0.005183     0.758450   \n",
       "10                                -0.002154     0.725305   \n",
       "11                                 0.000000     0.569515   \n",
       "12                                 0.027289     0.679513   \n",
       "13                                -0.003115     0.728485   \n",
       "14                                -0.000260     0.748870   \n",
       "15                                 0.004101     0.748238   \n",
       "16                                -0.001475     0.725240   \n",
       "17                                 0.019817     0.745651   \n",
       "18                                 0.006035     0.738243   \n",
       "19                                 0.007836     0.780190   \n",
       "20                                 0.000000     0.628162   \n",
       "21                                -0.000255     0.681480   \n",
       "22                                 0.001222     0.743180   \n",
       "23                                -0.001496     0.718753   \n",
       "24                                -0.000721     0.768337   \n",
       "25                                 0.009262     0.794206   \n",
       "26                                -0.004164     0.788438   \n",
       "\n",
       "    metrics.roc.threshold  metrics.roc.cohen_kappa  metrics.roc.f1  \\\n",
       "0                0.467516                 0.305956        0.900000   \n",
       "1                0.553150                 0.276460        0.878587   \n",
       "2                0.531989                 0.065295        0.541387   \n",
       "3                0.381755                 0.099720        0.707175   \n",
       "4                0.431184                 0.170072        0.830080   \n",
       "5                0.496916                 0.283560        0.892258   \n",
       "6                0.503444                 0.155997        0.712975   \n",
       "7                0.541763                 0.296770        0.860240   \n",
       "8                0.421783                 0.371241        0.914803   \n",
       "9                0.438095                 0.444266        0.921466   \n",
       "10               0.524421                 0.314680        0.886750   \n",
       "11               0.515043                 0.093012        0.790641   \n",
       "12               0.516775                 0.170691        0.781270   \n",
       "13               0.362802                 0.347280        0.899329   \n",
       "14               0.495588                 0.328321        0.888322   \n",
       "15               0.498755                 0.248933        0.840191   \n",
       "16               0.565510                 0.234021        0.822742   \n",
       "17               0.450929                 0.320051        0.868982   \n",
       "18               0.577855                 0.158175        0.757078   \n",
       "19               0.584454                 0.333833        0.891401   \n",
       "20               0.492373                 0.129225        0.825503   \n",
       "21               0.420519                 0.211176        0.817474   \n",
       "22               0.509078                 0.267377        0.853188   \n",
       "23               0.502827                 0.239104        0.841438   \n",
       "24               0.500146                 0.203669        0.793961   \n",
       "25               0.587655                 0.338453        0.873181   \n",
       "26               0.624263                 0.229135        0.799466   \n",
       "\n",
       "    metrics.roc.recall  metrics.roc.precision  metrics.roc.tn  metrics.roc.fp  \\\n",
       "0             0.880126               0.920792              63              72   \n",
       "1             0.837014               0.924506              70              65   \n",
       "2             0.381703               0.930769             108              27   \n",
       "3             0.575184               0.917785              86              49   \n",
       "4             0.760252               0.914033              67              68   \n",
       "5             0.866456               0.919643              63              72   \n",
       "6             0.572029               0.946087             104              31   \n",
       "7             0.792850               0.940150              87              48   \n",
       "8             0.903260               0.926645              67              68   \n",
       "9             0.914661               0.928373             156             129   \n",
       "10            0.856674               0.919014             147             138   \n",
       "11            0.711707               0.889269             123             162   \n",
       "12            0.679978               0.918021             174             111   \n",
       "13            0.879650               0.919908             145             140   \n",
       "14            0.857221               0.921765             152             133   \n",
       "15            0.770788               0.923329             168             117   \n",
       "16            0.740153               0.926078             177             108   \n",
       "17            0.814551               0.931207             175             110   \n",
       "18            0.627080               0.955069             112              39   \n",
       "19            0.835098               0.955844             100              51   \n",
       "20            0.744327               0.926554              73              78   \n",
       "21            0.714826               0.954545             106              45   \n",
       "22            0.769289               0.957627             106              45   \n",
       "23            0.752648               0.953979             103              48   \n",
       "24            0.676248               0.961290             115              36   \n",
       "25            0.794251               0.969529             118              33   \n",
       "26            0.680030               0.969795             123              28   \n",
       "\n",
       "    metrics.roc.fn  metrics.roc.tp  metrics.prc.threshold  \\\n",
       "0              114             837               0.747734   \n",
       "1              155             796               0.398322   \n",
       "2              588             363               0.449369   \n",
       "3              404             547               0.060915   \n",
       "4              228             723               0.095497   \n",
       "5              127             824               0.471729   \n",
       "6              407             544               0.491952   \n",
       "7              197             754               0.212362   \n",
       "8               92             859               0.116349   \n",
       "9              156            1672               0.339557   \n",
       "10             262            1566               0.313176   \n",
       "11             527            1301               0.370111   \n",
       "12             585            1243               0.126562   \n",
       "13             220            1608               0.198932   \n",
       "14             261            1567               0.486012   \n",
       "15             419            1409               0.490823   \n",
       "16             475            1353               0.134792   \n",
       "17             339            1489               0.131199   \n",
       "18             493             829               0.294460   \n",
       "19             218            1104               0.290201   \n",
       "20             338             984               0.350013   \n",
       "21             377             945               0.052058   \n",
       "22             305            1017               0.064208   \n",
       "23             327             995               0.466251   \n",
       "24             428             894               0.492732   \n",
       "25             272            1050               0.233375   \n",
       "26             423             899               0.118878   \n",
       "\n",
       "    metrics.prc.cohen_kappa  metrics.prc.f1  metrics.prc.recall  \\\n",
       "0                 -0.001843        0.000000            0.000000   \n",
       "1                  0.234950        0.935807            0.981073   \n",
       "2                  0.178185        0.936847            0.990536   \n",
       "3                  0.000000        0.933726            1.000000   \n",
       "4                  0.025661        0.934644            1.000000   \n",
       "5                  0.292451        0.944167            0.995794   \n",
       "6                  0.434160        0.945547            0.976866   \n",
       "7                  0.305085        0.945165            0.996845   \n",
       "8                  0.327367        0.945527            0.994742   \n",
       "9                  0.515887        0.949618            0.984683   \n",
       "10                 0.295998        0.940206            0.997812   \n",
       "11                 0.000000        0.927683            1.000000   \n",
       "12                 0.318603        0.939103            0.991247   \n",
       "13                 0.291811        0.938807            0.994530   \n",
       "14                 0.365151        0.939734            0.985230   \n",
       "15                 0.169130        0.934799            1.000000   \n",
       "16                 0.228249        0.936553            0.997265   \n",
       "17                 0.395456        0.943779            0.991794   \n",
       "18                 0.191548        0.948625            0.991679   \n",
       "19                 0.053125        0.946537            0.997731   \n",
       "20                 0.000000        0.945975            1.000000   \n",
       "21                 0.046568        0.947331            1.000000   \n",
       "22                 0.033596        0.946614            0.999244   \n",
       "23                 0.035107        0.946991            1.000000   \n",
       "24                 0.207995        0.948932            0.990923   \n",
       "25                 0.215006        0.948895            0.990166   \n",
       "26                 0.206779        0.947368            0.987141   \n",
       "\n",
       "    metrics.prc.precision  metrics.prc.tn  metrics.prc.fp  metrics.prc.fn  \\\n",
       "0                0.000000             134               1             951   \n",
       "1                0.894535              25             110              18   \n",
       "2                0.888679              17             118               9   \n",
       "3                0.875691               0             135               0   \n",
       "4                0.877306               2             133               0   \n",
       "5                0.897630              27             108               4   \n",
       "6                0.916174              50              85              22   \n",
       "7                0.898578              28             107               3   \n",
       "8                0.900952              31             104               5   \n",
       "9                0.916964             122             163              28   \n",
       "10               0.888889              57             228               4   \n",
       "11               0.865121               0             285               0   \n",
       "12               0.892171              66             219              16   \n",
       "13               0.888998              58             227              10   \n",
       "14               0.898254              81             204              27   \n",
       "15               0.877580              30             255               0   \n",
       "16               0.882809              43             242               5   \n",
       "17               0.900199              84             201              15   \n",
       "18               0.909154              20             131              11   \n",
       "19               0.900341               5             146               3   \n",
       "20               0.897488               0             151               0   \n",
       "21               0.899932               4             147               0   \n",
       "22               0.899251               3             148               1   \n",
       "23               0.899320               3             148               0   \n",
       "24               0.910354              22             129              12   \n",
       "25               0.910926              23             128              13   \n",
       "26               0.910677              23             128              17   \n",
       "\n",
       "    metrics.prc.tp  metrics.tuning.threshold  metrics.tuning.cohen_kappa  \\\n",
       "0                0                     0.201                    0.097081   \n",
       "1              933                     0.396                    0.234950   \n",
       "2              942                     0.445                    0.178185   \n",
       "3              951                     0.000                    0.000000   \n",
       "4              951                     0.081                    0.025661   \n",
       "5              947                     0.471                    0.292451   \n",
       "6              929                     0.491                    0.412532   \n",
       "7              948                     0.212                    0.305085   \n",
       "8              946                     0.115                    0.327367   \n",
       "9             1800                     0.339                    0.515887   \n",
       "10            1824                     0.311                    0.295998   \n",
       "11            1828                     0.000                    0.000000   \n",
       "12            1812                     0.126                    0.318603   \n",
       "13            1818                     0.197                    0.287268   \n",
       "14            1801                     0.486                    0.365151   \n",
       "15            1828                     0.491                    0.166579   \n",
       "16            1823                     0.132                    0.223353   \n",
       "17            1813                     0.131                    0.395456   \n",
       "18            1311                     0.290                    0.191548   \n",
       "19            1319                     0.281                    0.053125   \n",
       "20            1322                     0.000                    0.000000   \n",
       "21            1322                     0.037                    0.046568   \n",
       "22            1321                     0.064                    0.033596   \n",
       "23            1322                     0.466                    0.035107   \n",
       "24            1310                     0.493                    0.229014   \n",
       "25            1309                     0.228                    0.215006   \n",
       "26            1305                     0.148                    0.272373   \n",
       "\n",
       "    metrics.tuning.f1  metrics.tuning.recall  metrics.tuning.precision  \\\n",
       "0            0.936884               0.998948                  0.882080   \n",
       "1            0.935807               0.981073                  0.894535   \n",
       "2            0.936847               0.990536                  0.888679   \n",
       "3            0.933726               1.000000                  0.875691   \n",
       "4            0.934644               1.000000                  0.877306   \n",
       "5            0.944167               0.995794                  0.897630   \n",
       "6            0.945233               0.980021                  0.912831   \n",
       "7            0.945165               0.996845                  0.898578   \n",
       "8            0.945527               0.994742                  0.900952   \n",
       "9            0.949618               0.984683                  0.916964   \n",
       "10           0.940206               0.997812                  0.888889   \n",
       "11           0.927683               1.000000                  0.865121   \n",
       "12           0.939103               0.991247                  0.892171   \n",
       "13           0.938565               0.994530                  0.888563   \n",
       "14           0.939734               0.985230                  0.898254   \n",
       "15           0.934254               0.998906                  0.877463   \n",
       "16           0.936312               0.997265                  0.882381   \n",
       "17           0.943779               0.991794                  0.900199   \n",
       "18           0.948625               0.991679                  0.909154   \n",
       "19           0.946537               0.997731                  0.900341   \n",
       "20           0.945975               1.000000                  0.897488   \n",
       "21           0.947331               1.000000                  0.899932   \n",
       "22           0.946614               0.999244                  0.899251   \n",
       "23           0.946991               1.000000                  0.899320   \n",
       "24           0.947636               0.985628                  0.912465   \n",
       "25           0.948895               0.990166                  0.910926   \n",
       "26           0.947368               0.980333                  0.916549   \n",
       "\n",
       "    metrics.tuning.tn  metrics.tuning.fp  metrics.tuning.fn  \\\n",
       "0                   8                127                  1   \n",
       "1                  25                110                 18   \n",
       "2                  17                118                  9   \n",
       "3                   0                135                  0   \n",
       "4                   2                133                  0   \n",
       "5                  27                108                  4   \n",
       "6                  46                 89                 19   \n",
       "7                  28                107                  3   \n",
       "8                  31                104                  5   \n",
       "9                 122                163                 28   \n",
       "10                 57                228                  4   \n",
       "11                  0                285                  0   \n",
       "12                 66                219                 16   \n",
       "13                 57                228                 10   \n",
       "14                 81                204                 27   \n",
       "15                 30                255                  2   \n",
       "16                 42                243                  5   \n",
       "17                 84                201                 15   \n",
       "18                 20                131                 11   \n",
       "19                  5                146                  3   \n",
       "20                  0                151                  0   \n",
       "21                  4                147                  0   \n",
       "22                  3                148                  1   \n",
       "23                  3                148                  0   \n",
       "24                 26                125                 19   \n",
       "25                 23                128                 13   \n",
       "26                 33                118                 26   \n",
       "\n",
       "    metrics.tuning.tp params.splitter  params.min_weight_fraction_leaf  \\\n",
       "0                 950             NaN                              NaN   \n",
       "1                 933             NaN                              NaN   \n",
       "2                 942            best                             0.45   \n",
       "3                 951             NaN                              NaN   \n",
       "4                 951             NaN                              NaN   \n",
       "5                 947             NaN                              NaN   \n",
       "6                 932             NaN                              NaN   \n",
       "7                 948             NaN                              NaN   \n",
       "8                 946             NaN                              NaN   \n",
       "9                1800             NaN                              NaN   \n",
       "10               1824             NaN                              NaN   \n",
       "11               1828            best                             0.10   \n",
       "12               1812             NaN                              NaN   \n",
       "13               1818             NaN                              NaN   \n",
       "14               1801             NaN                              NaN   \n",
       "15               1826             NaN                              NaN   \n",
       "16               1823             NaN                              NaN   \n",
       "17               1813             NaN                              NaN   \n",
       "18               1311             NaN                              NaN   \n",
       "19               1319             NaN                              NaN   \n",
       "20               1322            best                             0.10   \n",
       "21               1322             NaN                              NaN   \n",
       "22               1321             NaN                              NaN   \n",
       "23               1322             NaN                              NaN   \n",
       "24               1303             NaN                              NaN   \n",
       "25               1309             NaN                              NaN   \n",
       "26               1296             NaN                              NaN   \n",
       "\n",
       "    params.min_impurity_decrease  params.max_leaf_nodes params.criterion  \\\n",
       "0                            NaN                    NaN              NaN   \n",
       "1                            NaN                    NaN              NaN   \n",
       "2                           0.00                   97.0             gini   \n",
       "3                            NaN                    NaN              NaN   \n",
       "4                            NaN                    NaN              NaN   \n",
       "5                            NaN                    NaN              NaN   \n",
       "6                            NaN                    NaN              NaN   \n",
       "7                            NaN                    NaN              NaN   \n",
       "8                            NaN                  106.0              NaN   \n",
       "9                            NaN                    NaN              NaN   \n",
       "10                           NaN                    NaN              NaN   \n",
       "11                          0.05                 1249.0             gini   \n",
       "12                           NaN                    NaN              NaN   \n",
       "13                           NaN                    NaN              NaN   \n",
       "14                           NaN                    NaN              NaN   \n",
       "15                           NaN                    NaN              NaN   \n",
       "16                           NaN                    NaN              NaN   \n",
       "17                           NaN                   99.0              NaN   \n",
       "18                           NaN                    NaN              NaN   \n",
       "19                           NaN                    NaN              NaN   \n",
       "20                          0.05                 1153.0             gini   \n",
       "21                           NaN                    NaN              NaN   \n",
       "22                           NaN                    NaN              NaN   \n",
       "23                           NaN                    NaN              NaN   \n",
       "24                           NaN                    NaN              NaN   \n",
       "25                           NaN                    NaN              NaN   \n",
       "26                           NaN                  106.0              NaN   \n",
       "\n",
       "    params.ccp_alpha params.weights  params.p  params.n_neighbors  \\\n",
       "0                NaN            NaN       NaN                 NaN   \n",
       "1                NaN            NaN       NaN                 NaN   \n",
       "2                0.0            NaN       NaN                 NaN   \n",
       "3                NaN       distance       1.0                11.0   \n",
       "4                NaN            NaN       NaN                 NaN   \n",
       "5                NaN            NaN       NaN                 NaN   \n",
       "6                NaN            NaN       NaN                 NaN   \n",
       "7                NaN            NaN       NaN                 NaN   \n",
       "8                NaN            NaN       NaN                 NaN   \n",
       "9                NaN            NaN       NaN                 NaN   \n",
       "10               NaN            NaN       NaN                 NaN   \n",
       "11               0.0            NaN       NaN                 NaN   \n",
       "12               NaN       distance       1.0                 2.0   \n",
       "13               NaN            NaN       NaN                 NaN   \n",
       "14               NaN            NaN       NaN                 NaN   \n",
       "15               NaN            NaN       NaN                 NaN   \n",
       "16               NaN            NaN       NaN                 NaN   \n",
       "17               NaN            NaN       NaN                 NaN   \n",
       "18               NaN            NaN       NaN                 NaN   \n",
       "19               NaN            NaN       NaN                 NaN   \n",
       "20               0.0            NaN       NaN                 NaN   \n",
       "21               NaN       distance       1.0                12.0   \n",
       "22               NaN            NaN       NaN                 NaN   \n",
       "23               NaN            NaN       NaN                 NaN   \n",
       "24               NaN            NaN       NaN                 NaN   \n",
       "25               NaN            NaN       NaN                 NaN   \n",
       "26               NaN            NaN       NaN                 NaN   \n",
       "\n",
       "   params.metric  params.leaf_size params.algorithm  params.tol  \\\n",
       "0            NaN               NaN              NaN         NaN   \n",
       "1            NaN               NaN              NaN         NaN   \n",
       "2            NaN               NaN              NaN         NaN   \n",
       "3      manhattan              44.0            brute         NaN   \n",
       "4            NaN               NaN              NaN       0.006   \n",
       "5            NaN               NaN          SAMME.R         NaN   \n",
       "6            NaN               NaN          SAMME.R         NaN   \n",
       "7            NaN               NaN              NaN         NaN   \n",
       "8            NaN               NaN              NaN         NaN   \n",
       "9            NaN               NaN              NaN         NaN   \n",
       "10           NaN               NaN              NaN         NaN   \n",
       "11           NaN               NaN              NaN         NaN   \n",
       "12     manhattan              30.0          kd_tree         NaN   \n",
       "13           NaN               NaN              NaN       0.007   \n",
       "14           NaN               NaN          SAMME.R         NaN   \n",
       "15           NaN               NaN          SAMME.R         NaN   \n",
       "16           NaN               NaN              NaN         NaN   \n",
       "17           NaN               NaN              NaN         NaN   \n",
       "18           NaN               NaN              NaN         NaN   \n",
       "19           NaN               NaN              NaN         NaN   \n",
       "20           NaN               NaN              NaN         NaN   \n",
       "21     manhattan              44.0          kd_tree         NaN   \n",
       "22           NaN               NaN              NaN       0.004   \n",
       "23           NaN               NaN          SAMME.R         NaN   \n",
       "24           NaN               NaN          SAMME.R         NaN   \n",
       "25           NaN               NaN              NaN         NaN   \n",
       "26           NaN               NaN              NaN         NaN   \n",
       "\n",
       "   params.shrinking params.probability params.kernel  params.gamma  \\\n",
       "0               NaN                NaN           NaN           NaN   \n",
       "1               NaN                NaN           NaN           NaN   \n",
       "2               NaN                NaN           NaN           NaN   \n",
       "3               NaN                NaN           NaN           NaN   \n",
       "4              True               True           rbf         0.811   \n",
       "5               NaN                NaN           NaN           NaN   \n",
       "6               NaN                NaN           NaN           NaN   \n",
       "7               NaN                NaN           NaN         0.650   \n",
       "8               NaN                NaN           NaN           NaN   \n",
       "9               NaN                NaN           NaN           NaN   \n",
       "10              NaN                NaN           NaN           NaN   \n",
       "11              NaN                NaN           NaN           NaN   \n",
       "12              NaN                NaN           NaN           NaN   \n",
       "13            False               True           rbf         0.816   \n",
       "14              NaN                NaN           NaN           NaN   \n",
       "15              NaN                NaN           NaN           NaN   \n",
       "16              NaN                NaN           NaN         0.050   \n",
       "17              NaN                NaN           NaN           NaN   \n",
       "18              NaN                NaN           NaN           NaN   \n",
       "19              NaN                NaN           NaN           NaN   \n",
       "20              NaN                NaN           NaN           NaN   \n",
       "21              NaN                NaN           NaN           NaN   \n",
       "22             True               True           rbf         0.846   \n",
       "23              NaN                NaN           NaN           NaN   \n",
       "24              NaN                NaN           NaN           NaN   \n",
       "25              NaN                NaN           NaN         0.400   \n",
       "26              NaN                NaN           NaN           NaN   \n",
       "\n",
       "   params.decision_function_shape  params.C params.replacement  \\\n",
       "0                             NaN       NaN                NaN   \n",
       "1                             NaN       NaN                NaN   \n",
       "2                             NaN       NaN                NaN   \n",
       "3                             NaN       NaN                NaN   \n",
       "4                             ovo      2.85                NaN   \n",
       "5                             NaN       NaN               True   \n",
       "6                             NaN       NaN                NaN   \n",
       "7                             NaN       NaN                NaN   \n",
       "8                             NaN       NaN                NaN   \n",
       "9                             NaN       NaN                NaN   \n",
       "10                            NaN       NaN                NaN   \n",
       "11                            NaN       NaN                NaN   \n",
       "12                            NaN       NaN                NaN   \n",
       "13                            ovo      4.35                NaN   \n",
       "14                            NaN       NaN               True   \n",
       "15                            NaN       NaN                NaN   \n",
       "16                            NaN       NaN                NaN   \n",
       "17                            NaN       NaN                NaN   \n",
       "18                            NaN       NaN                NaN   \n",
       "19                            NaN       NaN                NaN   \n",
       "20                            NaN       NaN                NaN   \n",
       "21                            NaN       NaN                NaN   \n",
       "22                            ovo      8.60                NaN   \n",
       "23                            NaN       NaN               True   \n",
       "24                            NaN       NaN                NaN   \n",
       "25                            NaN       NaN                NaN   \n",
       "26                            NaN       NaN                NaN   \n",
       "\n",
       "    params.learning_rate  params.subsample  params.seed  \\\n",
       "0                    NaN               NaN          NaN   \n",
       "1                    NaN               NaN          NaN   \n",
       "2                    NaN               NaN          NaN   \n",
       "3                    NaN               NaN          NaN   \n",
       "4                    NaN               NaN          NaN   \n",
       "5                 0.0930               NaN          NaN   \n",
       "6                 0.4000               NaN          NaN   \n",
       "7                 0.0090              0.95       2022.0   \n",
       "8                 0.0365               NaN          NaN   \n",
       "9                    NaN               NaN          NaN   \n",
       "10                   NaN               NaN          NaN   \n",
       "11                   NaN               NaN          NaN   \n",
       "12                   NaN               NaN          NaN   \n",
       "13                   NaN               NaN          NaN   \n",
       "14                0.0810               NaN          NaN   \n",
       "15                0.4500               NaN          NaN   \n",
       "16                0.0090              0.90       2022.0   \n",
       "17                0.0160               NaN          NaN   \n",
       "18                   NaN               NaN          NaN   \n",
       "19                   NaN               NaN          NaN   \n",
       "20                   NaN               NaN          NaN   \n",
       "21                   NaN               NaN          NaN   \n",
       "22                   NaN               NaN          NaN   \n",
       "23                0.0670               NaN          NaN   \n",
       "24                0.4500               NaN          NaN   \n",
       "25                0.0070              0.90       2022.0   \n",
       "26                0.0490               NaN          NaN   \n",
       "\n",
       "    params.scale_pos_weight params.objective  params.lambda  \\\n",
       "0                       NaN              NaN            NaN   \n",
       "1                       NaN              NaN            NaN   \n",
       "2                       NaN              NaN            NaN   \n",
       "3                       NaN              NaN            NaN   \n",
       "4                       NaN              NaN            NaN   \n",
       "5                       NaN              NaN            NaN   \n",
       "6                       NaN              NaN            NaN   \n",
       "7                  2.187097  binary:logistic            0.6   \n",
       "8                       NaN              NaN            NaN   \n",
       "9                       NaN              NaN            NaN   \n",
       "10                      NaN              NaN            NaN   \n",
       "11                      NaN              NaN            NaN   \n",
       "12                      NaN              NaN            NaN   \n",
       "13                      NaN              NaN            NaN   \n",
       "14                      NaN              NaN            NaN   \n",
       "15                      NaN              NaN            NaN   \n",
       "16                 2.398345  binary:logistic            0.1   \n",
       "17                      NaN              NaN            NaN   \n",
       "18                      NaN              NaN            NaN   \n",
       "19                      NaN              NaN            NaN   \n",
       "20                      NaN              NaN            NaN   \n",
       "21                      NaN              NaN            NaN   \n",
       "22                      NaN              NaN            NaN   \n",
       "23                      NaN              NaN            NaN   \n",
       "24                      NaN              NaN            NaN   \n",
       "25                 2.139746  binary:logistic            0.1   \n",
       "26                      NaN              NaN            NaN   \n",
       "\n",
       "   params.eval_metric  params.colsample_bytree params.scoring  \\\n",
       "0                 NaN                      NaN            NaN   \n",
       "1                 NaN                      NaN            NaN   \n",
       "2                 NaN                      NaN            NaN   \n",
       "3                 NaN                      NaN            NaN   \n",
       "4                 NaN                      NaN            NaN   \n",
       "5                 NaN                      NaN            NaN   \n",
       "6                 NaN                      NaN            NaN   \n",
       "7                 auc                      0.7            NaN   \n",
       "8                 NaN                      NaN        roc_auc   \n",
       "9                 NaN                      NaN            NaN   \n",
       "10                NaN                      NaN            NaN   \n",
       "11                NaN                      NaN            NaN   \n",
       "12                NaN                      NaN            NaN   \n",
       "13                NaN                      NaN            NaN   \n",
       "14                NaN                      NaN            NaN   \n",
       "15                NaN                      NaN            NaN   \n",
       "16              aucpr                      0.8            NaN   \n",
       "17                NaN                      NaN        roc_auc   \n",
       "18                NaN                      NaN            NaN   \n",
       "19                NaN                      NaN            NaN   \n",
       "20                NaN                      NaN            NaN   \n",
       "21                NaN                      NaN            NaN   \n",
       "22                NaN                      NaN            NaN   \n",
       "23                NaN                      NaN            NaN   \n",
       "24                NaN                      NaN            NaN   \n",
       "25              aucpr                      0.5            NaN   \n",
       "26                NaN                      NaN             f1   \n",
       "\n",
       "    params.max_iter          params.loss  params.l2_regularization  \n",
       "0               NaN                  NaN                       NaN  \n",
       "1               NaN                  NaN                       NaN  \n",
       "2               NaN                  NaN                       NaN  \n",
       "3               NaN                  NaN                       NaN  \n",
       "4               NaN                  NaN                       NaN  \n",
       "5               NaN                  NaN                       NaN  \n",
       "6               NaN                  NaN                       NaN  \n",
       "7               NaN                  NaN                       NaN  \n",
       "8             350.0  binary_crossentropy                      0.00  \n",
       "9               NaN                  NaN                       NaN  \n",
       "10              NaN                  NaN                       NaN  \n",
       "11              NaN                  NaN                       NaN  \n",
       "12              NaN                  NaN                       NaN  \n",
       "13              NaN                  NaN                       NaN  \n",
       "14              NaN                  NaN                       NaN  \n",
       "15              NaN                  NaN                       NaN  \n",
       "16              NaN                  NaN                       NaN  \n",
       "17            400.0  binary_crossentropy                      0.40  \n",
       "18              NaN                  NaN                       NaN  \n",
       "19              NaN                  NaN                       NaN  \n",
       "20              NaN                  NaN                       NaN  \n",
       "21              NaN                  NaN                       NaN  \n",
       "22              NaN                  NaN                       NaN  \n",
       "23              NaN                  NaN                       NaN  \n",
       "24              NaN                  NaN                       NaN  \n",
       "25              NaN                  NaN                       NaN  \n",
       "26            275.0  binary_crossentropy                      0.15  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SPECIESES = [\"1\", \"2\", \"1 2\"]\n",
    "MODELS = [\"RandomForestClassifier\", \"BalancedRandomForestClassifier\", \"DecisionTreeClassifier\", \"KNeighborsClassifier\", \"SVM\", \"RUSBoostClassifier\" , \"AdaBoostClassifier\", \"XGBClassifier\", \"HistGradientBoostingClassifier\"]\n",
    "TARGET = \"is_damaged\"\n",
    "\n",
    "binary_classifcation_results = list()\n",
    "\n",
    "for SPECIES in SPECIESES:\n",
    "    num_cols = [col for col in binned_data[SPECIES][\"train\"].columns if (binned_data[SPECIES][\"train\"][col].dtype != object)]\n",
    "    sampling_strategy_over_sample = {\n",
    "        \"healthy\": dict(Counter(binned_data[SPECIES][\"train\"][\"damage_class_group\"]))[\"healthy\"],\n",
    "        \"damaged\": dict(Counter(binned_data[SPECIES][\"train\"][\"damage_class_group\"]))[\"damaged\"],\n",
    "        \"dead\": dict(Counter(binned_data[SPECIES][\"train\"][\"damage_class_group\"]))[\"healthy\"]\n",
    "    }\n",
    "    sampler = SMOTEENN(sampling_strategy=sampling_strategy_over_sample, smote=SMOTE(random_state=2022, k_neighbors=6, sampling_strategy=sampling_strategy_over_sample), enn=EditedNearestNeighbours(n_neighbors=5, kind_sel=\"mode\", n_jobs=58), random_state=2022, n_jobs=58)\n",
    "    X_resampled, y_resampled = sampler.fit_resample(X=binned_data[SPECIES][\"train\"][num_cols], y=binned_data[SPECIES][\"train\"][\"damage_class_group\"])\n",
    "    \n",
    "    # over sample (TARGET WILL BECOME TWICE NUMBERS)\n",
    "    sampling_strategy_under_sample = {\n",
    "        \"healthy\": dict(Counter(y_resampled))[\"healthy\"],\n",
    "        \"damaged\": dict(Counter(y_resampled))[\"healthy\"],\n",
    "        \"dead\": dict(Counter(y_resampled))[\"dead\"]\n",
    "    }\n",
    "    under_sampler = RandomUnderSampler(random_state=2022, sampling_strategy=sampling_strategy_under_sample)\n",
    "    X_resampled, y_resampled = under_sampler.fit_resample(X=X_resampled[num_cols], y=y_resampled)\n",
    "\n",
    "    for MODEL in MODELS:\n",
    "        if os.path.exists(f\"{EXPORT_PATH}/{MODEL}_{SPECIES_CODE[SPECIES]}_{TARGET}.json\"):\n",
    "            continue\n",
    "        print(\"-\"*100)\n",
    "        print(f\"{MODEL} -> {SPECIES_CODE[SPECIES]}@{TARGET}\")\n",
    "        print(\"\\t performing backward feature elemination...\")\n",
    "        try:\n",
    "            init_model_params = get_model_params(_model=MODEL, _target=TARGET, _species=SPECIES_CODE[SPECIES])\n",
    "        except FileNotFoundError:\n",
    "            init_model_params = {}\n",
    "            \n",
    "        if \"class_weight\" in init_model_params:\n",
    "            init_model_params[\"class_weight\"] = define_class_weight(X_resampled[TARGET])\n",
    "        if \"pos_scale\" in init_model_params:\n",
    "            init_model_params[\"pos_scale\"] = define_pos_scale(X_resampled[TARGET])\n",
    "\n",
    "        skf = StratifiedKFold(n_splits=3, shuffle=True, random_state=2022)\n",
    "        f1_scorer = metrics.make_scorer(metrics.f1_score, **{\"average\": \"weighted\"})\n",
    "\n",
    "        if MODEL == \"RandomForestClassifier\":\n",
    "            model = RandomForestClassifier(**init_model_params)\n",
    "        elif MODEL == \"XGBClassifier\":\n",
    "            model = xgb.XGBClassifier(**init_model_params)\n",
    "        elif MODEL == \"KNeighborsClassifier\":\n",
    "            model = KNeighborsClassifier(**init_model_params)\n",
    "        elif MODEL == \"DecisionTreeClassifier\":\n",
    "            model = DecisionTreeClassifier(**init_model_params)\n",
    "        elif MODEL == \"HistGradientBoostingClassifier\":\n",
    "            model = HistGradientBoostingClassifier(**init_model_params)\n",
    "        elif MODEL == \"BalancedRandomForestClassifier\":\n",
    "            model = BalancedRandomForestClassifier(**init_model_params)\n",
    "        elif MODEL == \"RUSBoostClassifier\":\n",
    "            model = RUSBoostClassifier(**init_model_params)\n",
    "        elif MODEL == \"AdaBoostClassifier\":\n",
    "            model = AdaBoostClassifier(**init_model_params)\n",
    "        else: #SVM\n",
    "            model = SVC(**init_model_params)\n",
    "\n",
    "        sfs = SequentialFeatureSelector(estimator=model, direction=\"backward\", scoring=f1_scorer, cv=skf, n_jobs=58)\n",
    "        sfs.fit(X_resampled[all_features], X_resampled[TARGET])\n",
    "        relevant_features = list(X_resampled[all_features].columns[sfs.get_support()])\n",
    "\n",
    "        # TRAINING DATA\n",
    "        X_train = X_resampled[relevant_features]\n",
    "        y_train = X_resampled[TARGET]\n",
    "        # TEST DATA\n",
    "        X_test = binned_data[SPECIES][\"test\"][relevant_features]\n",
    "        y_test = binned_data[SPECIES][\"test\"][TARGET]\n",
    "\n",
    "        print(\"\\t performing hyperparameter tuning...\")\n",
    "\n",
    "        if MODEL == \"RandomForestClassifier\":\n",
    "            params_rf = PARAMS_RF\n",
    "            params_rf[\"class_weight\"] = [define_class_weight(y_train.values)]\n",
    "            fitted_model_params = parameter_tuning(_model=RandomForestClassifier(), _params=params_rf, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = RandomForestClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"XGBClassifier\":\n",
    "            params_xgb = PARAMS_XGB\n",
    "            params_xgb['scale_pos_weight'] = [define_pos_scale(y_train.values)]\n",
    "            fitted_model_params = parameter_tuning(_model=xgb.XGBClassifier(), _params=params_xgb, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = xgb.XGBClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"KNeighborsClassifier\":\n",
    "            params_kn = PARAMS_KN\n",
    "            fitted_model_params = parameter_tuning(_model=KNeighborsClassifier(), _params=params_kn, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = KNeighborsClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"DecisionTreeClassifier\":\n",
    "            params_dt = PARAMS_DT\n",
    "            params_dt['class_weight'] = [define_class_weight(y_train.values)]\n",
    "            fitted_model_params = parameter_tuning(_model=DecisionTreeClassifier(), _params=params_dt, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = DecisionTreeClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"HistGradientBoostingClassifier\":\n",
    "            params_hgb = PARAMS_HGB\n",
    "            fitted_model_params = parameter_tuning(_model=HistGradientBoostingClassifier(), _params=params_hgb, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = HistGradientBoostingClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"BalancedRandomForestClassifier\":\n",
    "            params_brf = PARAMS_BRF\n",
    "            fitted_model_params = parameter_tuning(_model=BalancedRandomForestClassifier(), _params=params_brf, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = BalancedRandomForestClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"RUSBoostClassifier\":\n",
    "            params_rus = PARAMS_RUS\n",
    "            fitted_model_params = parameter_tuning(_model=RUSBoostClassifier(), _params=params_rus, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = RUSBoostClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"AdaBoostClassifier\":\n",
    "            params_ada = PARAMS_ADA\n",
    "            fitted_model_params = parameter_tuning(_model=AdaBoostClassifier(), _params=params_ada, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = AdaBoostClassifier(**fitted_model_params)\n",
    "        else:\n",
    "            params_svm = PARAMS_SVM\n",
    "            params_svm['class_weight'] = [define_class_weight(y_train.values)]\n",
    "            fitted_model_params = parameter_tuning(_model=SVC(), _params=params_svm, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = SVC(**fitted_model_params)\n",
    "\n",
    "        # CREATING BAGGING CLASSIFIER\n",
    "        model = BaggingClassifier(base_estimator=model, n_estimators=15, max_samples=.2, max_features=1., bootstrap=True, bootstrap_features=True, oob_score=True, n_jobs=16)\n",
    "        print(\"\\t fitting model...\")\n",
    "        model.fit(X_train, y_train)\n",
    "        # save model\n",
    "        pickle.dump(model, open(f\"{EXPORT_PATH}/{MODEL}_{SPECIES_CODE[SPECIES]}_{TARGET}.sav\", 'wb'))\n",
    "\n",
    "        # predict probabilities\n",
    "        y_pred_proba = model.predict_proba(X_test)\n",
    "\n",
    "        print(\"\\t performing permutation feature importance...\")\n",
    "        from sklearn.inspection import permutation_importance\n",
    "        permutation_importance = permutation_importance(model, X_test, y_test, n_repeats=5, random_state=2022, n_jobs=32, scoring=f1_scorer)\n",
    "        permutation_importance_obj = {}\n",
    "        for i, feat_imp in enumerate(permutation_importance.importances_mean):\n",
    "            permutation_importance_obj[all_features[i]] = feat_imp\n",
    "\n",
    "        print(\"\\t evaluating...\")\n",
    "        results = {}\n",
    "        results[\"species\"] = SPECIES_CODE[SPECIES]\n",
    "        results[\"model\"] = MODEL\n",
    "        results[\"target\"] = TARGET\n",
    "        results[\"params\"] = fitted_model_params\n",
    "        results[\"relevant_features\"] = relevant_features\n",
    "        results[\"feature_permutaion_importance\"] = permutation_importance_obj\n",
    "\n",
    "        results[\"metrics\"] = {}\n",
    "        results[\"metrics\"][\"auc\"] = metrics.roc_auc_score(y_test.values, y_pred_proba[:, 1])\n",
    "\n",
    "        ## ROC AUC\n",
    "        results[\"metrics\"][\"roc\"] = {}\n",
    "        threshold_roc, gmean_roc = roc_auc(y_test.values, y_pred_proba[:,1], axes=None)\n",
    "        results[\"metrics\"][\"roc\"][\"threshold\"] = threshold_roc\n",
    "        y_pred_roc = apply_prediction(y_pred_proba[:, 1], threshold_roc)\n",
    "        results[\"metrics\"][\"roc\"][\"cohen_kappa\"] = metrics.cohen_kappa_score(y_test.values, y_pred_roc)\n",
    "        results[\"metrics\"][\"roc\"][\"f1\"] = metrics.f1_score(y_test.values, y_pred_roc)\n",
    "        results[\"metrics\"][\"roc\"][\"recall\"] = metrics.recall_score(y_test.values, y_pred_roc)\n",
    "        results[\"metrics\"][\"roc\"][\"precision\"] = metrics.precision_score(y_test.values, y_pred_roc)\n",
    "        tn, fp, fn, tp = metrics.confusion_matrix(y_test, y_pred_roc).ravel()\n",
    "        results[\"metrics\"][\"roc\"][\"tn\"] = tn\n",
    "        results[\"metrics\"][\"roc\"][\"fp\"] = fp\n",
    "        results[\"metrics\"][\"roc\"][\"fn\"] = fn\n",
    "        results[\"metrics\"][\"roc\"][\"tp\"] = tp\n",
    "\n",
    "        ## PRC\n",
    "        results[\"metrics\"][\"prc\"] = {}\n",
    "        threshold_prc, fscore_prc = prc_rc(y_test.values, y_pred_proba[:,1], axes=None)\n",
    "        results[\"metrics\"][\"prc\"][\"threshold\"] = threshold_prc\n",
    "        y_pred_prc = apply_prediction(y_pred_proba[:, 1], threshold_prc)\n",
    "        results[\"metrics\"][\"prc\"][\"cohen_kappa\"] = metrics.cohen_kappa_score(y_test.values, y_pred_prc)\n",
    "        results[\"metrics\"][\"prc\"][\"f1\"] = metrics.f1_score(y_test.values, y_pred_prc)\n",
    "        results[\"metrics\"][\"prc\"][\"recall\"] = metrics.recall_score(y_test.values, y_pred_prc)\n",
    "        results[\"metrics\"][\"prc\"][\"precision\"] = metrics.precision_score(y_test.values, y_pred_prc)\n",
    "        tn, fp, fn, tp = metrics.confusion_matrix(y_test, y_pred_prc).ravel()\n",
    "        results[\"metrics\"][\"prc\"][\"tn\"] = tn\n",
    "        results[\"metrics\"][\"prc\"][\"fp\"] = fp\n",
    "        results[\"metrics\"][\"prc\"][\"fn\"] = fn\n",
    "        results[\"metrics\"][\"prc\"][\"tp\"] = tp\n",
    "\n",
    "        ## TUNING\n",
    "        results[\"metrics\"][\"tuning\"] = {}\n",
    "        threshold_tuning, fscore_tuneing = tune_threshold(y_test.values, y_pred_proba[:,1], axes=None)\n",
    "        results[\"metrics\"][\"tuning\"][\"threshold\"] = threshold_tuning\n",
    "        y_pred_tuning = apply_prediction(y_pred_proba[:, 1], threshold_tuning)\n",
    "        results[\"metrics\"][\"tuning\"][\"cohen_kappa\"] = metrics.cohen_kappa_score(y_test.values, y_pred_tuning)\n",
    "        results[\"metrics\"][\"tuning\"][\"f1\"] = metrics.f1_score(y_test.values, y_pred_tuning)\n",
    "        results[\"metrics\"][\"tuning\"][\"recall\"] = metrics.recall_score(y_test.values, y_pred_tuning)\n",
    "        results[\"metrics\"][\"tuning\"][\"precision\"] = metrics.precision_score(y_test.values, y_pred_tuning)\n",
    "        tn, fp, fn, tp = metrics.confusion_matrix(y_test, y_pred_tuning).ravel()\n",
    "        results[\"metrics\"][\"tuning\"][\"tn\"] = tn\n",
    "        results[\"metrics\"][\"tuning\"][\"fp\"] = fp\n",
    "        results[\"metrics\"][\"tuning\"][\"fn\"] = fn\n",
    "        results[\"metrics\"][\"tuning\"][\"tp\"] = tp\n",
    "\n",
    "        # quick export to dump data\n",
    "        with open(f\"{EXPORT_PATH}/{MODEL}_{SPECIES_CODE[SPECIES]}_{TARGET}.json\", 'w', encoding='utf-8') as f:\n",
    "            json.dump(str(dict((k, v) for k,v in results.items())), f, ensure_ascii=False, indent=4)\n",
    "        pd.json_normalize(results).to_csv(f\"{EXPORT_PATH}/{MODEL}_{SPECIES_CODE[SPECIES]}_{TARGET}.csv\", index=False)\n",
    "\n",
    "        binary_classifcation_results.append(results)\n",
    "\n",
    "print(\"-\"*75)\n",
    "print(f\"EXPORTING OVERALL RESULTS TO {EXPORT_PATH}/modelling_pipeline_results.csv\")\n",
    "print(\"-\"*75)\n",
    "df_result = pd.json_normalize(binary_classifcation_results)\n",
    "df_result.to_csv(f\"{EXPORT_PATH}/modelling_pipeline_results.csv\", index=False)\n",
    "df_result"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a170eaa-9d46-4320-ad15-1d7e36dcd416",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### Dead Vegetation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "2c21f98b-cdbf-4b9e-9ff8-b8250b77c2ba",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-04-08T04:27:29.285994Z",
     "iopub.status.busy": "2022-04-08T04:27:29.285994Z",
     "iopub.status.idle": "2022-04-08T21:30:09.578477Z",
     "shell.execute_reply": "2022-04-08T21:30:09.578477Z",
     "shell.execute_reply.started": "2022-04-08T04:27:29.285994Z"
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "----------------------------------------------------------------------------------------------------\n",
      "RandomForestClassifier -> Deciduous@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "BalancedRandomForestClassifier -> Deciduous@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "DecisionTreeClassifier -> Deciduous@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "KNeighborsClassifier -> Deciduous@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "SVM -> Deciduous@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "RUSBoostClassifier -> Deciduous@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "AdaBoostClassifier -> Deciduous@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "XGBClassifier -> Deciduous@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "HistGradientBoostingClassifier -> Deciduous@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "RandomForestClassifier -> Conifer@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "BalancedRandomForestClassifier -> Conifer@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "DecisionTreeClassifier -> Conifer@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "KNeighborsClassifier -> Conifer@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "SVM -> Conifer@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "RUSBoostClassifier -> Conifer@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "AdaBoostClassifier -> Conifer@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "XGBClassifier -> Conifer@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "HistGradientBoostingClassifier -> Conifer@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "RandomForestClassifier -> Mixed@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "BalancedRandomForestClassifier -> Mixed@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "DecisionTreeClassifier -> Mixed@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "KNeighborsClassifier -> Mixed@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "SVM -> Mixed@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "RUSBoostClassifier -> Mixed@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "AdaBoostClassifier -> Mixed@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "XGBClassifier -> Mixed@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "HistGradientBoostingClassifier -> Mixed@is_dead\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "---------------------------------------------------------------------------\n",
      "EXPORTING OVERALL RESULTS TO ./results/optimization/v5/modelling_pipeline_results.csv\n",
      "---------------------------------------------------------------------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>species</th>\n",
       "      <th>model</th>\n",
       "      <th>target</th>\n",
       "      <th>relevant_features</th>\n",
       "      <th>params.warm_start</th>\n",
       "      <th>params.random_state</th>\n",
       "      <th>params.n_jobs</th>\n",
       "      <th>params.n_estimators</th>\n",
       "      <th>params.min_samples_split</th>\n",
       "      <th>params.min_samples_leaf</th>\n",
       "      <th>params.max_features</th>\n",
       "      <th>params.max_depth</th>\n",
       "      <th>params.class_weight.0</th>\n",
       "      <th>params.class_weight.1</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_0</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_1</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_2</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_3</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_4</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_5</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_6</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_7</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_8</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_9</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_10</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_11</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_12</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_13</th>\n",
       "      <th>feature_permutaion_importance.tree_1</th>\n",
       "      <th>feature_permutaion_importance.evi2</th>\n",
       "      <th>feature_permutaion_importance.evi2-1</th>\n",
       "      <th>feature_permutaion_importance.evi2_diff</th>\n",
       "      <th>feature_permutaion_importance.evi2_max_diff</th>\n",
       "      <th>feature_permutaion_importance.evi2_raster</th>\n",
       "      <th>feature_permutaion_importance.evi2_raster-1</th>\n",
       "      <th>feature_permutaion_importance.evi2_raster_diff</th>\n",
       "      <th>feature_permutaion_importance.evi2_vegetation_raster</th>\n",
       "      <th>feature_permutaion_importance.evi2_vegetation_raster-1</th>\n",
       "      <th>feature_permutaion_importance.evi2_vegetation_raster_diff</th>\n",
       "      <th>feature_permutaion_importance.ndvi</th>\n",
       "      <th>feature_permutaion_importance.ndvi-1</th>\n",
       "      <th>feature_permutaion_importance.ndvi_diff</th>\n",
       "      <th>metrics.auc</th>\n",
       "      <th>metrics.roc.threshold</th>\n",
       "      <th>metrics.roc.cohen_kappa</th>\n",
       "      <th>metrics.roc.f1</th>\n",
       "      <th>metrics.roc.recall</th>\n",
       "      <th>metrics.roc.precision</th>\n",
       "      <th>metrics.roc.tn</th>\n",
       "      <th>metrics.roc.fp</th>\n",
       "      <th>metrics.roc.fn</th>\n",
       "      <th>metrics.roc.tp</th>\n",
       "      <th>metrics.prc.threshold</th>\n",
       "      <th>metrics.prc.cohen_kappa</th>\n",
       "      <th>metrics.prc.f1</th>\n",
       "      <th>metrics.prc.recall</th>\n",
       "      <th>metrics.prc.precision</th>\n",
       "      <th>metrics.prc.tn</th>\n",
       "      <th>metrics.prc.fp</th>\n",
       "      <th>metrics.prc.fn</th>\n",
       "      <th>metrics.prc.tp</th>\n",
       "      <th>metrics.tuning.threshold</th>\n",
       "      <th>metrics.tuning.cohen_kappa</th>\n",
       "      <th>metrics.tuning.f1</th>\n",
       "      <th>metrics.tuning.recall</th>\n",
       "      <th>metrics.tuning.precision</th>\n",
       "      <th>metrics.tuning.tn</th>\n",
       "      <th>metrics.tuning.fp</th>\n",
       "      <th>metrics.tuning.fn</th>\n",
       "      <th>metrics.tuning.tp</th>\n",
       "      <th>params.splitter</th>\n",
       "      <th>params.min_weight_fraction_leaf</th>\n",
       "      <th>params.min_impurity_decrease</th>\n",
       "      <th>params.max_leaf_nodes</th>\n",
       "      <th>params.criterion</th>\n",
       "      <th>params.ccp_alpha</th>\n",
       "      <th>params.weights</th>\n",
       "      <th>params.p</th>\n",
       "      <th>params.n_neighbors</th>\n",
       "      <th>params.metric</th>\n",
       "      <th>params.leaf_size</th>\n",
       "      <th>params.algorithm</th>\n",
       "      <th>params.tol</th>\n",
       "      <th>params.shrinking</th>\n",
       "      <th>params.probability</th>\n",
       "      <th>params.kernel</th>\n",
       "      <th>params.gamma</th>\n",
       "      <th>params.decision_function_shape</th>\n",
       "      <th>params.C</th>\n",
       "      <th>params.replacement</th>\n",
       "      <th>params.learning_rate</th>\n",
       "      <th>params.subsample</th>\n",
       "      <th>params.seed</th>\n",
       "      <th>params.scale_pos_weight</th>\n",
       "      <th>params.objective</th>\n",
       "      <th>params.lambda</th>\n",
       "      <th>params.eval_metric</th>\n",
       "      <th>params.colsample_bytree</th>\n",
       "      <th>params.scoring</th>\n",
       "      <th>params.max_iter</th>\n",
       "      <th>params.loss</th>\n",
       "      <th>params.l2_regularization</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>RandomForestClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_2, location_cluster_3, locat...</td>\n",
       "      <td>False</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>336.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0.796774</td>\n",
       "      <td>1.342391</td>\n",
       "      <td>-0.006210</td>\n",
       "      <td>-6.968349e-03</td>\n",
       "      <td>-6.019512e-03</td>\n",
       "      <td>-0.002970</td>\n",
       "      <td>-0.004402</td>\n",
       "      <td>-0.006589</td>\n",
       "      <td>-0.006874</td>\n",
       "      <td>-0.005352</td>\n",
       "      <td>-0.001727</td>\n",
       "      <td>0.001253</td>\n",
       "      <td>-0.004401</td>\n",
       "      <td>-0.000576</td>\n",
       "      <td>-2.682255e-03</td>\n",
       "      <td>-0.001056</td>\n",
       "      <td>-0.000859</td>\n",
       "      <td>-0.003161</td>\n",
       "      <td>-1.914322e-04</td>\n",
       "      <td>-1.065061e-02</td>\n",
       "      <td>5.776561e-04</td>\n",
       "      <td>-0.004211</td>\n",
       "      <td>-0.001535</td>\n",
       "      <td>-0.000672</td>\n",
       "      <td>-0.008009</td>\n",
       "      <td>-0.003925</td>\n",
       "      <td>-0.002684</td>\n",
       "      <td>-6.704692e-04</td>\n",
       "      <td>-0.009049</td>\n",
       "      <td>-0.004305</td>\n",
       "      <td>0.572062</td>\n",
       "      <td>0.230730</td>\n",
       "      <td>0.012074</td>\n",
       "      <td>0.028103</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.014354</td>\n",
       "      <td>665</td>\n",
       "      <td>412</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>0.443427</td>\n",
       "      <td>-0.015198</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>993</td>\n",
       "      <td>84</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.389</td>\n",
       "      <td>0.025656</td>\n",
       "      <td>0.040816</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.021739</td>\n",
       "      <td>942</td>\n",
       "      <td>135</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>BalancedRandomForestClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_0, location_cluster_2, locat...</td>\n",
       "      <td>True</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>320.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>96.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.010607</td>\n",
       "      <td>-6.728600e-03</td>\n",
       "      <td>-7.726560e-03</td>\n",
       "      <td>-0.002119</td>\n",
       "      <td>-0.008920</td>\n",
       "      <td>-0.008323</td>\n",
       "      <td>-0.008724</td>\n",
       "      <td>-0.000909</td>\n",
       "      <td>-0.002320</td>\n",
       "      <td>-0.004831</td>\n",
       "      <td>-0.001413</td>\n",
       "      <td>-0.002924</td>\n",
       "      <td>1.624869e-03</td>\n",
       "      <td>-0.005529</td>\n",
       "      <td>-0.012190</td>\n",
       "      <td>-0.016019</td>\n",
       "      <td>-4.730376e-03</td>\n",
       "      <td>-3.124558e-03</td>\n",
       "      <td>-2.316937e-03</td>\n",
       "      <td>-0.007027</td>\n",
       "      <td>-0.004924</td>\n",
       "      <td>-0.006629</td>\n",
       "      <td>-0.000599</td>\n",
       "      <td>-0.011499</td>\n",
       "      <td>-0.018961</td>\n",
       "      <td>-3.325830e-03</td>\n",
       "      <td>-0.005529</td>\n",
       "      <td>-0.013759</td>\n",
       "      <td>0.471165</td>\n",
       "      <td>0.301560</td>\n",
       "      <td>0.002082</td>\n",
       "      <td>0.018349</td>\n",
       "      <td>0.555556</td>\n",
       "      <td>0.009328</td>\n",
       "      <td>546</td>\n",
       "      <td>531</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>0.430567</td>\n",
       "      <td>-0.016095</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>883</td>\n",
       "      <td>194</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.400</td>\n",
       "      <td>0.005963</td>\n",
       "      <td>0.021898</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.011321</td>\n",
       "      <td>815</td>\n",
       "      <td>262</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>DecisionTreeClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_2, location_cluster_3, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>log2</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.796774</td>\n",
       "      <td>1.342391</td>\n",
       "      <td>-0.051592</td>\n",
       "      <td>2.112726e-02</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.028227</td>\n",
       "      <td>-0.025632</td>\n",
       "      <td>-0.070775</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.020836</td>\n",
       "      <td>-0.003673</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.441978e-02</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.009990</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.120815e-02</td>\n",
       "      <td>0.004980</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001717</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>-0.014483</td>\n",
       "      <td>-0.000269</td>\n",
       "      <td>0.431910</td>\n",
       "      <td>0.520115</td>\n",
       "      <td>0.007092</td>\n",
       "      <td>0.023121</td>\n",
       "      <td>0.444444</td>\n",
       "      <td>0.011869</td>\n",
       "      <td>744</td>\n",
       "      <td>333</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>0.551776</td>\n",
       "      <td>-0.016220</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>843</td>\n",
       "      <td>234</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.517</td>\n",
       "      <td>0.007092</td>\n",
       "      <td>0.023121</td>\n",
       "      <td>0.444444</td>\n",
       "      <td>0.011869</td>\n",
       "      <td>744</td>\n",
       "      <td>333</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>best</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.00</td>\n",
       "      <td>801.0</td>\n",
       "      <td>gini</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>KNeighborsClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_4, location_cluster_6, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.018647</td>\n",
       "      <td>-6.797864e-03</td>\n",
       "      <td>3.337381e-04</td>\n",
       "      <td>0.007109</td>\n",
       "      <td>0.003320</td>\n",
       "      <td>-0.002749</td>\n",
       "      <td>0.001879</td>\n",
       "      <td>0.001996</td>\n",
       "      <td>0.000999</td>\n",
       "      <td>-0.006030</td>\n",
       "      <td>0.007447</td>\n",
       "      <td>-0.004281</td>\n",
       "      <td>-3.518166e-03</td>\n",
       "      <td>0.001993</td>\n",
       "      <td>-0.007015</td>\n",
       "      <td>0.001879</td>\n",
       "      <td>1.555866e-02</td>\n",
       "      <td>2.213365e-03</td>\n",
       "      <td>8.999620e-04</td>\n",
       "      <td>-0.006906</td>\n",
       "      <td>-0.011350</td>\n",
       "      <td>0.000885</td>\n",
       "      <td>-0.002309</td>\n",
       "      <td>-0.007015</td>\n",
       "      <td>-0.003078</td>\n",
       "      <td>-5.048628e-03</td>\n",
       "      <td>-0.001981</td>\n",
       "      <td>0.002546</td>\n",
       "      <td>0.502579</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>0.011805</td>\n",
       "      <td>0.027842</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.014218</td>\n",
       "      <td>661</td>\n",
       "      <td>416</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>-0.016402</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>745</td>\n",
       "      <td>332</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.134</td>\n",
       "      <td>0.011805</td>\n",
       "      <td>0.027842</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.014218</td>\n",
       "      <td>661</td>\n",
       "      <td>416</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>uniform</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>manhattan</td>\n",
       "      <td>42.0</td>\n",
       "      <td>kd_tree</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>SVM</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_5, evi2_raster, evi2_vegetat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.796774</td>\n",
       "      <td>1.342391</td>\n",
       "      <td>-0.013728</td>\n",
       "      <td>-1.524097e-02</td>\n",
       "      <td>-1.192576e-02</td>\n",
       "      <td>-0.014295</td>\n",
       "      <td>-0.014862</td>\n",
       "      <td>-0.010117</td>\n",
       "      <td>-0.012114</td>\n",
       "      <td>-0.011070</td>\n",
       "      <td>-0.013444</td>\n",
       "      <td>-0.012966</td>\n",
       "      <td>-0.010021</td>\n",
       "      <td>-0.013440</td>\n",
       "      <td>-7.725528e-03</td>\n",
       "      <td>-0.014485</td>\n",
       "      <td>-0.005902</td>\n",
       "      <td>-0.015147</td>\n",
       "      <td>-1.145041e-02</td>\n",
       "      <td>-8.585087e-03</td>\n",
       "      <td>-1.287407e-02</td>\n",
       "      <td>-0.012875</td>\n",
       "      <td>-0.006664</td>\n",
       "      <td>-0.008875</td>\n",
       "      <td>-0.014485</td>\n",
       "      <td>-0.018723</td>\n",
       "      <td>-0.003104</td>\n",
       "      <td>-6.381594e-03</td>\n",
       "      <td>-0.014011</td>\n",
       "      <td>-0.012866</td>\n",
       "      <td>0.469308</td>\n",
       "      <td>0.035447</td>\n",
       "      <td>0.007407</td>\n",
       "      <td>0.023609</td>\n",
       "      <td>0.777778</td>\n",
       "      <td>0.011986</td>\n",
       "      <td>500</td>\n",
       "      <td>577</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>0.134484</td>\n",
       "      <td>-0.016324</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>795</td>\n",
       "      <td>282</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.035</td>\n",
       "      <td>0.007285</td>\n",
       "      <td>0.023490</td>\n",
       "      <td>0.777778</td>\n",
       "      <td>0.011925</td>\n",
       "      <td>497</td>\n",
       "      <td>580</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.007</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>rbf</td>\n",
       "      <td>0.766</td>\n",
       "      <td>ovo</td>\n",
       "      <td>5.85</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>RUSBoostClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_4, location_cluster_10, loca...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>410.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.006816</td>\n",
       "      <td>-4.439295e-03</td>\n",
       "      <td>-8.309086e-03</td>\n",
       "      <td>-0.015903</td>\n",
       "      <td>-0.010446</td>\n",
       "      <td>-0.001403</td>\n",
       "      <td>-0.004656</td>\n",
       "      <td>-0.003570</td>\n",
       "      <td>0.001437</td>\n",
       "      <td>-0.000385</td>\n",
       "      <td>0.000736</td>\n",
       "      <td>0.002741</td>\n",
       "      <td>-5.328653e-03</td>\n",
       "      <td>-0.000702</td>\n",
       "      <td>-0.004601</td>\n",
       "      <td>0.007834</td>\n",
       "      <td>-1.548265e-02</td>\n",
       "      <td>-5.719070e-03</td>\n",
       "      <td>-2.383058e-03</td>\n",
       "      <td>-0.001445</td>\n",
       "      <td>-0.005561</td>\n",
       "      <td>-0.001882</td>\n",
       "      <td>-0.008221</td>\n",
       "      <td>-0.004072</td>\n",
       "      <td>-0.001787</td>\n",
       "      <td>-6.723447e-03</td>\n",
       "      <td>-0.001868</td>\n",
       "      <td>-0.007150</td>\n",
       "      <td>0.718044</td>\n",
       "      <td>0.492048</td>\n",
       "      <td>0.073240</td>\n",
       "      <td>0.087591</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.046875</td>\n",
       "      <td>955</td>\n",
       "      <td>122</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>0.516331</td>\n",
       "      <td>-0.008357</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1068</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.514</td>\n",
       "      <td>0.097389</td>\n",
       "      <td>0.105263</td>\n",
       "      <td>0.111111</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>1068</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAMME.R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>0.0930</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>AdaBoostClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_1, location_cluster_4, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>320.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.000619</td>\n",
       "      <td>3.755198e-03</td>\n",
       "      <td>8.094120e-03</td>\n",
       "      <td>0.001450</td>\n",
       "      <td>0.000081</td>\n",
       "      <td>0.009271</td>\n",
       "      <td>-0.001987</td>\n",
       "      <td>0.003792</td>\n",
       "      <td>-0.001122</td>\n",
       "      <td>0.004712</td>\n",
       "      <td>0.000406</td>\n",
       "      <td>0.001154</td>\n",
       "      <td>-3.949386e-04</td>\n",
       "      <td>-0.001227</td>\n",
       "      <td>-0.000281</td>\n",
       "      <td>-0.000879</td>\n",
       "      <td>-3.363313e-05</td>\n",
       "      <td>2.700098e-03</td>\n",
       "      <td>-4.076144e-05</td>\n",
       "      <td>0.001060</td>\n",
       "      <td>0.001319</td>\n",
       "      <td>0.001973</td>\n",
       "      <td>-0.000643</td>\n",
       "      <td>-0.003235</td>\n",
       "      <td>0.002073</td>\n",
       "      <td>6.530846e-03</td>\n",
       "      <td>0.000155</td>\n",
       "      <td>0.000066</td>\n",
       "      <td>0.718972</td>\n",
       "      <td>0.483869</td>\n",
       "      <td>0.061774</td>\n",
       "      <td>0.076433</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.040541</td>\n",
       "      <td>935</td>\n",
       "      <td>142</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>0.505838</td>\n",
       "      <td>-0.012201</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1053</td>\n",
       "      <td>24</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.499</td>\n",
       "      <td>0.202073</td>\n",
       "      <td>0.212766</td>\n",
       "      <td>0.555556</td>\n",
       "      <td>0.131579</td>\n",
       "      <td>1044</td>\n",
       "      <td>33</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAMME.R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.4000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>XGBClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_10, tree_1, evi2-1, evi2_ras...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>485.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.003435</td>\n",
       "      <td>7.175136e-03</td>\n",
       "      <td>-6.469896e-04</td>\n",
       "      <td>0.000093</td>\n",
       "      <td>0.006893</td>\n",
       "      <td>0.000185</td>\n",
       "      <td>-0.000277</td>\n",
       "      <td>-0.000647</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000556</td>\n",
       "      <td>0.000278</td>\n",
       "      <td>0.005675</td>\n",
       "      <td>-1.270475e-03</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.002040</td>\n",
       "      <td>0.000278</td>\n",
       "      <td>-5.546114e-04</td>\n",
       "      <td>1.056517e-02</td>\n",
       "      <td>-2.773913e-04</td>\n",
       "      <td>0.005395</td>\n",
       "      <td>0.000278</td>\n",
       "      <td>-0.000092</td>\n",
       "      <td>0.008491</td>\n",
       "      <td>0.000185</td>\n",
       "      <td>0.000093</td>\n",
       "      <td>1.387662e-02</td>\n",
       "      <td>0.000648</td>\n",
       "      <td>-0.000809</td>\n",
       "      <td>0.654699</td>\n",
       "      <td>0.285132</td>\n",
       "      <td>0.044271</td>\n",
       "      <td>0.059406</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.031088</td>\n",
       "      <td>890</td>\n",
       "      <td>187</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>0.406628</td>\n",
       "      <td>-0.014880</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1008</td>\n",
       "      <td>69</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.366</td>\n",
       "      <td>0.053901</td>\n",
       "      <td>0.068376</td>\n",
       "      <td>0.444444</td>\n",
       "      <td>0.037037</td>\n",
       "      <td>973</td>\n",
       "      <td>104</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.800</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0090</td>\n",
       "      <td>0.70</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>1.684783</td>\n",
       "      <td>binary:logistic</td>\n",
       "      <td>0.0</td>\n",
       "      <td>auc</td>\n",
       "      <td>0.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>HistGradientBoostingClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_4, location_cluster_12, tree...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>106.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.007239</td>\n",
       "      <td>-6.711041e-04</td>\n",
       "      <td>-8.842459e-03</td>\n",
       "      <td>-0.000096</td>\n",
       "      <td>-0.000096</td>\n",
       "      <td>-0.002869</td>\n",
       "      <td>-0.006103</td>\n",
       "      <td>0.000864</td>\n",
       "      <td>0.000672</td>\n",
       "      <td>-0.000384</td>\n",
       "      <td>0.000769</td>\n",
       "      <td>-0.000287</td>\n",
       "      <td>7.681793e-04</td>\n",
       "      <td>-0.001437</td>\n",
       "      <td>0.000480</td>\n",
       "      <td>-0.000287</td>\n",
       "      <td>1.248847e-03</td>\n",
       "      <td>-1.917957e-04</td>\n",
       "      <td>-2.010604e-03</td>\n",
       "      <td>-0.002485</td>\n",
       "      <td>0.000192</td>\n",
       "      <td>0.002308</td>\n",
       "      <td>0.000192</td>\n",
       "      <td>0.000192</td>\n",
       "      <td>-0.012321</td>\n",
       "      <td>2.212094e-03</td>\n",
       "      <td>-0.000767</td>\n",
       "      <td>-0.004108</td>\n",
       "      <td>0.642526</td>\n",
       "      <td>0.138111</td>\n",
       "      <td>0.033142</td>\n",
       "      <td>0.048583</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.025210</td>\n",
       "      <td>845</td>\n",
       "      <td>232</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>0.293467</td>\n",
       "      <td>-0.015314</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>986</td>\n",
       "      <td>91</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.137</td>\n",
       "      <td>0.033142</td>\n",
       "      <td>0.048583</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.025210</td>\n",
       "      <td>845</td>\n",
       "      <td>232</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0230</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>roc_auc</td>\n",
       "      <td>400.0</td>\n",
       "      <td>binary_crossentropy</td>\n",
       "      <td>0.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>RandomForestClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_3, location_cluster_5, locat...</td>\n",
       "      <td>True</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>176.0</td>\n",
       "      <td>0.849586</td>\n",
       "      <td>1.215131</td>\n",
       "      <td>-0.000237</td>\n",
       "      <td>-4.267087e-04</td>\n",
       "      <td>-2.845175e-04</td>\n",
       "      <td>-0.000190</td>\n",
       "      <td>-0.000285</td>\n",
       "      <td>-0.000237</td>\n",
       "      <td>-0.001042</td>\n",
       "      <td>-0.000047</td>\n",
       "      <td>-0.000095</td>\n",
       "      <td>-0.000142</td>\n",
       "      <td>0.000427</td>\n",
       "      <td>-0.000047</td>\n",
       "      <td>-9.483164e-05</td>\n",
       "      <td>0.000190</td>\n",
       "      <td>-0.000284</td>\n",
       "      <td>-0.000142</td>\n",
       "      <td>-2.370679e-04</td>\n",
       "      <td>-2.370454e-04</td>\n",
       "      <td>-4.272020e-04</td>\n",
       "      <td>-0.000047</td>\n",
       "      <td>-0.000237</td>\n",
       "      <td>-0.000237</td>\n",
       "      <td>-0.000237</td>\n",
       "      <td>-0.000332</td>\n",
       "      <td>-0.000521</td>\n",
       "      <td>9.492169e-05</td>\n",
       "      <td>0.000047</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.872014</td>\n",
       "      <td>0.129958</td>\n",
       "      <td>0.010599</td>\n",
       "      <td>0.016173</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.008152</td>\n",
       "      <td>1377</td>\n",
       "      <td>730</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0.449513</td>\n",
       "      <td>-0.003688</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2096</td>\n",
       "      <td>11</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.342</td>\n",
       "      <td>0.203308</td>\n",
       "      <td>0.206897</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.130435</td>\n",
       "      <td>2087</td>\n",
       "      <td>20</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>BalancedRandomForestClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_0, location_cluster_1, locat...</td>\n",
       "      <td>False</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>160.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.000808</td>\n",
       "      <td>-5.702743e-04</td>\n",
       "      <td>-3.327108e-04</td>\n",
       "      <td>-0.000760</td>\n",
       "      <td>-0.000475</td>\n",
       "      <td>-0.000475</td>\n",
       "      <td>0.000333</td>\n",
       "      <td>0.000715</td>\n",
       "      <td>-0.000285</td>\n",
       "      <td>0.000190</td>\n",
       "      <td>0.000238</td>\n",
       "      <td>-0.000238</td>\n",
       "      <td>3.330044e-04</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>-0.000238</td>\n",
       "      <td>-0.000190</td>\n",
       "      <td>6.775267e-08</td>\n",
       "      <td>9.512474e-05</td>\n",
       "      <td>-1.426193e-04</td>\n",
       "      <td>0.000143</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.000618</td>\n",
       "      <td>0.000238</td>\n",
       "      <td>-0.001140</td>\n",
       "      <td>-0.000453</td>\n",
       "      <td>2.854194e-04</td>\n",
       "      <td>0.000238</td>\n",
       "      <td>-0.000570</td>\n",
       "      <td>0.778200</td>\n",
       "      <td>0.163597</td>\n",
       "      <td>0.006791</td>\n",
       "      <td>0.012397</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.006237</td>\n",
       "      <td>1151</td>\n",
       "      <td>956</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0.378372</td>\n",
       "      <td>-0.004963</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2067</td>\n",
       "      <td>40</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.356</td>\n",
       "      <td>0.049092</td>\n",
       "      <td>0.054054</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.029412</td>\n",
       "      <td>2041</td>\n",
       "      <td>66</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>DecisionTreeClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_2, location_cluster_4, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>log2</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.849586</td>\n",
       "      <td>1.215131</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-6.216950e-02</td>\n",
       "      <td>-2.772803e-02</td>\n",
       "      <td>-0.006446</td>\n",
       "      <td>-0.004338</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001108</td>\n",
       "      <td>-0.000119</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.001657</td>\n",
       "      <td>0.802049</td>\n",
       "      <td>0.451734</td>\n",
       "      <td>0.014594</td>\n",
       "      <td>0.020134</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.010169</td>\n",
       "      <td>1523</td>\n",
       "      <td>584</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0.653772</td>\n",
       "      <td>-0.004388</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2087</td>\n",
       "      <td>20</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.616</td>\n",
       "      <td>0.020506</td>\n",
       "      <td>0.025641</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>2036</td>\n",
       "      <td>71</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>best</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.15</td>\n",
       "      <td>1665.0</td>\n",
       "      <td>entropy</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>KNeighborsClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_0, location_cluster_5, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.001226</td>\n",
       "      <td>3.458888e-03</td>\n",
       "      <td>6.918990e-04</td>\n",
       "      <td>0.001384</td>\n",
       "      <td>0.000346</td>\n",
       "      <td>0.001483</td>\n",
       "      <td>0.002065</td>\n",
       "      <td>0.001658</td>\n",
       "      <td>0.001732</td>\n",
       "      <td>0.000606</td>\n",
       "      <td>0.002151</td>\n",
       "      <td>0.000268</td>\n",
       "      <td>2.162801e-03</td>\n",
       "      <td>0.001017</td>\n",
       "      <td>0.001916</td>\n",
       "      <td>0.001669</td>\n",
       "      <td>7.907588e-04</td>\n",
       "      <td>3.633361e-03</td>\n",
       "      <td>1.384009e-03</td>\n",
       "      <td>-0.000814</td>\n",
       "      <td>0.004039</td>\n",
       "      <td>0.000099</td>\n",
       "      <td>0.001127</td>\n",
       "      <td>0.000014</td>\n",
       "      <td>0.003309</td>\n",
       "      <td>1.900141e-04</td>\n",
       "      <td>0.001755</td>\n",
       "      <td>0.003902</td>\n",
       "      <td>0.657570</td>\n",
       "      <td>0.500393</td>\n",
       "      <td>0.083490</td>\n",
       "      <td>0.088235</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.048387</td>\n",
       "      <td>2048</td>\n",
       "      <td>59</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0.651457</td>\n",
       "      <td>-0.004755</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2077</td>\n",
       "      <td>30</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.500</td>\n",
       "      <td>0.083490</td>\n",
       "      <td>0.088235</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.048387</td>\n",
       "      <td>2048</td>\n",
       "      <td>59</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>distance</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>manhattan</td>\n",
       "      <td>42.0</td>\n",
       "      <td>brute</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>SVM</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_4, location_cluster_5, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.849586</td>\n",
       "      <td>1.215131</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.733720e-05</td>\n",
       "      <td>1.902593e-07</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>0.000047</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000331</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.733720e-05</td>\n",
       "      <td>0.000142</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>-0.000723</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>-4.771631e-04</td>\n",
       "      <td>0.000190</td>\n",
       "      <td>-0.000419</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.000572</td>\n",
       "      <td>-0.000477</td>\n",
       "      <td>-4.189272e-04</td>\n",
       "      <td>0.000331</td>\n",
       "      <td>-0.000209</td>\n",
       "      <td>0.867347</td>\n",
       "      <td>0.023011</td>\n",
       "      <td>0.014390</td>\n",
       "      <td>0.019920</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.010081</td>\n",
       "      <td>1616</td>\n",
       "      <td>491</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>0.480565</td>\n",
       "      <td>0.285134</td>\n",
       "      <td>0.285714</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2107</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0.438</td>\n",
       "      <td>0.285134</td>\n",
       "      <td>0.285714</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2107</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.005</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>rbf</td>\n",
       "      <td>0.916</td>\n",
       "      <td>ovo</td>\n",
       "      <td>7.10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>RUSBoostClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_2, location_cluster_4, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>455.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000049</td>\n",
       "      <td>-3.166702e-03</td>\n",
       "      <td>-1.560610e-03</td>\n",
       "      <td>0.000195</td>\n",
       "      <td>0.000488</td>\n",
       "      <td>-0.000049</td>\n",
       "      <td>0.000644</td>\n",
       "      <td>-0.001024</td>\n",
       "      <td>-0.000341</td>\n",
       "      <td>-0.000244</td>\n",
       "      <td>-0.001707</td>\n",
       "      <td>-0.000488</td>\n",
       "      <td>-2.807417e-10</td>\n",
       "      <td>-0.001561</td>\n",
       "      <td>-0.000878</td>\n",
       "      <td>-0.000390</td>\n",
       "      <td>9.750000e-05</td>\n",
       "      <td>-9.263705e-04</td>\n",
       "      <td>-1.950058e-04</td>\n",
       "      <td>0.000390</td>\n",
       "      <td>-0.002439</td>\n",
       "      <td>0.004100</td>\n",
       "      <td>-0.001317</td>\n",
       "      <td>0.000146</td>\n",
       "      <td>-0.000439</td>\n",
       "      <td>7.313105e-04</td>\n",
       "      <td>-0.000293</td>\n",
       "      <td>0.001219</td>\n",
       "      <td>0.823999</td>\n",
       "      <td>0.481585</td>\n",
       "      <td>0.039535</td>\n",
       "      <td>0.044843</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.023041</td>\n",
       "      <td>1895</td>\n",
       "      <td>212</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>0.532455</td>\n",
       "      <td>-0.000812</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2106</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.516</td>\n",
       "      <td>0.248934</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>2106</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAMME.R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0950</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>AdaBoostClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_0, location_cluster_4, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>395.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.000559</td>\n",
       "      <td>-9.543740e-04</td>\n",
       "      <td>-2.693561e-04</td>\n",
       "      <td>0.000191</td>\n",
       "      <td>-0.000425</td>\n",
       "      <td>-0.000287</td>\n",
       "      <td>-0.000371</td>\n",
       "      <td>-0.000700</td>\n",
       "      <td>0.000970</td>\n",
       "      <td>-0.001194</td>\n",
       "      <td>-0.000905</td>\n",
       "      <td>-0.001240</td>\n",
       "      <td>-6.116644e-04</td>\n",
       "      <td>-0.000334</td>\n",
       "      <td>-0.000811</td>\n",
       "      <td>-0.000358</td>\n",
       "      <td>-5.225256e-05</td>\n",
       "      <td>2.868260e-04</td>\n",
       "      <td>1.912932e-04</td>\n",
       "      <td>0.000622</td>\n",
       "      <td>-0.000620</td>\n",
       "      <td>-0.000143</td>\n",
       "      <td>-0.000414</td>\n",
       "      <td>-0.000896</td>\n",
       "      <td>0.000967</td>\n",
       "      <td>1.161305e-03</td>\n",
       "      <td>-0.000859</td>\n",
       "      <td>-0.000040</td>\n",
       "      <td>0.754074</td>\n",
       "      <td>0.487706</td>\n",
       "      <td>0.038677</td>\n",
       "      <td>0.043956</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.022727</td>\n",
       "      <td>1935</td>\n",
       "      <td>172</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>0.498975</td>\n",
       "      <td>-0.004601</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2082</td>\n",
       "      <td>25</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.498</td>\n",
       "      <td>0.056221</td>\n",
       "      <td>0.060606</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>0.037037</td>\n",
       "      <td>2081</td>\n",
       "      <td>26</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAMME.R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.4250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>XGBClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_1, location_cluster_5, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>215.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.000348</td>\n",
       "      <td>1.030885e-04</td>\n",
       "      <td>-3.973387e-04</td>\n",
       "      <td>-0.000497</td>\n",
       "      <td>-0.000497</td>\n",
       "      <td>-0.000497</td>\n",
       "      <td>-0.000856</td>\n",
       "      <td>-0.000497</td>\n",
       "      <td>-0.000497</td>\n",
       "      <td>0.000365</td>\n",
       "      <td>-0.000547</td>\n",
       "      <td>-0.000450</td>\n",
       "      <td>-1.488424e-04</td>\n",
       "      <td>-0.000447</td>\n",
       "      <td>-0.000497</td>\n",
       "      <td>-0.000397</td>\n",
       "      <td>-2.599615e-04</td>\n",
       "      <td>7.035861e-04</td>\n",
       "      <td>9.898245e-05</td>\n",
       "      <td>-0.001152</td>\n",
       "      <td>-0.000248</td>\n",
       "      <td>-0.002090</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.000490</td>\n",
       "      <td>-0.001679</td>\n",
       "      <td>-2.219967e-03</td>\n",
       "      <td>-0.000102</td>\n",
       "      <td>0.000132</td>\n",
       "      <td>0.731767</td>\n",
       "      <td>0.173605</td>\n",
       "      <td>0.007288</td>\n",
       "      <td>0.012889</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.006486</td>\n",
       "      <td>1188</td>\n",
       "      <td>919</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0.555872</td>\n",
       "      <td>-0.004073</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2092</td>\n",
       "      <td>15</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.480</td>\n",
       "      <td>0.150133</td>\n",
       "      <td>0.153846</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>2089</td>\n",
       "      <td>18</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0090</td>\n",
       "      <td>0.65</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>1.430262</td>\n",
       "      <td>binary:logistic</td>\n",
       "      <td>0.4</td>\n",
       "      <td>aucpr</td>\n",
       "      <td>0.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>HistGradientBoostingClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_5, location_cluster_10, loca...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>106.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.000143</td>\n",
       "      <td>2.262181e-08</td>\n",
       "      <td>-4.758498e-05</td>\n",
       "      <td>0.000190</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>0.001191</td>\n",
       "      <td>0.000572</td>\n",
       "      <td>0.001144</td>\n",
       "      <td>0.001096</td>\n",
       "      <td>-0.000143</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.000190</td>\n",
       "      <td>1.477762e-03</td>\n",
       "      <td>-0.000048</td>\n",
       "      <td>-0.001378</td>\n",
       "      <td>-0.000571</td>\n",
       "      <td>-1.188337e-03</td>\n",
       "      <td>-9.034368e-04</td>\n",
       "      <td>-1.903399e-04</td>\n",
       "      <td>-0.000666</td>\n",
       "      <td>-0.002090</td>\n",
       "      <td>-0.000048</td>\n",
       "      <td>-0.002137</td>\n",
       "      <td>-0.000048</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>2.262181e-08</td>\n",
       "      <td>-0.001853</td>\n",
       "      <td>-0.000665</td>\n",
       "      <td>0.831356</td>\n",
       "      <td>0.040739</td>\n",
       "      <td>0.014113</td>\n",
       "      <td>0.019646</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.009940</td>\n",
       "      <td>1609</td>\n",
       "      <td>498</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>0.176783</td>\n",
       "      <td>-0.005420</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1995</td>\n",
       "      <td>112</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.149</td>\n",
       "      <td>0.031512</td>\n",
       "      <td>0.036810</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.019108</td>\n",
       "      <td>1953</td>\n",
       "      <td>154</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>85.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0370</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>roc_auc</td>\n",
       "      <td>250.0</td>\n",
       "      <td>binary_crossentropy</td>\n",
       "      <td>0.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>RandomForestClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_4, location_cluster_5, locat...</td>\n",
       "      <td>True</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>464.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.784936</td>\n",
       "      <td>1.377389</td>\n",
       "      <td>-0.005754</td>\n",
       "      <td>-2.042901e-03</td>\n",
       "      <td>-6.085973e-03</td>\n",
       "      <td>0.000702</td>\n",
       "      <td>-0.001391</td>\n",
       "      <td>-0.000492</td>\n",
       "      <td>-0.001609</td>\n",
       "      <td>-0.002403</td>\n",
       "      <td>0.000754</td>\n",
       "      <td>-0.000281</td>\n",
       "      <td>0.000421</td>\n",
       "      <td>-0.000109</td>\n",
       "      <td>-5.257345e-04</td>\n",
       "      <td>-0.002655</td>\n",
       "      <td>-0.000355</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.260215e-03</td>\n",
       "      <td>2.347689e-04</td>\n",
       "      <td>-6.564138e-03</td>\n",
       "      <td>-0.003748</td>\n",
       "      <td>0.002310</td>\n",
       "      <td>0.004537</td>\n",
       "      <td>0.000211</td>\n",
       "      <td>-0.003083</td>\n",
       "      <td>-0.000633</td>\n",
       "      <td>-7.232384e-03</td>\n",
       "      <td>0.002106</td>\n",
       "      <td>-0.001296</td>\n",
       "      <td>0.908271</td>\n",
       "      <td>0.261394</td>\n",
       "      <td>0.038132</td>\n",
       "      <td>0.043243</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.022099</td>\n",
       "      <td>1292</td>\n",
       "      <td>177</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0.511634</td>\n",
       "      <td>-0.004729</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1443</td>\n",
       "      <td>26</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0.503</td>\n",
       "      <td>0.060070</td>\n",
       "      <td>0.064516</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.037037</td>\n",
       "      <td>1443</td>\n",
       "      <td>26</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>BalancedRandomForestClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_5, location_cluster_11, tree...</td>\n",
       "      <td>True</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>304.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>32.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.002819</td>\n",
       "      <td>-5.623265e-03</td>\n",
       "      <td>-3.641251e-03</td>\n",
       "      <td>-0.000069</td>\n",
       "      <td>-0.000896</td>\n",
       "      <td>-0.000758</td>\n",
       "      <td>0.001728</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000138</td>\n",
       "      <td>0.001105</td>\n",
       "      <td>-0.001652</td>\n",
       "      <td>-0.000069</td>\n",
       "      <td>-1.927086e-03</td>\n",
       "      <td>-0.001857</td>\n",
       "      <td>-0.000207</td>\n",
       "      <td>-0.001102</td>\n",
       "      <td>-1.652319e-03</td>\n",
       "      <td>-1.720788e-03</td>\n",
       "      <td>1.379725e-04</td>\n",
       "      <td>-0.000138</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.000620</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.006177</td>\n",
       "      <td>-0.003162</td>\n",
       "      <td>-6.236506e-03</td>\n",
       "      <td>-0.001308</td>\n",
       "      <td>-0.000482</td>\n",
       "      <td>0.805140</td>\n",
       "      <td>0.123400</td>\n",
       "      <td>0.016942</td>\n",
       "      <td>0.022222</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.011236</td>\n",
       "      <td>1117</td>\n",
       "      <td>352</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0.309646</td>\n",
       "      <td>-0.005278</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1353</td>\n",
       "      <td>116</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0.123</td>\n",
       "      <td>0.016880</td>\n",
       "      <td>0.022161</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.011204</td>\n",
       "      <td>1116</td>\n",
       "      <td>353</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>DecisionTreeClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_12, evi2-1, evi2_diff, evi2_...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.784936</td>\n",
       "      <td>1.377389</td>\n",
       "      <td>-0.014297</td>\n",
       "      <td>7.123452e-05</td>\n",
       "      <td>8.544787e-04</td>\n",
       "      <td>-0.004219</td>\n",
       "      <td>-0.004394</td>\n",
       "      <td>-0.001066</td>\n",
       "      <td>-0.000711</td>\n",
       "      <td>-0.000142</td>\n",
       "      <td>-0.005523</td>\n",
       "      <td>-0.000142</td>\n",
       "      <td>-0.000284</td>\n",
       "      <td>-0.000284</td>\n",
       "      <td>2.135334e-04</td>\n",
       "      <td>0.000427</td>\n",
       "      <td>-0.000711</td>\n",
       "      <td>-0.000709</td>\n",
       "      <td>-4.975402e-04</td>\n",
       "      <td>4.235511e-08</td>\n",
       "      <td>1.495730e-03</td>\n",
       "      <td>0.000356</td>\n",
       "      <td>-0.012320</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000071</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.004731</td>\n",
       "      <td>-2.133213e-04</td>\n",
       "      <td>0.000142</td>\n",
       "      <td>-0.002484</td>\n",
       "      <td>0.876447</td>\n",
       "      <td>0.199914</td>\n",
       "      <td>0.016575</td>\n",
       "      <td>0.021858</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.011050</td>\n",
       "      <td>1111</td>\n",
       "      <td>358</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0.641039</td>\n",
       "      <td>-0.004463</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1451</td>\n",
       "      <td>18</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0.603</td>\n",
       "      <td>0.082842</td>\n",
       "      <td>0.086957</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.052632</td>\n",
       "      <td>1451</td>\n",
       "      <td>18</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>best</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.00</td>\n",
       "      <td>385.0</td>\n",
       "      <td>gini</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>KNeighborsClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_2, location_cluster_4, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.001862</td>\n",
       "      <td>-6.450834e-04</td>\n",
       "      <td>5.916218e-03</td>\n",
       "      <td>-0.000143</td>\n",
       "      <td>-0.000143</td>\n",
       "      <td>-0.002291</td>\n",
       "      <td>-0.001075</td>\n",
       "      <td>0.000718</td>\n",
       "      <td>-0.000643</td>\n",
       "      <td>-0.000501</td>\n",
       "      <td>0.003023</td>\n",
       "      <td>-0.001218</td>\n",
       "      <td>1.742573e-03</td>\n",
       "      <td>-0.001576</td>\n",
       "      <td>-0.000932</td>\n",
       "      <td>0.002013</td>\n",
       "      <td>2.734175e-03</td>\n",
       "      <td>7.186555e-04</td>\n",
       "      <td>4.447000e-03</td>\n",
       "      <td>-0.000430</td>\n",
       "      <td>0.002085</td>\n",
       "      <td>-0.000645</td>\n",
       "      <td>0.001797</td>\n",
       "      <td>0.000790</td>\n",
       "      <td>-0.000214</td>\n",
       "      <td>-1.576070e-03</td>\n",
       "      <td>0.000647</td>\n",
       "      <td>-0.000215</td>\n",
       "      <td>0.871341</td>\n",
       "      <td>0.125153</td>\n",
       "      <td>0.020306</td>\n",
       "      <td>0.025559</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.012945</td>\n",
       "      <td>1164</td>\n",
       "      <td>305</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0.701346</td>\n",
       "      <td>-0.005013</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1424</td>\n",
       "      <td>45</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0.698</td>\n",
       "      <td>0.035179</td>\n",
       "      <td>0.040000</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.021739</td>\n",
       "      <td>1424</td>\n",
       "      <td>45</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>distance</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>minkowski</td>\n",
       "      <td>16.0</td>\n",
       "      <td>brute</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>SVM</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_5, evi2-1, evi2_raster, evi2...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.784936</td>\n",
       "      <td>1.377389</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000544</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.087649e-03</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001292</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000272</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.530633</td>\n",
       "      <td>0.000807</td>\n",
       "      <td>0.002736</td>\n",
       "      <td>0.008130</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.004082</td>\n",
       "      <td>493</td>\n",
       "      <td>976</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0.118274</td>\n",
       "      <td>-0.004962</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1429</td>\n",
       "      <td>40</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0.109</td>\n",
       "      <td>0.037772</td>\n",
       "      <td>0.042553</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.023256</td>\n",
       "      <td>1427</td>\n",
       "      <td>42</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.009</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>rbf</td>\n",
       "      <td>0.556</td>\n",
       "      <td>ovo</td>\n",
       "      <td>1.85</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>RUSBoostClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_0, location_cluster_4, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>275.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.002454</td>\n",
       "      <td>2.130238e-04</td>\n",
       "      <td>-1.649290e-03</td>\n",
       "      <td>-0.002159</td>\n",
       "      <td>-0.002379</td>\n",
       "      <td>-0.000643</td>\n",
       "      <td>-0.000856</td>\n",
       "      <td>-0.000286</td>\n",
       "      <td>-0.000928</td>\n",
       "      <td>0.000236</td>\n",
       "      <td>0.000256</td>\n",
       "      <td>-0.000427</td>\n",
       "      <td>2.120386e-03</td>\n",
       "      <td>-0.000428</td>\n",
       "      <td>-0.002277</td>\n",
       "      <td>0.000310</td>\n",
       "      <td>-3.559806e-04</td>\n",
       "      <td>7.081975e-05</td>\n",
       "      <td>-1.881835e-07</td>\n",
       "      <td>0.001909</td>\n",
       "      <td>-0.003117</td>\n",
       "      <td>-0.000499</td>\n",
       "      <td>0.007692</td>\n",
       "      <td>0.000424</td>\n",
       "      <td>-0.000071</td>\n",
       "      <td>-6.424334e-04</td>\n",
       "      <td>0.003597</td>\n",
       "      <td>-0.000143</td>\n",
       "      <td>0.918822</td>\n",
       "      <td>0.242497</td>\n",
       "      <td>0.034073</td>\n",
       "      <td>0.039216</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>1273</td>\n",
       "      <td>196</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0.613736</td>\n",
       "      <td>-0.003269</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1463</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0.564</td>\n",
       "      <td>0.163638</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.125000</td>\n",
       "      <td>1462</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAMME.R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>0.0830</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>AdaBoostClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_0, location_cluster_4, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>350.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.002998</td>\n",
       "      <td>-2.590371e-03</td>\n",
       "      <td>-2.454455e-03</td>\n",
       "      <td>-0.002182</td>\n",
       "      <td>-0.002998</td>\n",
       "      <td>-0.002804</td>\n",
       "      <td>-0.001569</td>\n",
       "      <td>-0.001229</td>\n",
       "      <td>-0.001297</td>\n",
       "      <td>-0.001774</td>\n",
       "      <td>-0.001638</td>\n",
       "      <td>-0.001910</td>\n",
       "      <td>-9.560022e-04</td>\n",
       "      <td>-0.002930</td>\n",
       "      <td>-0.000342</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-3.066400e-03</td>\n",
       "      <td>1.367515e-04</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000274</td>\n",
       "      <td>-0.002795</td>\n",
       "      <td>0.000284</td>\n",
       "      <td>0.000430</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.821055e-03</td>\n",
       "      <td>0.005687</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.928693</td>\n",
       "      <td>0.455384</td>\n",
       "      <td>0.049399</td>\n",
       "      <td>0.054422</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.027972</td>\n",
       "      <td>1330</td>\n",
       "      <td>139</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0.496771</td>\n",
       "      <td>-0.004242</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1455</td>\n",
       "      <td>14</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0.496</td>\n",
       "      <td>0.101410</td>\n",
       "      <td>0.105263</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.066667</td>\n",
       "      <td>1455</td>\n",
       "      <td>14</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAMME</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.4000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>XGBClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_0, location_cluster_13, tree...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.003481</td>\n",
       "      <td>-3.344876e-03</td>\n",
       "      <td>2.076988e-04</td>\n",
       "      <td>0.000411</td>\n",
       "      <td>-0.001095</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.001300</td>\n",
       "      <td>0.000069</td>\n",
       "      <td>0.001784</td>\n",
       "      <td>0.000343</td>\n",
       "      <td>0.000206</td>\n",
       "      <td>0.000274</td>\n",
       "      <td>-3.422522e-04</td>\n",
       "      <td>-0.001505</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.003685</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>-8.211625e-04</td>\n",
       "      <td>3.427200e-04</td>\n",
       "      <td>0.001097</td>\n",
       "      <td>0.000480</td>\n",
       "      <td>0.010215</td>\n",
       "      <td>0.000891</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.001231</td>\n",
       "      <td>-2.738765e-04</td>\n",
       "      <td>0.004730</td>\n",
       "      <td>0.000411</td>\n",
       "      <td>0.950987</td>\n",
       "      <td>0.305783</td>\n",
       "      <td>0.075992</td>\n",
       "      <td>0.080808</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.042105</td>\n",
       "      <td>1378</td>\n",
       "      <td>91</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0.386694</td>\n",
       "      <td>-0.004775</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1441</td>\n",
       "      <td>28</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0.304</td>\n",
       "      <td>0.075992</td>\n",
       "      <td>0.080808</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.042105</td>\n",
       "      <td>1378</td>\n",
       "      <td>91</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.850</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0090</td>\n",
       "      <td>0.70</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>1.754777</td>\n",
       "      <td>binary:logistic</td>\n",
       "      <td>0.3</td>\n",
       "      <td>aucpr</td>\n",
       "      <td>0.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>HistGradientBoostingClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>[location_cluster_4, location_cluster_10, loca...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000542</td>\n",
       "      <td>-2.118401e-03</td>\n",
       "      <td>-1.341581e-03</td>\n",
       "      <td>-0.002526</td>\n",
       "      <td>-0.001241</td>\n",
       "      <td>-0.000663</td>\n",
       "      <td>-0.000073</td>\n",
       "      <td>-0.000146</td>\n",
       "      <td>-0.000731</td>\n",
       "      <td>-0.001106</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000412</td>\n",
       "      <td>-1.368522e-06</td>\n",
       "      <td>0.000473</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000336</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.294294e-03</td>\n",
       "      <td>-1.709682e-03</td>\n",
       "      <td>0.000553</td>\n",
       "      <td>0.000289</td>\n",
       "      <td>0.001710</td>\n",
       "      <td>0.000125</td>\n",
       "      <td>0.000217</td>\n",
       "      <td>-0.000365</td>\n",
       "      <td>-2.916075e-04</td>\n",
       "      <td>0.001366</td>\n",
       "      <td>-0.000292</td>\n",
       "      <td>0.952859</td>\n",
       "      <td>0.056707</td>\n",
       "      <td>0.069206</td>\n",
       "      <td>0.074074</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.038462</td>\n",
       "      <td>1369</td>\n",
       "      <td>100</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0.609908</td>\n",
       "      <td>-0.003894</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1459</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0.505</td>\n",
       "      <td>0.129868</td>\n",
       "      <td>0.133333</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.090909</td>\n",
       "      <td>1459</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>71.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0455</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f1</td>\n",
       "      <td>425.0</td>\n",
       "      <td>binary_crossentropy</td>\n",
       "      <td>0.20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      species                           model   target  \\\n",
       "0   Deciduous          RandomForestClassifier  is_dead   \n",
       "1   Deciduous  BalancedRandomForestClassifier  is_dead   \n",
       "2   Deciduous          DecisionTreeClassifier  is_dead   \n",
       "3   Deciduous            KNeighborsClassifier  is_dead   \n",
       "4   Deciduous                             SVM  is_dead   \n",
       "5   Deciduous              RUSBoostClassifier  is_dead   \n",
       "6   Deciduous              AdaBoostClassifier  is_dead   \n",
       "7   Deciduous                   XGBClassifier  is_dead   \n",
       "8   Deciduous  HistGradientBoostingClassifier  is_dead   \n",
       "9     Conifer          RandomForestClassifier  is_dead   \n",
       "10    Conifer  BalancedRandomForestClassifier  is_dead   \n",
       "11    Conifer          DecisionTreeClassifier  is_dead   \n",
       "12    Conifer            KNeighborsClassifier  is_dead   \n",
       "13    Conifer                             SVM  is_dead   \n",
       "14    Conifer              RUSBoostClassifier  is_dead   \n",
       "15    Conifer              AdaBoostClassifier  is_dead   \n",
       "16    Conifer                   XGBClassifier  is_dead   \n",
       "17    Conifer  HistGradientBoostingClassifier  is_dead   \n",
       "18      Mixed          RandomForestClassifier  is_dead   \n",
       "19      Mixed  BalancedRandomForestClassifier  is_dead   \n",
       "20      Mixed          DecisionTreeClassifier  is_dead   \n",
       "21      Mixed            KNeighborsClassifier  is_dead   \n",
       "22      Mixed                             SVM  is_dead   \n",
       "23      Mixed              RUSBoostClassifier  is_dead   \n",
       "24      Mixed              AdaBoostClassifier  is_dead   \n",
       "25      Mixed                   XGBClassifier  is_dead   \n",
       "26      Mixed  HistGradientBoostingClassifier  is_dead   \n",
       "\n",
       "                                    relevant_features params.warm_start  \\\n",
       "0   [location_cluster_2, location_cluster_3, locat...             False   \n",
       "1   [location_cluster_0, location_cluster_2, locat...              True   \n",
       "2   [location_cluster_2, location_cluster_3, locat...               NaN   \n",
       "3   [location_cluster_4, location_cluster_6, locat...               NaN   \n",
       "4   [location_cluster_5, evi2_raster, evi2_vegetat...               NaN   \n",
       "5   [location_cluster_4, location_cluster_10, loca...               NaN   \n",
       "6   [location_cluster_1, location_cluster_4, locat...               NaN   \n",
       "7   [location_cluster_10, tree_1, evi2-1, evi2_ras...               NaN   \n",
       "8   [location_cluster_4, location_cluster_12, tree...               NaN   \n",
       "9   [location_cluster_3, location_cluster_5, locat...              True   \n",
       "10  [location_cluster_0, location_cluster_1, locat...             False   \n",
       "11  [location_cluster_2, location_cluster_4, locat...               NaN   \n",
       "12  [location_cluster_0, location_cluster_5, locat...               NaN   \n",
       "13  [location_cluster_4, location_cluster_5, locat...               NaN   \n",
       "14  [location_cluster_2, location_cluster_4, locat...               NaN   \n",
       "15  [location_cluster_0, location_cluster_4, locat...               NaN   \n",
       "16  [location_cluster_1, location_cluster_5, locat...               NaN   \n",
       "17  [location_cluster_5, location_cluster_10, loca...               NaN   \n",
       "18  [location_cluster_4, location_cluster_5, locat...              True   \n",
       "19  [location_cluster_5, location_cluster_11, tree...              True   \n",
       "20  [location_cluster_12, evi2-1, evi2_diff, evi2_...               NaN   \n",
       "21  [location_cluster_2, location_cluster_4, locat...               NaN   \n",
       "22  [location_cluster_5, evi2-1, evi2_raster, evi2...               NaN   \n",
       "23  [location_cluster_0, location_cluster_4, locat...               NaN   \n",
       "24  [location_cluster_0, location_cluster_4, locat...               NaN   \n",
       "25  [location_cluster_0, location_cluster_13, tree...               NaN   \n",
       "26  [location_cluster_4, location_cluster_10, loca...               NaN   \n",
       "\n",
       "    params.random_state  params.n_jobs  params.n_estimators  \\\n",
       "0                2022.0           58.0                336.0   \n",
       "1                2022.0           58.0                320.0   \n",
       "2                2022.0            NaN                  NaN   \n",
       "3                   NaN           58.0                  NaN   \n",
       "4                2022.0            NaN                  NaN   \n",
       "5                2022.0            NaN                410.0   \n",
       "6                2022.0            NaN                320.0   \n",
       "7                   NaN           58.0                485.0   \n",
       "8                2022.0            NaN                  NaN   \n",
       "9                2022.0           58.0                192.0   \n",
       "10               2022.0           58.0                160.0   \n",
       "11               2022.0            NaN                  NaN   \n",
       "12                  NaN           58.0                  NaN   \n",
       "13               2022.0            NaN                  NaN   \n",
       "14               2022.0            NaN                455.0   \n",
       "15               2022.0            NaN                395.0   \n",
       "16                  NaN           58.0                215.0   \n",
       "17               2022.0            NaN                  NaN   \n",
       "18               2022.0           58.0                464.0   \n",
       "19               2022.0           58.0                304.0   \n",
       "20               2022.0            NaN                  NaN   \n",
       "21                  NaN           58.0                  NaN   \n",
       "22               2022.0            NaN                  NaN   \n",
       "23               2022.0            NaN                275.0   \n",
       "24               2022.0            NaN                350.0   \n",
       "25                  NaN           58.0                380.0   \n",
       "26               2022.0            NaN                  NaN   \n",
       "\n",
       "    params.min_samples_split  params.min_samples_leaf params.max_features  \\\n",
       "0                        6.0                      2.0                sqrt   \n",
       "1                        4.0                      2.0                sqrt   \n",
       "2                       12.0                     11.0                log2   \n",
       "3                        NaN                      NaN                 NaN   \n",
       "4                        NaN                      NaN                 NaN   \n",
       "5                        NaN                      NaN                 NaN   \n",
       "6                        NaN                      NaN                 NaN   \n",
       "7                        NaN                      NaN                 NaN   \n",
       "8                        NaN                      6.0                 NaN   \n",
       "9                        6.0                      2.0                sqrt   \n",
       "10                       4.0                      2.0                sqrt   \n",
       "11                      10.0                      2.0                log2   \n",
       "12                       NaN                      NaN                 NaN   \n",
       "13                       NaN                      NaN                 NaN   \n",
       "14                       NaN                      NaN                 NaN   \n",
       "15                       NaN                      NaN                 NaN   \n",
       "16                       NaN                      NaN                 NaN   \n",
       "17                       NaN                     25.0                 NaN   \n",
       "18                      10.0                      4.0                sqrt   \n",
       "19                       8.0                      2.0                sqrt   \n",
       "20                      18.0                      8.0                sqrt   \n",
       "21                       NaN                      NaN                 NaN   \n",
       "22                       NaN                      NaN                 NaN   \n",
       "23                       NaN                      NaN                 NaN   \n",
       "24                       NaN                      NaN                 NaN   \n",
       "25                       NaN                      NaN                 NaN   \n",
       "26                       NaN                     31.0                 NaN   \n",
       "\n",
       "    params.max_depth  params.class_weight.0  params.class_weight.1  \\\n",
       "0               80.0               0.796774               1.342391   \n",
       "1               96.0                    NaN                    NaN   \n",
       "2               29.0               0.796774               1.342391   \n",
       "3                NaN                    NaN                    NaN   \n",
       "4                NaN               0.796774               1.342391   \n",
       "5                NaN                    NaN                    NaN   \n",
       "6                NaN                    NaN                    NaN   \n",
       "7                7.0                    NaN                    NaN   \n",
       "8              106.0                    NaN                    NaN   \n",
       "9              176.0               0.849586               1.215131   \n",
       "10             160.0                    NaN                    NaN   \n",
       "11              21.0               0.849586               1.215131   \n",
       "12               NaN                    NaN                    NaN   \n",
       "13               NaN               0.849586               1.215131   \n",
       "14               NaN                    NaN                    NaN   \n",
       "15               NaN                    NaN                    NaN   \n",
       "16               7.0                    NaN                    NaN   \n",
       "17             106.0                    NaN                    NaN   \n",
       "18              32.0               0.784936               1.377389   \n",
       "19              32.0                    NaN                    NaN   \n",
       "20              20.0               0.784936               1.377389   \n",
       "21               NaN                    NaN                    NaN   \n",
       "22               NaN               0.784936               1.377389   \n",
       "23               NaN                    NaN                    NaN   \n",
       "24               NaN                    NaN                    NaN   \n",
       "25               6.0                    NaN                    NaN   \n",
       "26              50.0                    NaN                    NaN   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_0  \\\n",
       "0                                          -0.006210   \n",
       "1                                          -0.010607   \n",
       "2                                          -0.051592   \n",
       "3                                          -0.018647   \n",
       "4                                          -0.013728   \n",
       "5                                          -0.006816   \n",
       "6                                          -0.000619   \n",
       "7                                           0.003435   \n",
       "8                                          -0.007239   \n",
       "9                                          -0.000237   \n",
       "10                                         -0.000808   \n",
       "11                                          0.000000   \n",
       "12                                          0.001226   \n",
       "13                                          0.000000   \n",
       "14                                          0.000049   \n",
       "15                                         -0.000559   \n",
       "16                                         -0.000348   \n",
       "17                                         -0.000143   \n",
       "18                                         -0.005754   \n",
       "19                                         -0.002819   \n",
       "20                                         -0.014297   \n",
       "21                                         -0.001862   \n",
       "22                                          0.000000   \n",
       "23                                         -0.002454   \n",
       "24                                         -0.002998   \n",
       "25                                         -0.003481   \n",
       "26                                          0.000542   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_1  \\\n",
       "0                                      -6.968349e-03   \n",
       "1                                      -6.728600e-03   \n",
       "2                                       2.112726e-02   \n",
       "3                                      -6.797864e-03   \n",
       "4                                      -1.524097e-02   \n",
       "5                                      -4.439295e-03   \n",
       "6                                       3.755198e-03   \n",
       "7                                       7.175136e-03   \n",
       "8                                      -6.711041e-04   \n",
       "9                                      -4.267087e-04   \n",
       "10                                     -5.702743e-04   \n",
       "11                                     -6.216950e-02   \n",
       "12                                      3.458888e-03   \n",
       "13                                      4.733720e-05   \n",
       "14                                     -3.166702e-03   \n",
       "15                                     -9.543740e-04   \n",
       "16                                      1.030885e-04   \n",
       "17                                      2.262181e-08   \n",
       "18                                     -2.042901e-03   \n",
       "19                                     -5.623265e-03   \n",
       "20                                      7.123452e-05   \n",
       "21                                     -6.450834e-04   \n",
       "22                                      0.000000e+00   \n",
       "23                                      2.130238e-04   \n",
       "24                                     -2.590371e-03   \n",
       "25                                     -3.344876e-03   \n",
       "26                                     -2.118401e-03   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_2  \\\n",
       "0                                      -6.019512e-03   \n",
       "1                                      -7.726560e-03   \n",
       "2                                       0.000000e+00   \n",
       "3                                       3.337381e-04   \n",
       "4                                      -1.192576e-02   \n",
       "5                                      -8.309086e-03   \n",
       "6                                       8.094120e-03   \n",
       "7                                      -6.469896e-04   \n",
       "8                                      -8.842459e-03   \n",
       "9                                      -2.845175e-04   \n",
       "10                                     -3.327108e-04   \n",
       "11                                     -2.772803e-02   \n",
       "12                                      6.918990e-04   \n",
       "13                                      1.902593e-07   \n",
       "14                                     -1.560610e-03   \n",
       "15                                     -2.693561e-04   \n",
       "16                                     -3.973387e-04   \n",
       "17                                     -4.758498e-05   \n",
       "18                                     -6.085973e-03   \n",
       "19                                     -3.641251e-03   \n",
       "20                                      8.544787e-04   \n",
       "21                                      5.916218e-03   \n",
       "22                                      0.000000e+00   \n",
       "23                                     -1.649290e-03   \n",
       "24                                     -2.454455e-03   \n",
       "25                                      2.076988e-04   \n",
       "26                                     -1.341581e-03   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_3  \\\n",
       "0                                          -0.002970   \n",
       "1                                          -0.002119   \n",
       "2                                           0.000000   \n",
       "3                                           0.007109   \n",
       "4                                          -0.014295   \n",
       "5                                          -0.015903   \n",
       "6                                           0.001450   \n",
       "7                                           0.000093   \n",
       "8                                          -0.000096   \n",
       "9                                          -0.000190   \n",
       "10                                         -0.000760   \n",
       "11                                         -0.006446   \n",
       "12                                          0.001384   \n",
       "13                                          0.000000   \n",
       "14                                          0.000195   \n",
       "15                                          0.000191   \n",
       "16                                         -0.000497   \n",
       "17                                          0.000190   \n",
       "18                                          0.000702   \n",
       "19                                         -0.000069   \n",
       "20                                         -0.004219   \n",
       "21                                         -0.000143   \n",
       "22                                          0.000000   \n",
       "23                                         -0.002159   \n",
       "24                                         -0.002182   \n",
       "25                                          0.000411   \n",
       "26                                         -0.002526   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_4  \\\n",
       "0                                          -0.004402   \n",
       "1                                          -0.008920   \n",
       "2                                          -0.028227   \n",
       "3                                           0.003320   \n",
       "4                                          -0.014862   \n",
       "5                                          -0.010446   \n",
       "6                                           0.000081   \n",
       "7                                           0.006893   \n",
       "8                                          -0.000096   \n",
       "9                                          -0.000285   \n",
       "10                                         -0.000475   \n",
       "11                                         -0.004338   \n",
       "12                                          0.000346   \n",
       "13                                          0.000095   \n",
       "14                                          0.000488   \n",
       "15                                         -0.000425   \n",
       "16                                         -0.000497   \n",
       "17                                          0.000095   \n",
       "18                                         -0.001391   \n",
       "19                                         -0.000896   \n",
       "20                                         -0.004394   \n",
       "21                                         -0.000143   \n",
       "22                                          0.000000   \n",
       "23                                         -0.002379   \n",
       "24                                         -0.002998   \n",
       "25                                         -0.001095   \n",
       "26                                         -0.001241   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_5  \\\n",
       "0                                          -0.006589   \n",
       "1                                          -0.008323   \n",
       "2                                          -0.025632   \n",
       "3                                          -0.002749   \n",
       "4                                          -0.010117   \n",
       "5                                          -0.001403   \n",
       "6                                           0.009271   \n",
       "7                                           0.000185   \n",
       "8                                          -0.002869   \n",
       "9                                          -0.000237   \n",
       "10                                         -0.000475   \n",
       "11                                          0.000000   \n",
       "12                                          0.001483   \n",
       "13                                          0.000095   \n",
       "14                                         -0.000049   \n",
       "15                                         -0.000287   \n",
       "16                                         -0.000497   \n",
       "17                                          0.001191   \n",
       "18                                         -0.000492   \n",
       "19                                         -0.000758   \n",
       "20                                         -0.001066   \n",
       "21                                         -0.002291   \n",
       "22                                          0.000000   \n",
       "23                                         -0.000643   \n",
       "24                                         -0.002804   \n",
       "25                                          0.000000   \n",
       "26                                         -0.000663   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_6  \\\n",
       "0                                          -0.006874   \n",
       "1                                          -0.008724   \n",
       "2                                          -0.070775   \n",
       "3                                           0.001879   \n",
       "4                                          -0.012114   \n",
       "5                                          -0.004656   \n",
       "6                                          -0.001987   \n",
       "7                                          -0.000277   \n",
       "8                                          -0.006103   \n",
       "9                                          -0.001042   \n",
       "10                                          0.000333   \n",
       "11                                          0.000000   \n",
       "12                                          0.002065   \n",
       "13                                          0.000047   \n",
       "14                                          0.000644   \n",
       "15                                         -0.000371   \n",
       "16                                         -0.000856   \n",
       "17                                          0.000572   \n",
       "18                                         -0.001609   \n",
       "19                                          0.001728   \n",
       "20                                         -0.000711   \n",
       "21                                         -0.001075   \n",
       "22                                          0.000000   \n",
       "23                                         -0.000856   \n",
       "24                                         -0.001569   \n",
       "25                                         -0.001300   \n",
       "26                                         -0.000073   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_7  \\\n",
       "0                                          -0.005352   \n",
       "1                                          -0.000909   \n",
       "2                                           0.000000   \n",
       "3                                           0.001996   \n",
       "4                                          -0.011070   \n",
       "5                                          -0.003570   \n",
       "6                                           0.003792   \n",
       "7                                          -0.000647   \n",
       "8                                           0.000864   \n",
       "9                                          -0.000047   \n",
       "10                                          0.000715   \n",
       "11                                          0.000000   \n",
       "12                                          0.001658   \n",
       "13                                          0.000000   \n",
       "14                                         -0.001024   \n",
       "15                                         -0.000700   \n",
       "16                                         -0.000497   \n",
       "17                                          0.001144   \n",
       "18                                         -0.002403   \n",
       "19                                          0.000000   \n",
       "20                                         -0.000142   \n",
       "21                                          0.000718   \n",
       "22                                          0.000000   \n",
       "23                                         -0.000286   \n",
       "24                                         -0.001229   \n",
       "25                                          0.000069   \n",
       "26                                         -0.000146   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_8  \\\n",
       "0                                          -0.001727   \n",
       "1                                          -0.002320   \n",
       "2                                           0.000000   \n",
       "3                                           0.000999   \n",
       "4                                          -0.013444   \n",
       "5                                           0.001437   \n",
       "6                                          -0.001122   \n",
       "7                                           0.000000   \n",
       "8                                           0.000672   \n",
       "9                                          -0.000095   \n",
       "10                                         -0.000285   \n",
       "11                                          0.000000   \n",
       "12                                          0.001732   \n",
       "13                                          0.000000   \n",
       "14                                         -0.000341   \n",
       "15                                          0.000970   \n",
       "16                                         -0.000497   \n",
       "17                                          0.001096   \n",
       "18                                          0.000754   \n",
       "19                                          0.000138   \n",
       "20                                         -0.005523   \n",
       "21                                         -0.000643   \n",
       "22                                          0.000544   \n",
       "23                                         -0.000928   \n",
       "24                                         -0.001297   \n",
       "25                                          0.001784   \n",
       "26                                         -0.000731   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_9  \\\n",
       "0                                           0.001253   \n",
       "1                                          -0.004831   \n",
       "2                                          -0.020836   \n",
       "3                                          -0.006030   \n",
       "4                                          -0.012966   \n",
       "5                                          -0.000385   \n",
       "6                                           0.004712   \n",
       "7                                           0.000556   \n",
       "8                                          -0.000384   \n",
       "9                                          -0.000142   \n",
       "10                                          0.000190   \n",
       "11                                          0.000000   \n",
       "12                                          0.000606   \n",
       "13                                          0.000000   \n",
       "14                                         -0.000244   \n",
       "15                                         -0.001194   \n",
       "16                                          0.000365   \n",
       "17                                         -0.000143   \n",
       "18                                         -0.000281   \n",
       "19                                          0.001105   \n",
       "20                                         -0.000142   \n",
       "21                                         -0.000501   \n",
       "22                                          0.000000   \n",
       "23                                          0.000236   \n",
       "24                                         -0.001774   \n",
       "25                                          0.000343   \n",
       "26                                         -0.001106   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_10  \\\n",
       "0                                           -0.004401   \n",
       "1                                           -0.001413   \n",
       "2                                           -0.003673   \n",
       "3                                            0.007447   \n",
       "4                                           -0.010021   \n",
       "5                                            0.000736   \n",
       "6                                            0.000406   \n",
       "7                                            0.000278   \n",
       "8                                            0.000769   \n",
       "9                                            0.000427   \n",
       "10                                           0.000238   \n",
       "11                                           0.000000   \n",
       "12                                           0.002151   \n",
       "13                                           0.000331   \n",
       "14                                          -0.001707   \n",
       "15                                          -0.000905   \n",
       "16                                          -0.000547   \n",
       "17                                           0.000000   \n",
       "18                                           0.000421   \n",
       "19                                          -0.001652   \n",
       "20                                          -0.000284   \n",
       "21                                           0.003023   \n",
       "22                                           0.000000   \n",
       "23                                           0.000256   \n",
       "24                                          -0.001638   \n",
       "25                                           0.000206   \n",
       "26                                           0.000000   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_11  \\\n",
       "0                                           -0.000576   \n",
       "1                                           -0.002924   \n",
       "2                                            0.000000   \n",
       "3                                           -0.004281   \n",
       "4                                           -0.013440   \n",
       "5                                            0.002741   \n",
       "6                                            0.001154   \n",
       "7                                            0.005675   \n",
       "8                                           -0.000287   \n",
       "9                                           -0.000047   \n",
       "10                                          -0.000238   \n",
       "11                                           0.000000   \n",
       "12                                           0.000268   \n",
       "13                                           0.000000   \n",
       "14                                          -0.000488   \n",
       "15                                          -0.001240   \n",
       "16                                          -0.000450   \n",
       "17                                          -0.000190   \n",
       "18                                          -0.000109   \n",
       "19                                          -0.000069   \n",
       "20                                          -0.000284   \n",
       "21                                          -0.001218   \n",
       "22                                           0.000000   \n",
       "23                                          -0.000427   \n",
       "24                                          -0.001910   \n",
       "25                                           0.000274   \n",
       "26                                           0.000412   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_12  \\\n",
       "0                                       -2.682255e-03   \n",
       "1                                        1.624869e-03   \n",
       "2                                        1.441978e-02   \n",
       "3                                       -3.518166e-03   \n",
       "4                                       -7.725528e-03   \n",
       "5                                       -5.328653e-03   \n",
       "6                                       -3.949386e-04   \n",
       "7                                       -1.270475e-03   \n",
       "8                                        7.681793e-04   \n",
       "9                                       -9.483164e-05   \n",
       "10                                       3.330044e-04   \n",
       "11                                       0.000000e+00   \n",
       "12                                       2.162801e-03   \n",
       "13                                       4.733720e-05   \n",
       "14                                      -2.807417e-10   \n",
       "15                                      -6.116644e-04   \n",
       "16                                      -1.488424e-04   \n",
       "17                                       1.477762e-03   \n",
       "18                                      -5.257345e-04   \n",
       "19                                      -1.927086e-03   \n",
       "20                                       2.135334e-04   \n",
       "21                                       1.742573e-03   \n",
       "22                                       0.000000e+00   \n",
       "23                                       2.120386e-03   \n",
       "24                                      -9.560022e-04   \n",
       "25                                      -3.422522e-04   \n",
       "26                                      -1.368522e-06   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_13  \\\n",
       "0                                           -0.001056   \n",
       "1                                           -0.005529   \n",
       "2                                            0.000000   \n",
       "3                                            0.001993   \n",
       "4                                           -0.014485   \n",
       "5                                           -0.000702   \n",
       "6                                           -0.001227   \n",
       "7                                            0.000000   \n",
       "8                                           -0.001437   \n",
       "9                                            0.000190   \n",
       "10                                           0.000095   \n",
       "11                                           0.000000   \n",
       "12                                           0.001017   \n",
       "13                                           0.000142   \n",
       "14                                          -0.001561   \n",
       "15                                          -0.000334   \n",
       "16                                          -0.000447   \n",
       "17                                          -0.000048   \n",
       "18                                          -0.002655   \n",
       "19                                          -0.001857   \n",
       "20                                           0.000427   \n",
       "21                                          -0.001576   \n",
       "22                                           0.000000   \n",
       "23                                          -0.000428   \n",
       "24                                          -0.002930   \n",
       "25                                          -0.001505   \n",
       "26                                           0.000473   \n",
       "\n",
       "    feature_permutaion_importance.tree_1  feature_permutaion_importance.evi2  \\\n",
       "0                              -0.000859                           -0.003161   \n",
       "1                              -0.012190                           -0.016019   \n",
       "2                               0.009990                            0.000000   \n",
       "3                              -0.007015                            0.001879   \n",
       "4                              -0.005902                           -0.015147   \n",
       "5                              -0.004601                            0.007834   \n",
       "6                              -0.000281                           -0.000879   \n",
       "7                               0.002040                            0.000278   \n",
       "8                               0.000480                           -0.000287   \n",
       "9                              -0.000284                           -0.000142   \n",
       "10                             -0.000238                           -0.000190   \n",
       "11                              0.000000                            0.000000   \n",
       "12                              0.001916                            0.001669   \n",
       "13                              0.000095                           -0.000723   \n",
       "14                             -0.000878                           -0.000390   \n",
       "15                             -0.000811                           -0.000358   \n",
       "16                             -0.000497                           -0.000397   \n",
       "17                             -0.001378                           -0.000571   \n",
       "18                             -0.000355                            0.000000   \n",
       "19                             -0.000207                           -0.001102   \n",
       "20                             -0.000711                           -0.000709   \n",
       "21                             -0.000932                            0.002013   \n",
       "22                              0.000000                            0.000000   \n",
       "23                             -0.002277                            0.000310   \n",
       "24                             -0.000342                            0.000000   \n",
       "25                              0.000000                           -0.003685   \n",
       "26                              0.000000                            0.000336   \n",
       "\n",
       "    feature_permutaion_importance.evi2-1  \\\n",
       "0                          -1.914322e-04   \n",
       "1                          -4.730376e-03   \n",
       "2                           0.000000e+00   \n",
       "3                           1.555866e-02   \n",
       "4                          -1.145041e-02   \n",
       "5                          -1.548265e-02   \n",
       "6                          -3.363313e-05   \n",
       "7                          -5.546114e-04   \n",
       "8                           1.248847e-03   \n",
       "9                          -2.370679e-04   \n",
       "10                          6.775267e-08   \n",
       "11                          0.000000e+00   \n",
       "12                          7.907588e-04   \n",
       "13                          0.000000e+00   \n",
       "14                          9.750000e-05   \n",
       "15                         -5.225256e-05   \n",
       "16                         -2.599615e-04   \n",
       "17                         -1.188337e-03   \n",
       "18                          4.260215e-03   \n",
       "19                         -1.652319e-03   \n",
       "20                         -4.975402e-04   \n",
       "21                          2.734175e-03   \n",
       "22                          0.000000e+00   \n",
       "23                         -3.559806e-04   \n",
       "24                         -3.066400e-03   \n",
       "25                          0.000000e+00   \n",
       "26                          0.000000e+00   \n",
       "\n",
       "    feature_permutaion_importance.evi2_diff  \\\n",
       "0                             -1.065061e-02   \n",
       "1                             -3.124558e-03   \n",
       "2                              0.000000e+00   \n",
       "3                              2.213365e-03   \n",
       "4                             -8.585087e-03   \n",
       "5                             -5.719070e-03   \n",
       "6                              2.700098e-03   \n",
       "7                              1.056517e-02   \n",
       "8                             -1.917957e-04   \n",
       "9                             -2.370454e-04   \n",
       "10                             9.512474e-05   \n",
       "11                             0.000000e+00   \n",
       "12                             3.633361e-03   \n",
       "13                             0.000000e+00   \n",
       "14                            -9.263705e-04   \n",
       "15                             2.868260e-04   \n",
       "16                             7.035861e-04   \n",
       "17                            -9.034368e-04   \n",
       "18                             2.347689e-04   \n",
       "19                            -1.720788e-03   \n",
       "20                             4.235511e-08   \n",
       "21                             7.186555e-04   \n",
       "22                             0.000000e+00   \n",
       "23                             7.081975e-05   \n",
       "24                             1.367515e-04   \n",
       "25                            -8.211625e-04   \n",
       "26                             1.294294e-03   \n",
       "\n",
       "    feature_permutaion_importance.evi2_max_diff  \\\n",
       "0                                  5.776561e-04   \n",
       "1                                 -2.316937e-03   \n",
       "2                                  1.120815e-02   \n",
       "3                                  8.999620e-04   \n",
       "4                                 -1.287407e-02   \n",
       "5                                 -2.383058e-03   \n",
       "6                                 -4.076144e-05   \n",
       "7                                 -2.773913e-04   \n",
       "8                                 -2.010604e-03   \n",
       "9                                 -4.272020e-04   \n",
       "10                                -1.426193e-04   \n",
       "11                                 0.000000e+00   \n",
       "12                                 1.384009e-03   \n",
       "13                                -4.771631e-04   \n",
       "14                                -1.950058e-04   \n",
       "15                                 1.912932e-04   \n",
       "16                                 9.898245e-05   \n",
       "17                                -1.903399e-04   \n",
       "18                                -6.564138e-03   \n",
       "19                                 1.379725e-04   \n",
       "20                                 1.495730e-03   \n",
       "21                                 4.447000e-03   \n",
       "22                                 1.087649e-03   \n",
       "23                                -1.881835e-07   \n",
       "24                                 0.000000e+00   \n",
       "25                                 3.427200e-04   \n",
       "26                                -1.709682e-03   \n",
       "\n",
       "    feature_permutaion_importance.evi2_raster  \\\n",
       "0                                   -0.004211   \n",
       "1                                   -0.007027   \n",
       "2                                    0.004980   \n",
       "3                                   -0.006906   \n",
       "4                                   -0.012875   \n",
       "5                                   -0.001445   \n",
       "6                                    0.001060   \n",
       "7                                    0.005395   \n",
       "8                                   -0.002485   \n",
       "9                                   -0.000047   \n",
       "10                                   0.000143   \n",
       "11                                   0.000000   \n",
       "12                                  -0.000814   \n",
       "13                                   0.000190   \n",
       "14                                   0.000390   \n",
       "15                                   0.000622   \n",
       "16                                  -0.001152   \n",
       "17                                  -0.000666   \n",
       "18                                  -0.003748   \n",
       "19                                  -0.000138   \n",
       "20                                   0.000356   \n",
       "21                                  -0.000430   \n",
       "22                                   0.000000   \n",
       "23                                   0.001909   \n",
       "24                                   0.000274   \n",
       "25                                   0.001097   \n",
       "26                                   0.000553   \n",
       "\n",
       "    feature_permutaion_importance.evi2_raster-1  \\\n",
       "0                                     -0.001535   \n",
       "1                                     -0.004924   \n",
       "2                                      0.000000   \n",
       "3                                     -0.011350   \n",
       "4                                     -0.006664   \n",
       "5                                     -0.005561   \n",
       "6                                      0.001319   \n",
       "7                                      0.000278   \n",
       "8                                      0.000192   \n",
       "9                                     -0.000237   \n",
       "10                                     0.000000   \n",
       "11                                     0.000000   \n",
       "12                                     0.004039   \n",
       "13                                    -0.000419   \n",
       "14                                    -0.002439   \n",
       "15                                    -0.000620   \n",
       "16                                    -0.000248   \n",
       "17                                    -0.002090   \n",
       "18                                     0.002310   \n",
       "19                                     0.000000   \n",
       "20                                    -0.012320   \n",
       "21                                     0.002085   \n",
       "22                                     0.000000   \n",
       "23                                    -0.003117   \n",
       "24                                    -0.002795   \n",
       "25                                     0.000480   \n",
       "26                                     0.000289   \n",
       "\n",
       "    feature_permutaion_importance.evi2_raster_diff  \\\n",
       "0                                        -0.000672   \n",
       "1                                        -0.006629   \n",
       "2                                         0.001717   \n",
       "3                                         0.000885   \n",
       "4                                        -0.008875   \n",
       "5                                        -0.001882   \n",
       "6                                         0.001973   \n",
       "7                                        -0.000092   \n",
       "8                                         0.002308   \n",
       "9                                        -0.000237   \n",
       "10                                       -0.000618   \n",
       "11                                        0.001108   \n",
       "12                                        0.000099   \n",
       "13                                        0.000000   \n",
       "14                                        0.004100   \n",
       "15                                       -0.000143   \n",
       "16                                       -0.002090   \n",
       "17                                       -0.000048   \n",
       "18                                        0.004537   \n",
       "19                                       -0.000620   \n",
       "20                                        0.000000   \n",
       "21                                       -0.000645   \n",
       "22                                        0.001292   \n",
       "23                                       -0.000499   \n",
       "24                                        0.000284   \n",
       "25                                        0.010215   \n",
       "26                                        0.001710   \n",
       "\n",
       "    feature_permutaion_importance.evi2_vegetation_raster  \\\n",
       "0                                           -0.008009      \n",
       "1                                           -0.000599      \n",
       "2                                            0.000000      \n",
       "3                                           -0.002309      \n",
       "4                                           -0.014485      \n",
       "5                                           -0.008221      \n",
       "6                                           -0.000643      \n",
       "7                                            0.008491      \n",
       "8                                            0.000192      \n",
       "9                                           -0.000237      \n",
       "10                                           0.000238      \n",
       "11                                          -0.000119      \n",
       "12                                           0.001127      \n",
       "13                                           0.000000      \n",
       "14                                          -0.001317      \n",
       "15                                          -0.000414      \n",
       "16                                           0.000000      \n",
       "17                                          -0.002137      \n",
       "18                                           0.000211      \n",
       "19                                           0.000000      \n",
       "20                                           0.000071      \n",
       "21                                           0.001797      \n",
       "22                                           0.000000      \n",
       "23                                           0.007692      \n",
       "24                                           0.000430      \n",
       "25                                           0.000891      \n",
       "26                                           0.000125      \n",
       "\n",
       "    feature_permutaion_importance.evi2_vegetation_raster-1  \\\n",
       "0                                           -0.003925        \n",
       "1                                           -0.011499        \n",
       "2                                            0.000000        \n",
       "3                                           -0.007015        \n",
       "4                                           -0.018723        \n",
       "5                                           -0.004072        \n",
       "6                                           -0.003235        \n",
       "7                                            0.000185        \n",
       "8                                            0.000192        \n",
       "9                                           -0.000332        \n",
       "10                                          -0.001140        \n",
       "11                                           0.000000        \n",
       "12                                           0.000014        \n",
       "13                                          -0.000572        \n",
       "14                                           0.000146        \n",
       "15                                          -0.000896        \n",
       "16                                          -0.000490        \n",
       "17                                          -0.000048        \n",
       "18                                          -0.003083        \n",
       "19                                           0.006177        \n",
       "20                                           0.000000        \n",
       "21                                           0.000790        \n",
       "22                                           0.000000        \n",
       "23                                           0.000424        \n",
       "24                                           0.000000        \n",
       "25                                           0.000000        \n",
       "26                                           0.000217        \n",
       "\n",
       "    feature_permutaion_importance.evi2_vegetation_raster_diff  \\\n",
       "0                                           -0.002684           \n",
       "1                                           -0.018961           \n",
       "2                                            0.000000           \n",
       "3                                           -0.003078           \n",
       "4                                           -0.003104           \n",
       "5                                           -0.001787           \n",
       "6                                            0.002073           \n",
       "7                                            0.000093           \n",
       "8                                           -0.012321           \n",
       "9                                           -0.000521           \n",
       "10                                          -0.000453           \n",
       "11                                           0.000000           \n",
       "12                                           0.003309           \n",
       "13                                          -0.000477           \n",
       "14                                          -0.000439           \n",
       "15                                           0.000967           \n",
       "16                                          -0.001679           \n",
       "17                                           0.000095           \n",
       "18                                          -0.000633           \n",
       "19                                          -0.003162           \n",
       "20                                          -0.004731           \n",
       "21                                          -0.000214           \n",
       "22                                           0.000000           \n",
       "23                                          -0.000071           \n",
       "24                                           0.000000           \n",
       "25                                          -0.001231           \n",
       "26                                          -0.000365           \n",
       "\n",
       "    feature_permutaion_importance.ndvi  feature_permutaion_importance.ndvi-1  \\\n",
       "0                        -6.704692e-04                             -0.009049   \n",
       "1                        -3.325830e-03                             -0.005529   \n",
       "2                         0.000000e+00                             -0.014483   \n",
       "3                        -5.048628e-03                             -0.001981   \n",
       "4                        -6.381594e-03                             -0.014011   \n",
       "5                        -6.723447e-03                             -0.001868   \n",
       "6                         6.530846e-03                              0.000155   \n",
       "7                         1.387662e-02                              0.000648   \n",
       "8                         2.212094e-03                             -0.000767   \n",
       "9                         9.492169e-05                              0.000047   \n",
       "10                        2.854194e-04                              0.000238   \n",
       "11                        0.000000e+00                              0.000000   \n",
       "12                        1.900141e-04                              0.001755   \n",
       "13                       -4.189272e-04                              0.000331   \n",
       "14                        7.313105e-04                             -0.000293   \n",
       "15                        1.161305e-03                             -0.000859   \n",
       "16                       -2.219967e-03                             -0.000102   \n",
       "17                        2.262181e-08                             -0.001853   \n",
       "18                       -7.232384e-03                              0.002106   \n",
       "19                       -6.236506e-03                             -0.001308   \n",
       "20                       -2.133213e-04                              0.000142   \n",
       "21                       -1.576070e-03                              0.000647   \n",
       "22                        0.000000e+00                              0.000272   \n",
       "23                       -6.424334e-04                              0.003597   \n",
       "24                       -1.821055e-03                              0.005687   \n",
       "25                       -2.738765e-04                              0.004730   \n",
       "26                       -2.916075e-04                              0.001366   \n",
       "\n",
       "    feature_permutaion_importance.ndvi_diff  metrics.auc  \\\n",
       "0                                 -0.004305     0.572062   \n",
       "1                                 -0.013759     0.471165   \n",
       "2                                 -0.000269     0.431910   \n",
       "3                                  0.002546     0.502579   \n",
       "4                                 -0.012866     0.469308   \n",
       "5                                 -0.007150     0.718044   \n",
       "6                                  0.000066     0.718972   \n",
       "7                                 -0.000809     0.654699   \n",
       "8                                 -0.004108     0.642526   \n",
       "9                                  0.000000     0.872014   \n",
       "10                                -0.000570     0.778200   \n",
       "11                                -0.001657     0.802049   \n",
       "12                                 0.003902     0.657570   \n",
       "13                                -0.000209     0.867347   \n",
       "14                                 0.001219     0.823999   \n",
       "15                                -0.000040     0.754074   \n",
       "16                                 0.000132     0.731767   \n",
       "17                                -0.000665     0.831356   \n",
       "18                                -0.001296     0.908271   \n",
       "19                                -0.000482     0.805140   \n",
       "20                                -0.002484     0.876447   \n",
       "21                                -0.000215     0.871341   \n",
       "22                                 0.000000     0.530633   \n",
       "23                                -0.000143     0.918822   \n",
       "24                                 0.000000     0.928693   \n",
       "25                                 0.000411     0.950987   \n",
       "26                                -0.000292     0.952859   \n",
       "\n",
       "    metrics.roc.threshold  metrics.roc.cohen_kappa  metrics.roc.f1  \\\n",
       "0                0.230730                 0.012074        0.028103   \n",
       "1                0.301560                 0.002082        0.018349   \n",
       "2                0.520115                 0.007092        0.023121   \n",
       "3                0.166667                 0.011805        0.027842   \n",
       "4                0.035447                 0.007407        0.023609   \n",
       "5                0.492048                 0.073240        0.087591   \n",
       "6                0.483869                 0.061774        0.076433   \n",
       "7                0.285132                 0.044271        0.059406   \n",
       "8                0.138111                 0.033142        0.048583   \n",
       "9                0.129958                 0.010599        0.016173   \n",
       "10               0.163597                 0.006791        0.012397   \n",
       "11               0.451734                 0.014594        0.020134   \n",
       "12               0.500393                 0.083490        0.088235   \n",
       "13               0.023011                 0.014390        0.019920   \n",
       "14               0.481585                 0.039535        0.044843   \n",
       "15               0.487706                 0.038677        0.043956   \n",
       "16               0.173605                 0.007288        0.012889   \n",
       "17               0.040739                 0.014113        0.019646   \n",
       "18               0.261394                 0.038132        0.043243   \n",
       "19               0.123400                 0.016942        0.022222   \n",
       "20               0.199914                 0.016575        0.021858   \n",
       "21               0.125153                 0.020306        0.025559   \n",
       "22               0.000807                 0.002736        0.008130   \n",
       "23               0.242497                 0.034073        0.039216   \n",
       "24               0.455384                 0.049399        0.054422   \n",
       "25               0.305783                 0.075992        0.080808   \n",
       "26               0.056707                 0.069206        0.074074   \n",
       "\n",
       "    metrics.roc.recall  metrics.roc.precision  metrics.roc.tn  metrics.roc.fp  \\\n",
       "0             0.666667               0.014354             665             412   \n",
       "1             0.555556               0.009328             546             531   \n",
       "2             0.444444               0.011869             744             333   \n",
       "3             0.666667               0.014218             661             416   \n",
       "4             0.777778               0.011986             500             577   \n",
       "5             0.666667               0.046875             955             122   \n",
       "6             0.666667               0.040541             935             142   \n",
       "7             0.666667               0.031088             890             187   \n",
       "8             0.666667               0.025210             845             232   \n",
       "9             1.000000               0.008152            1377             730   \n",
       "10            1.000000               0.006237            1151             956   \n",
       "11            1.000000               0.010169            1523             584   \n",
       "12            0.500000               0.048387            2048              59   \n",
       "13            0.833333               0.010081            1616             491   \n",
       "14            0.833333               0.023041            1895             212   \n",
       "15            0.666667               0.022727            1935             172   \n",
       "16            1.000000               0.006486            1188             919   \n",
       "17            0.833333               0.009940            1609             498   \n",
       "18            1.000000               0.022099            1292             177   \n",
       "19            1.000000               0.011236            1117             352   \n",
       "20            1.000000               0.011050            1111             358   \n",
       "21            1.000000               0.012945            1164             305   \n",
       "22            1.000000               0.004082             493             976   \n",
       "23            1.000000               0.020000            1273             196   \n",
       "24            1.000000               0.027972            1330             139   \n",
       "25            1.000000               0.042105            1378              91   \n",
       "26            1.000000               0.038462            1369             100   \n",
       "\n",
       "    metrics.roc.fn  metrics.roc.tp  metrics.prc.threshold  \\\n",
       "0                3               6               0.443427   \n",
       "1                4               5               0.430567   \n",
       "2                5               4               0.551776   \n",
       "3                3               6               0.300000   \n",
       "4                2               7               0.134484   \n",
       "5                3               6               0.516331   \n",
       "6                3               6               0.505838   \n",
       "7                3               6               0.406628   \n",
       "8                3               6               0.293467   \n",
       "9                0               6               0.449513   \n",
       "10               0               6               0.378372   \n",
       "11               0               6               0.653772   \n",
       "12               3               3               0.651457   \n",
       "13               1               5               0.480565   \n",
       "14               1               5               0.532455   \n",
       "15               2               4               0.498975   \n",
       "16               0               6               0.555872   \n",
       "17               1               5               0.176783   \n",
       "18               0               4               0.511634   \n",
       "19               0               4               0.309646   \n",
       "20               0               4               0.641039   \n",
       "21               0               4               0.701346   \n",
       "22               0               4               0.118274   \n",
       "23               0               4               0.613736   \n",
       "24               0               4               0.496771   \n",
       "25               0               4               0.386694   \n",
       "26               0               4               0.609908   \n",
       "\n",
       "    metrics.prc.cohen_kappa  metrics.prc.f1  metrics.prc.recall  \\\n",
       "0                 -0.015198        0.000000            0.000000   \n",
       "1                 -0.016095        0.000000            0.000000   \n",
       "2                 -0.016220        0.000000            0.000000   \n",
       "3                 -0.016402        0.000000            0.000000   \n",
       "4                 -0.016324        0.000000            0.000000   \n",
       "5                 -0.008357        0.000000            0.000000   \n",
       "6                 -0.012201        0.000000            0.000000   \n",
       "7                 -0.014880        0.000000            0.000000   \n",
       "8                 -0.015314        0.000000            0.000000   \n",
       "9                 -0.003688        0.000000            0.000000   \n",
       "10                -0.004963        0.000000            0.000000   \n",
       "11                -0.004388        0.000000            0.000000   \n",
       "12                -0.004755        0.000000            0.000000   \n",
       "13                 0.285134        0.285714            0.166667   \n",
       "14                -0.000812        0.000000            0.000000   \n",
       "15                -0.004601        0.000000            0.000000   \n",
       "16                -0.004073        0.000000            0.000000   \n",
       "17                -0.005420        0.000000            0.000000   \n",
       "18                -0.004729        0.000000            0.000000   \n",
       "19                -0.005278        0.000000            0.000000   \n",
       "20                -0.004463        0.000000            0.000000   \n",
       "21                -0.005013        0.000000            0.000000   \n",
       "22                -0.004962        0.000000            0.000000   \n",
       "23                -0.003269        0.000000            0.000000   \n",
       "24                -0.004242        0.000000            0.000000   \n",
       "25                -0.004775        0.000000            0.000000   \n",
       "26                -0.003894        0.000000            0.000000   \n",
       "\n",
       "    metrics.prc.precision  metrics.prc.tn  metrics.prc.fp  metrics.prc.fn  \\\n",
       "0                     0.0             993              84               9   \n",
       "1                     0.0             883             194               9   \n",
       "2                     0.0             843             234               9   \n",
       "3                     0.0             745             332               9   \n",
       "4                     0.0             795             282               9   \n",
       "5                     0.0            1068               9               9   \n",
       "6                     0.0            1053              24               9   \n",
       "7                     0.0            1008              69               9   \n",
       "8                     0.0             986              91               9   \n",
       "9                     0.0            2096              11               6   \n",
       "10                    0.0            2067              40               6   \n",
       "11                    0.0            2087              20               6   \n",
       "12                    0.0            2077              30               6   \n",
       "13                    1.0            2107               0               5   \n",
       "14                    0.0            2106               1               6   \n",
       "15                    0.0            2082              25               6   \n",
       "16                    0.0            2092              15               6   \n",
       "17                    0.0            1995             112               6   \n",
       "18                    0.0            1443              26               4   \n",
       "19                    0.0            1353             116               4   \n",
       "20                    0.0            1451              18               4   \n",
       "21                    0.0            1424              45               4   \n",
       "22                    0.0            1429              40               4   \n",
       "23                    0.0            1463               6               4   \n",
       "24                    0.0            1455              14               4   \n",
       "25                    0.0            1441              28               4   \n",
       "26                    0.0            1459              10               4   \n",
       "\n",
       "    metrics.prc.tp  metrics.tuning.threshold  metrics.tuning.cohen_kappa  \\\n",
       "0                0                     0.389                    0.025656   \n",
       "1                0                     0.400                    0.005963   \n",
       "2                0                     0.517                    0.007092   \n",
       "3                0                     0.134                    0.011805   \n",
       "4                0                     0.035                    0.007285   \n",
       "5                0                     0.514                    0.097389   \n",
       "6                0                     0.499                    0.202073   \n",
       "7                0                     0.366                    0.053901   \n",
       "8                0                     0.137                    0.033142   \n",
       "9                0                     0.342                    0.203308   \n",
       "10               0                     0.356                    0.049092   \n",
       "11               0                     0.616                    0.020506   \n",
       "12               0                     0.500                    0.083490   \n",
       "13               1                     0.438                    0.285134   \n",
       "14               0                     0.516                    0.248934   \n",
       "15               0                     0.498                    0.056221   \n",
       "16               0                     0.480                    0.150133   \n",
       "17               0                     0.149                    0.031512   \n",
       "18               0                     0.503                    0.060070   \n",
       "19               0                     0.123                    0.016880   \n",
       "20               0                     0.603                    0.082842   \n",
       "21               0                     0.698                    0.035179   \n",
       "22               0                     0.109                    0.037772   \n",
       "23               0                     0.564                    0.163638   \n",
       "24               0                     0.496                    0.101410   \n",
       "25               0                     0.304                    0.075992   \n",
       "26               0                     0.505                    0.129868   \n",
       "\n",
       "    metrics.tuning.f1  metrics.tuning.recall  metrics.tuning.precision  \\\n",
       "0            0.040816               0.333333                  0.021739   \n",
       "1            0.021898               0.333333                  0.011321   \n",
       "2            0.023121               0.444444                  0.011869   \n",
       "3            0.027842               0.666667                  0.014218   \n",
       "4            0.023490               0.777778                  0.011925   \n",
       "5            0.105263               0.111111                  0.100000   \n",
       "6            0.212766               0.555556                  0.131579   \n",
       "7            0.068376               0.444444                  0.037037   \n",
       "8            0.048583               0.666667                  0.025210   \n",
       "9            0.206897               0.500000                  0.130435   \n",
       "10           0.054054               0.333333                  0.029412   \n",
       "11           0.025641               0.166667                  0.013889   \n",
       "12           0.088235               0.500000                  0.048387   \n",
       "13           0.285714               0.166667                  1.000000   \n",
       "14           0.250000               0.166667                  0.500000   \n",
       "15           0.060606               0.166667                  0.037037   \n",
       "16           0.153846               0.333333                  0.100000   \n",
       "17           0.036810               0.500000                  0.019108   \n",
       "18           0.064516               0.250000                  0.037037   \n",
       "19           0.022161               1.000000                  0.011204   \n",
       "20           0.086957               0.250000                  0.052632   \n",
       "21           0.040000               0.250000                  0.021739   \n",
       "22           0.042553               0.250000                  0.023256   \n",
       "23           0.166667               0.250000                  0.125000   \n",
       "24           0.105263               0.250000                  0.066667   \n",
       "25           0.080808               1.000000                  0.042105   \n",
       "26           0.133333               0.250000                  0.090909   \n",
       "\n",
       "    metrics.tuning.tn  metrics.tuning.fp  metrics.tuning.fn  \\\n",
       "0                 942                135                  6   \n",
       "1                 815                262                  6   \n",
       "2                 744                333                  5   \n",
       "3                 661                416                  3   \n",
       "4                 497                580                  2   \n",
       "5                1068                  9                  8   \n",
       "6                1044                 33                  4   \n",
       "7                 973                104                  5   \n",
       "8                 845                232                  3   \n",
       "9                2087                 20                  3   \n",
       "10               2041                 66                  4   \n",
       "11               2036                 71                  5   \n",
       "12               2048                 59                  3   \n",
       "13               2107                  0                  5   \n",
       "14               2106                  1                  5   \n",
       "15               2081                 26                  5   \n",
       "16               2089                 18                  4   \n",
       "17               1953                154                  3   \n",
       "18               1443                 26                  3   \n",
       "19               1116                353                  0   \n",
       "20               1451                 18                  3   \n",
       "21               1424                 45                  3   \n",
       "22               1427                 42                  3   \n",
       "23               1462                  7                  3   \n",
       "24               1455                 14                  3   \n",
       "25               1378                 91                  0   \n",
       "26               1459                 10                  3   \n",
       "\n",
       "    metrics.tuning.tp params.splitter  params.min_weight_fraction_leaf  \\\n",
       "0                   3             NaN                              NaN   \n",
       "1                   3             NaN                              NaN   \n",
       "2                   4            best                             0.30   \n",
       "3                   6             NaN                              NaN   \n",
       "4                   7             NaN                              NaN   \n",
       "5                   1             NaN                              NaN   \n",
       "6                   5             NaN                              NaN   \n",
       "7                   4             NaN                              NaN   \n",
       "8                   6             NaN                              NaN   \n",
       "9                   3             NaN                              NaN   \n",
       "10                  2             NaN                              NaN   \n",
       "11                  1            best                             0.20   \n",
       "12                  3             NaN                              NaN   \n",
       "13                  1             NaN                              NaN   \n",
       "14                  1             NaN                              NaN   \n",
       "15                  1             NaN                              NaN   \n",
       "16                  2             NaN                              NaN   \n",
       "17                  3             NaN                              NaN   \n",
       "18                  1             NaN                              NaN   \n",
       "19                  4             NaN                              NaN   \n",
       "20                  1            best                             0.05   \n",
       "21                  1             NaN                              NaN   \n",
       "22                  1             NaN                              NaN   \n",
       "23                  1             NaN                              NaN   \n",
       "24                  1             NaN                              NaN   \n",
       "25                  4             NaN                              NaN   \n",
       "26                  1             NaN                              NaN   \n",
       "\n",
       "    params.min_impurity_decrease  params.max_leaf_nodes params.criterion  \\\n",
       "0                            NaN                    NaN              NaN   \n",
       "1                            NaN                    NaN              NaN   \n",
       "2                           0.00                  801.0             gini   \n",
       "3                            NaN                    NaN              NaN   \n",
       "4                            NaN                    NaN              NaN   \n",
       "5                            NaN                    NaN              NaN   \n",
       "6                            NaN                    NaN              NaN   \n",
       "7                            NaN                    NaN              NaN   \n",
       "8                            NaN                   43.0              NaN   \n",
       "9                            NaN                    NaN              NaN   \n",
       "10                           NaN                    NaN              NaN   \n",
       "11                          0.15                 1665.0          entropy   \n",
       "12                           NaN                    NaN              NaN   \n",
       "13                           NaN                    NaN              NaN   \n",
       "14                           NaN                    NaN              NaN   \n",
       "15                           NaN                    NaN              NaN   \n",
       "16                           NaN                    NaN              NaN   \n",
       "17                           NaN                   85.0              NaN   \n",
       "18                           NaN                    NaN              NaN   \n",
       "19                           NaN                    NaN              NaN   \n",
       "20                          0.00                  385.0             gini   \n",
       "21                           NaN                    NaN              NaN   \n",
       "22                           NaN                    NaN              NaN   \n",
       "23                           NaN                    NaN              NaN   \n",
       "24                           NaN                    NaN              NaN   \n",
       "25                           NaN                    NaN              NaN   \n",
       "26                           NaN                   71.0              NaN   \n",
       "\n",
       "    params.ccp_alpha params.weights  params.p  params.n_neighbors  \\\n",
       "0                NaN            NaN       NaN                 NaN   \n",
       "1                NaN            NaN       NaN                 NaN   \n",
       "2                0.0            NaN       NaN                 NaN   \n",
       "3                NaN        uniform       2.0                 2.0   \n",
       "4                NaN            NaN       NaN                 NaN   \n",
       "5                NaN            NaN       NaN                 NaN   \n",
       "6                NaN            NaN       NaN                 NaN   \n",
       "7                NaN            NaN       NaN                 NaN   \n",
       "8                NaN            NaN       NaN                 NaN   \n",
       "9                NaN            NaN       NaN                 NaN   \n",
       "10               NaN            NaN       NaN                 NaN   \n",
       "11               0.0            NaN       NaN                 NaN   \n",
       "12               NaN       distance       1.0                 2.0   \n",
       "13               NaN            NaN       NaN                 NaN   \n",
       "14               NaN            NaN       NaN                 NaN   \n",
       "15               NaN            NaN       NaN                 NaN   \n",
       "16               NaN            NaN       NaN                 NaN   \n",
       "17               NaN            NaN       NaN                 NaN   \n",
       "18               NaN            NaN       NaN                 NaN   \n",
       "19               NaN            NaN       NaN                 NaN   \n",
       "20               0.0            NaN       NaN                 NaN   \n",
       "21               NaN       distance       1.0                 4.0   \n",
       "22               NaN            NaN       NaN                 NaN   \n",
       "23               NaN            NaN       NaN                 NaN   \n",
       "24               NaN            NaN       NaN                 NaN   \n",
       "25               NaN            NaN       NaN                 NaN   \n",
       "26               NaN            NaN       NaN                 NaN   \n",
       "\n",
       "   params.metric  params.leaf_size params.algorithm  params.tol  \\\n",
       "0            NaN               NaN              NaN         NaN   \n",
       "1            NaN               NaN              NaN         NaN   \n",
       "2            NaN               NaN              NaN         NaN   \n",
       "3      manhattan              42.0          kd_tree         NaN   \n",
       "4            NaN               NaN              NaN       0.007   \n",
       "5            NaN               NaN          SAMME.R         NaN   \n",
       "6            NaN               NaN          SAMME.R         NaN   \n",
       "7            NaN               NaN              NaN         NaN   \n",
       "8            NaN               NaN              NaN         NaN   \n",
       "9            NaN               NaN              NaN         NaN   \n",
       "10           NaN               NaN              NaN         NaN   \n",
       "11           NaN               NaN              NaN         NaN   \n",
       "12     manhattan              42.0            brute         NaN   \n",
       "13           NaN               NaN              NaN       0.005   \n",
       "14           NaN               NaN          SAMME.R         NaN   \n",
       "15           NaN               NaN          SAMME.R         NaN   \n",
       "16           NaN               NaN              NaN         NaN   \n",
       "17           NaN               NaN              NaN         NaN   \n",
       "18           NaN               NaN              NaN         NaN   \n",
       "19           NaN               NaN              NaN         NaN   \n",
       "20           NaN               NaN              NaN         NaN   \n",
       "21     minkowski              16.0            brute         NaN   \n",
       "22           NaN               NaN              NaN       0.009   \n",
       "23           NaN               NaN          SAMME.R         NaN   \n",
       "24           NaN               NaN            SAMME         NaN   \n",
       "25           NaN               NaN              NaN         NaN   \n",
       "26           NaN               NaN              NaN         NaN   \n",
       "\n",
       "   params.shrinking params.probability params.kernel  params.gamma  \\\n",
       "0               NaN                NaN           NaN           NaN   \n",
       "1               NaN                NaN           NaN           NaN   \n",
       "2               NaN                NaN           NaN           NaN   \n",
       "3               NaN                NaN           NaN           NaN   \n",
       "4              True               True           rbf         0.766   \n",
       "5               NaN                NaN           NaN           NaN   \n",
       "6               NaN                NaN           NaN           NaN   \n",
       "7               NaN                NaN           NaN         0.800   \n",
       "8               NaN                NaN           NaN           NaN   \n",
       "9               NaN                NaN           NaN           NaN   \n",
       "10              NaN                NaN           NaN           NaN   \n",
       "11              NaN                NaN           NaN           NaN   \n",
       "12              NaN                NaN           NaN           NaN   \n",
       "13            False               True           rbf         0.916   \n",
       "14              NaN                NaN           NaN           NaN   \n",
       "15              NaN                NaN           NaN           NaN   \n",
       "16              NaN                NaN           NaN         0.200   \n",
       "17              NaN                NaN           NaN           NaN   \n",
       "18              NaN                NaN           NaN           NaN   \n",
       "19              NaN                NaN           NaN           NaN   \n",
       "20              NaN                NaN           NaN           NaN   \n",
       "21              NaN                NaN           NaN           NaN   \n",
       "22            False               True           rbf         0.556   \n",
       "23              NaN                NaN           NaN           NaN   \n",
       "24              NaN                NaN           NaN           NaN   \n",
       "25              NaN                NaN           NaN         0.850   \n",
       "26              NaN                NaN           NaN           NaN   \n",
       "\n",
       "   params.decision_function_shape  params.C params.replacement  \\\n",
       "0                             NaN       NaN                NaN   \n",
       "1                             NaN       NaN                NaN   \n",
       "2                             NaN       NaN                NaN   \n",
       "3                             NaN       NaN                NaN   \n",
       "4                             ovo      5.85                NaN   \n",
       "5                             NaN       NaN               True   \n",
       "6                             NaN       NaN                NaN   \n",
       "7                             NaN       NaN                NaN   \n",
       "8                             NaN       NaN                NaN   \n",
       "9                             NaN       NaN                NaN   \n",
       "10                            NaN       NaN                NaN   \n",
       "11                            NaN       NaN                NaN   \n",
       "12                            NaN       NaN                NaN   \n",
       "13                            ovo      7.10                NaN   \n",
       "14                            NaN       NaN              False   \n",
       "15                            NaN       NaN                NaN   \n",
       "16                            NaN       NaN                NaN   \n",
       "17                            NaN       NaN                NaN   \n",
       "18                            NaN       NaN                NaN   \n",
       "19                            NaN       NaN                NaN   \n",
       "20                            NaN       NaN                NaN   \n",
       "21                            NaN       NaN                NaN   \n",
       "22                            ovo      1.85                NaN   \n",
       "23                            NaN       NaN               True   \n",
       "24                            NaN       NaN                NaN   \n",
       "25                            NaN       NaN                NaN   \n",
       "26                            NaN       NaN                NaN   \n",
       "\n",
       "    params.learning_rate  params.subsample  params.seed  \\\n",
       "0                    NaN               NaN          NaN   \n",
       "1                    NaN               NaN          NaN   \n",
       "2                    NaN               NaN          NaN   \n",
       "3                    NaN               NaN          NaN   \n",
       "4                    NaN               NaN          NaN   \n",
       "5                 0.0930               NaN          NaN   \n",
       "6                 0.4000               NaN          NaN   \n",
       "7                 0.0090              0.70       2022.0   \n",
       "8                 0.0230               NaN          NaN   \n",
       "9                    NaN               NaN          NaN   \n",
       "10                   NaN               NaN          NaN   \n",
       "11                   NaN               NaN          NaN   \n",
       "12                   NaN               NaN          NaN   \n",
       "13                   NaN               NaN          NaN   \n",
       "14                0.0950               NaN          NaN   \n",
       "15                0.4250               NaN          NaN   \n",
       "16                0.0090              0.65       2022.0   \n",
       "17                0.0370               NaN          NaN   \n",
       "18                   NaN               NaN          NaN   \n",
       "19                   NaN               NaN          NaN   \n",
       "20                   NaN               NaN          NaN   \n",
       "21                   NaN               NaN          NaN   \n",
       "22                   NaN               NaN          NaN   \n",
       "23                0.0830               NaN          NaN   \n",
       "24                0.4000               NaN          NaN   \n",
       "25                0.0090              0.70       2022.0   \n",
       "26                0.0455               NaN          NaN   \n",
       "\n",
       "    params.scale_pos_weight params.objective  params.lambda  \\\n",
       "0                       NaN              NaN            NaN   \n",
       "1                       NaN              NaN            NaN   \n",
       "2                       NaN              NaN            NaN   \n",
       "3                       NaN              NaN            NaN   \n",
       "4                       NaN              NaN            NaN   \n",
       "5                       NaN              NaN            NaN   \n",
       "6                       NaN              NaN            NaN   \n",
       "7                  1.684783  binary:logistic            0.0   \n",
       "8                       NaN              NaN            NaN   \n",
       "9                       NaN              NaN            NaN   \n",
       "10                      NaN              NaN            NaN   \n",
       "11                      NaN              NaN            NaN   \n",
       "12                      NaN              NaN            NaN   \n",
       "13                      NaN              NaN            NaN   \n",
       "14                      NaN              NaN            NaN   \n",
       "15                      NaN              NaN            NaN   \n",
       "16                 1.430262  binary:logistic            0.4   \n",
       "17                      NaN              NaN            NaN   \n",
       "18                      NaN              NaN            NaN   \n",
       "19                      NaN              NaN            NaN   \n",
       "20                      NaN              NaN            NaN   \n",
       "21                      NaN              NaN            NaN   \n",
       "22                      NaN              NaN            NaN   \n",
       "23                      NaN              NaN            NaN   \n",
       "24                      NaN              NaN            NaN   \n",
       "25                 1.754777  binary:logistic            0.3   \n",
       "26                      NaN              NaN            NaN   \n",
       "\n",
       "   params.eval_metric  params.colsample_bytree params.scoring  \\\n",
       "0                 NaN                      NaN            NaN   \n",
       "1                 NaN                      NaN            NaN   \n",
       "2                 NaN                      NaN            NaN   \n",
       "3                 NaN                      NaN            NaN   \n",
       "4                 NaN                      NaN            NaN   \n",
       "5                 NaN                      NaN            NaN   \n",
       "6                 NaN                      NaN            NaN   \n",
       "7                 auc                      0.7            NaN   \n",
       "8                 NaN                      NaN        roc_auc   \n",
       "9                 NaN                      NaN            NaN   \n",
       "10                NaN                      NaN            NaN   \n",
       "11                NaN                      NaN            NaN   \n",
       "12                NaN                      NaN            NaN   \n",
       "13                NaN                      NaN            NaN   \n",
       "14                NaN                      NaN            NaN   \n",
       "15                NaN                      NaN            NaN   \n",
       "16              aucpr                      0.5            NaN   \n",
       "17                NaN                      NaN        roc_auc   \n",
       "18                NaN                      NaN            NaN   \n",
       "19                NaN                      NaN            NaN   \n",
       "20                NaN                      NaN            NaN   \n",
       "21                NaN                      NaN            NaN   \n",
       "22                NaN                      NaN            NaN   \n",
       "23                NaN                      NaN            NaN   \n",
       "24                NaN                      NaN            NaN   \n",
       "25              aucpr                      0.5            NaN   \n",
       "26                NaN                      NaN             f1   \n",
       "\n",
       "    params.max_iter          params.loss  params.l2_regularization  \n",
       "0               NaN                  NaN                       NaN  \n",
       "1               NaN                  NaN                       NaN  \n",
       "2               NaN                  NaN                       NaN  \n",
       "3               NaN                  NaN                       NaN  \n",
       "4               NaN                  NaN                       NaN  \n",
       "5               NaN                  NaN                       NaN  \n",
       "6               NaN                  NaN                       NaN  \n",
       "7               NaN                  NaN                       NaN  \n",
       "8             400.0  binary_crossentropy                      0.40  \n",
       "9               NaN                  NaN                       NaN  \n",
       "10              NaN                  NaN                       NaN  \n",
       "11              NaN                  NaN                       NaN  \n",
       "12              NaN                  NaN                       NaN  \n",
       "13              NaN                  NaN                       NaN  \n",
       "14              NaN                  NaN                       NaN  \n",
       "15              NaN                  NaN                       NaN  \n",
       "16              NaN                  NaN                       NaN  \n",
       "17            250.0  binary_crossentropy                      0.75  \n",
       "18              NaN                  NaN                       NaN  \n",
       "19              NaN                  NaN                       NaN  \n",
       "20              NaN                  NaN                       NaN  \n",
       "21              NaN                  NaN                       NaN  \n",
       "22              NaN                  NaN                       NaN  \n",
       "23              NaN                  NaN                       NaN  \n",
       "24              NaN                  NaN                       NaN  \n",
       "25              NaN                  NaN                       NaN  \n",
       "26            425.0  binary_crossentropy                      0.20  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SPECIESES = [\"1\", \"2\", \"1 2\"]\n",
    "MODELS = [\"RandomForestClassifier\", \"BalancedRandomForestClassifier\", \"DecisionTreeClassifier\", \"KNeighborsClassifier\", \"SVM\", \"RUSBoostClassifier\" , \"AdaBoostClassifier\", \"XGBClassifier\", \"HistGradientBoostingClassifier\"]\n",
    "TARGET = \"is_dead\"\n",
    "\n",
    "binary_classifcation_results = list()\n",
    "\n",
    "for SPECIES in SPECIESES:\n",
    "    num_cols = [col for col in binned_data[SPECIES][\"train\"].columns if (binned_data[SPECIES][\"train\"][col].dtype != object)]\n",
    "    sampling_strategy_over_sample = {\n",
    "        \"healthy\": dict(Counter(binned_data[SPECIES][\"train\"][\"damage_class_group\"]))[\"healthy\"],\n",
    "        \"damaged\": dict(Counter(binned_data[SPECIES][\"train\"][\"damage_class_group\"]))[\"damaged\"],\n",
    "        \"dead\": dict(Counter(binned_data[SPECIES][\"train\"][\"damage_class_group\"]))[\"healthy\"]\n",
    "    }\n",
    "    sampler = SMOTEENN(sampling_strategy=sampling_strategy_over_sample, smote=SMOTE(random_state=2022, k_neighbors=6, sampling_strategy=sampling_strategy_over_sample), enn=EditedNearestNeighbours(n_neighbors=5, kind_sel=\"mode\", n_jobs=58), random_state=2022, n_jobs=58)\n",
    "    X_resampled, y_resampled = sampler.fit_resample(X=binned_data[SPECIES][\"train\"][num_cols], y=binned_data[SPECIES][\"train\"][\"damage_class_group\"])\n",
    "    \n",
    "    # over sample (TARGET WILL BECOME TWICE NUMBERS)\n",
    "    sampling_strategy_under_sample = {\n",
    "        \"healthy\": dict(Counter(y_resampled))[\"healthy\"],\n",
    "        \"damaged\": dict(Counter(y_resampled))[\"healthy\"],\n",
    "        \"dead\": dict(Counter(y_resampled))[\"dead\"]\n",
    "    }\n",
    "    under_sampler = RandomUnderSampler(random_state=2022, sampling_strategy=sampling_strategy_under_sample)\n",
    "    X_resampled, y_resampled = under_sampler.fit_resample(X=X_resampled[num_cols], y=y_resampled)\n",
    "\n",
    "    for MODEL in MODELS:\n",
    "        if os.path.exists(f\"{EXPORT_PATH}/{MODEL}_{SPECIES_CODE[SPECIES]}_{TARGET}.json\"):\n",
    "            continue\n",
    "        print(\"-\"*100)\n",
    "        print(f\"{MODEL} -> {SPECIES_CODE[SPECIES]}@{TARGET}\")\n",
    "        print(\"\\t performing backward feature elemination...\")\n",
    "        try:\n",
    "            init_model_params = get_model_params(_model=MODEL, _target=TARGET, _species=SPECIES_CODE[SPECIES])\n",
    "        except FileNotFoundError:\n",
    "            init_model_params = {}\n",
    "            \n",
    "        if \"class_weight\" in init_model_params:\n",
    "            init_model_params[\"class_weight\"] = define_class_weight(X_resampled[TARGET])\n",
    "        if \"pos_scale\" in init_model_params:\n",
    "            init_model_params[\"pos_scale\"] = define_pos_scale(X_resampled[TARGET])\n",
    "\n",
    "        skf = StratifiedKFold(n_splits=3, shuffle=True, random_state=2022)\n",
    "        f1_scorer = metrics.make_scorer(metrics.f1_score, **{\"average\": \"weighted\"})\n",
    "\n",
    "        if MODEL == \"RandomForestClassifier\":\n",
    "            model = RandomForestClassifier(**init_model_params)\n",
    "        elif MODEL == \"XGBClassifier\":\n",
    "            model = xgb.XGBClassifier(**init_model_params)\n",
    "        elif MODEL == \"KNeighborsClassifier\":\n",
    "            model = KNeighborsClassifier(**init_model_params)\n",
    "        elif MODEL == \"DecisionTreeClassifier\":\n",
    "            model = DecisionTreeClassifier(**init_model_params)\n",
    "        elif MODEL == \"HistGradientBoostingClassifier\":\n",
    "            model = HistGradientBoostingClassifier(**init_model_params)\n",
    "        elif MODEL == \"BalancedRandomForestClassifier\":\n",
    "            model = BalancedRandomForestClassifier(**init_model_params)\n",
    "        elif MODEL == \"RUSBoostClassifier\":\n",
    "            model = RUSBoostClassifier(**init_model_params)\n",
    "        elif MODEL == \"AdaBoostClassifier\":\n",
    "            model = AdaBoostClassifier(**init_model_params)\n",
    "        else: #SVM\n",
    "            model = SVC(**init_model_params)\n",
    "\n",
    "        sfs = SequentialFeatureSelector(estimator=model, direction=\"backward\", scoring=f1_scorer, cv=skf, n_jobs=58)\n",
    "        sfs.fit(X_resampled[all_features], X_resampled[TARGET])\n",
    "        relevant_features = list(X_resampled[all_features].columns[sfs.get_support()])\n",
    "\n",
    "        # TRAINING DATA\n",
    "        X_train = X_resampled[relevant_features]\n",
    "        y_train = X_resampled[TARGET]\n",
    "        # TEST DATA\n",
    "        X_test = binned_data[SPECIES][\"test\"][relevant_features]\n",
    "        y_test = binned_data[SPECIES][\"test\"][TARGET]\n",
    "\n",
    "        print(\"\\t performing hyperparameter tuning...\")\n",
    "\n",
    "        if MODEL == \"RandomForestClassifier\":\n",
    "            params_rf = PARAMS_RF\n",
    "            params_rf[\"class_weight\"] = [define_class_weight(y_train.values)]\n",
    "            fitted_model_params = parameter_tuning(_model=RandomForestClassifier(), _params=params_rf, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = RandomForestClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"XGBClassifier\":\n",
    "            params_xgb = PARAMS_XGB\n",
    "            params_xgb['scale_pos_weight'] = [define_pos_scale(y_train.values)]\n",
    "            fitted_model_params = parameter_tuning(_model=xgb.XGBClassifier(), _params=params_xgb, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = xgb.XGBClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"KNeighborsClassifier\":\n",
    "            params_kn = PARAMS_KN\n",
    "            fitted_model_params = parameter_tuning(_model=KNeighborsClassifier(), _params=params_kn, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = KNeighborsClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"DecisionTreeClassifier\":\n",
    "            params_dt = PARAMS_DT\n",
    "            params_dt['class_weight'] = [define_class_weight(y_train.values)]\n",
    "            fitted_model_params = parameter_tuning(_model=DecisionTreeClassifier(), _params=params_dt, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = DecisionTreeClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"HistGradientBoostingClassifier\":\n",
    "            params_hgb = PARAMS_HGB\n",
    "            fitted_model_params = parameter_tuning(_model=HistGradientBoostingClassifier(), _params=params_hgb, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = HistGradientBoostingClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"BalancedRandomForestClassifier\":\n",
    "            params_brf = PARAMS_BRF\n",
    "            fitted_model_params = parameter_tuning(_model=BalancedRandomForestClassifier(), _params=params_brf, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = BalancedRandomForestClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"RUSBoostClassifier\":\n",
    "            params_rus = PARAMS_RUS\n",
    "            fitted_model_params = parameter_tuning(_model=RUSBoostClassifier(), _params=params_rus, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = RUSBoostClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"AdaBoostClassifier\":\n",
    "            params_ada = PARAMS_ADA\n",
    "            fitted_model_params = parameter_tuning(_model=AdaBoostClassifier(), _params=params_ada, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = AdaBoostClassifier(**fitted_model_params)\n",
    "        else:\n",
    "            params_svm = PARAMS_SVM\n",
    "            params_svm['class_weight'] = [define_class_weight(y_train.values)]\n",
    "            fitted_model_params = parameter_tuning(_model=SVC(), _params=params_svm, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = SVC(**fitted_model_params)\n",
    "\n",
    "        # CREATING BAGGING CLASSIFIER\n",
    "        model = BaggingClassifier(base_estimator=model, n_estimators=15, max_samples=.2, max_features=1., bootstrap=True, bootstrap_features=True, oob_score=True, n_jobs=16)\n",
    "        print(\"\\t fitting model...\")\n",
    "        model.fit(X_train, y_train)\n",
    "        # save model\n",
    "        pickle.dump(model, open(f\"{EXPORT_PATH}/{MODEL}_{SPECIES_CODE[SPECIES]}_{TARGET}.sav\", 'wb'))\n",
    "\n",
    "        # predict probabilities\n",
    "        y_pred_proba = model.predict_proba(X_test)\n",
    "\n",
    "        print(\"\\t performing permutation feature importance...\")\n",
    "        from sklearn.inspection import permutation_importance\n",
    "        permutation_importance = permutation_importance(model, X_test, y_test, n_repeats=5, random_state=2022, n_jobs=32, scoring=f1_scorer)\n",
    "        permutation_importance_obj = {}\n",
    "        for i, feat_imp in enumerate(permutation_importance.importances_mean):\n",
    "            permutation_importance_obj[all_features[i]] = feat_imp\n",
    "\n",
    "        print(\"\\t evaluating...\")\n",
    "        results = {}\n",
    "        results[\"species\"] = SPECIES_CODE[SPECIES]\n",
    "        results[\"model\"] = MODEL\n",
    "        results[\"target\"] = TARGET\n",
    "        results[\"params\"] = fitted_model_params\n",
    "        results[\"relevant_features\"] = relevant_features\n",
    "        results[\"feature_permutaion_importance\"] = permutation_importance_obj\n",
    "\n",
    "        results[\"metrics\"] = {}\n",
    "        results[\"metrics\"][\"auc\"] = metrics.roc_auc_score(y_test.values, y_pred_proba[:, 1])\n",
    "\n",
    "        ## ROC AUC\n",
    "        results[\"metrics\"][\"roc\"] = {}\n",
    "        threshold_roc, gmean_roc = roc_auc(y_test.values, y_pred_proba[:,1], axes=None)\n",
    "        results[\"metrics\"][\"roc\"][\"threshold\"] = threshold_roc\n",
    "        y_pred_roc = apply_prediction(y_pred_proba[:, 1], threshold_roc)\n",
    "        results[\"metrics\"][\"roc\"][\"cohen_kappa\"] = metrics.cohen_kappa_score(y_test.values, y_pred_roc)\n",
    "        results[\"metrics\"][\"roc\"][\"f1\"] = metrics.f1_score(y_test.values, y_pred_roc)\n",
    "        results[\"metrics\"][\"roc\"][\"recall\"] = metrics.recall_score(y_test.values, y_pred_roc)\n",
    "        results[\"metrics\"][\"roc\"][\"precision\"] = metrics.precision_score(y_test.values, y_pred_roc)\n",
    "        tn, fp, fn, tp = metrics.confusion_matrix(y_test, y_pred_roc).ravel()\n",
    "        results[\"metrics\"][\"roc\"][\"tn\"] = tn\n",
    "        results[\"metrics\"][\"roc\"][\"fp\"] = fp\n",
    "        results[\"metrics\"][\"roc\"][\"fn\"] = fn\n",
    "        results[\"metrics\"][\"roc\"][\"tp\"] = tp\n",
    "\n",
    "        ## PRC\n",
    "        results[\"metrics\"][\"prc\"] = {}\n",
    "        threshold_prc, fscore_prc = prc_rc(y_test.values, y_pred_proba[:,1], axes=None)\n",
    "        results[\"metrics\"][\"prc\"][\"threshold\"] = threshold_prc\n",
    "        y_pred_prc = apply_prediction(y_pred_proba[:, 1], threshold_prc)\n",
    "        results[\"metrics\"][\"prc\"][\"cohen_kappa\"] = metrics.cohen_kappa_score(y_test.values, y_pred_prc)\n",
    "        results[\"metrics\"][\"prc\"][\"f1\"] = metrics.f1_score(y_test.values, y_pred_prc)\n",
    "        results[\"metrics\"][\"prc\"][\"recall\"] = metrics.recall_score(y_test.values, y_pred_prc)\n",
    "        results[\"metrics\"][\"prc\"][\"precision\"] = metrics.precision_score(y_test.values, y_pred_prc)\n",
    "        tn, fp, fn, tp = metrics.confusion_matrix(y_test, y_pred_prc).ravel()\n",
    "        results[\"metrics\"][\"prc\"][\"tn\"] = tn\n",
    "        results[\"metrics\"][\"prc\"][\"fp\"] = fp\n",
    "        results[\"metrics\"][\"prc\"][\"fn\"] = fn\n",
    "        results[\"metrics\"][\"prc\"][\"tp\"] = tp\n",
    "\n",
    "        ## TUNING\n",
    "        results[\"metrics\"][\"tuning\"] = {}\n",
    "        threshold_tuning, fscore_tuneing = tune_threshold(y_test.values, y_pred_proba[:,1], axes=None)\n",
    "        results[\"metrics\"][\"tuning\"][\"threshold\"] = threshold_tuning\n",
    "        y_pred_tuning = apply_prediction(y_pred_proba[:, 1], threshold_tuning)\n",
    "        results[\"metrics\"][\"tuning\"][\"cohen_kappa\"] = metrics.cohen_kappa_score(y_test.values, y_pred_tuning)\n",
    "        results[\"metrics\"][\"tuning\"][\"f1\"] = metrics.f1_score(y_test.values, y_pred_tuning)\n",
    "        results[\"metrics\"][\"tuning\"][\"recall\"] = metrics.recall_score(y_test.values, y_pred_tuning)\n",
    "        results[\"metrics\"][\"tuning\"][\"precision\"] = metrics.precision_score(y_test.values, y_pred_tuning)\n",
    "        tn, fp, fn, tp = metrics.confusion_matrix(y_test, y_pred_tuning).ravel()\n",
    "        results[\"metrics\"][\"tuning\"][\"tn\"] = tn\n",
    "        results[\"metrics\"][\"tuning\"][\"fp\"] = fp\n",
    "        results[\"metrics\"][\"tuning\"][\"fn\"] = fn\n",
    "        results[\"metrics\"][\"tuning\"][\"tp\"] = tp\n",
    "\n",
    "        # quick export to dump data\n",
    "        with open(f\"{EXPORT_PATH}/{MODEL}_{SPECIES_CODE[SPECIES]}_{TARGET}.json\", 'w', encoding='utf-8') as f:\n",
    "            json.dump(str(dict((k, v) for k,v in results.items())), f, ensure_ascii=False, indent=4)\n",
    "        pd.json_normalize(results).to_csv(f\"{EXPORT_PATH}/{MODEL}_{SPECIES_CODE[SPECIES]}_{TARGET}.csv\", index=False)\n",
    "\n",
    "        binary_classifcation_results.append(results)\n",
    "\n",
    "print(\"-\"*75)\n",
    "print(f\"EXPORTING OVERALL RESULTS TO {EXPORT_PATH}/modelling_pipeline_results.csv\")\n",
    "print(\"-\"*75)\n",
    "df_result = pd.json_normalize(binary_classifcation_results)\n",
    "df_result.to_csv(f\"{EXPORT_PATH}/modelling_pipeline_results_dead.csv\", index=False)\n",
    "df_result"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74eac696-e661-4066-9933-f361dfe15bd9",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### Healthy Vegetation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "fb958213-2167-47a8-ad59-fa1ebb938c69",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-04-08T21:30:09.578477Z",
     "iopub.status.busy": "2022-04-08T21:30:09.578477Z",
     "iopub.status.idle": "2022-04-09T18:48:11.532003Z",
     "shell.execute_reply": "2022-04-09T18:48:11.532003Z",
     "shell.execute_reply.started": "2022-04-08T21:30:09.578477Z"
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "----------------------------------------------------------------------------------------------------\n",
      "RandomForestClassifier -> Deciduous@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "BalancedRandomForestClassifier -> Deciduous@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "DecisionTreeClassifier -> Deciduous@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "KNeighborsClassifier -> Deciduous@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "SVM -> Deciduous@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "RUSBoostClassifier -> Deciduous@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "AdaBoostClassifier -> Deciduous@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "XGBClassifier -> Deciduous@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "HistGradientBoostingClassifier -> Deciduous@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "RandomForestClassifier -> Conifer@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "BalancedRandomForestClassifier -> Conifer@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "DecisionTreeClassifier -> Conifer@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "KNeighborsClassifier -> Conifer@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "SVM -> Conifer@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "RUSBoostClassifier -> Conifer@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "AdaBoostClassifier -> Conifer@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "XGBClassifier -> Conifer@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "HistGradientBoostingClassifier -> Conifer@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "RandomForestClassifier -> Mixed@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "BalancedRandomForestClassifier -> Mixed@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "DecisionTreeClassifier -> Mixed@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "KNeighborsClassifier -> Mixed@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "SVM -> Mixed@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "RUSBoostClassifier -> Mixed@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "AdaBoostClassifier -> Mixed@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "XGBClassifier -> Mixed@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "----------------------------------------------------------------------------------------------------\n",
      "HistGradientBoostingClassifier -> Mixed@is_healthy\n",
      "\t performing backward feature elemination...\n",
      "\t performing hyperparameter tuning...\n",
      "\t fitting model...\n",
      "\t performing permutation feature importance...\n",
      "\t evaluating...\n",
      "---------------------------------------------------------------------------\n",
      "EXPORTING OVERALL RESULTS TO ./results/optimization/v5/modelling_pipeline_results.csv\n",
      "---------------------------------------------------------------------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>species</th>\n",
       "      <th>model</th>\n",
       "      <th>target</th>\n",
       "      <th>relevant_features</th>\n",
       "      <th>params.warm_start</th>\n",
       "      <th>params.random_state</th>\n",
       "      <th>params.n_jobs</th>\n",
       "      <th>params.n_estimators</th>\n",
       "      <th>params.min_samples_split</th>\n",
       "      <th>params.min_samples_leaf</th>\n",
       "      <th>params.max_features</th>\n",
       "      <th>params.max_depth</th>\n",
       "      <th>params.class_weight.0</th>\n",
       "      <th>params.class_weight.1</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_0</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_1</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_2</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_3</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_4</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_5</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_6</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_7</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_8</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_9</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_10</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_11</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_12</th>\n",
       "      <th>feature_permutaion_importance.location_cluster_13</th>\n",
       "      <th>feature_permutaion_importance.tree_1</th>\n",
       "      <th>feature_permutaion_importance.evi2</th>\n",
       "      <th>feature_permutaion_importance.evi2-1</th>\n",
       "      <th>feature_permutaion_importance.evi2_diff</th>\n",
       "      <th>feature_permutaion_importance.evi2_max_diff</th>\n",
       "      <th>feature_permutaion_importance.evi2_raster</th>\n",
       "      <th>feature_permutaion_importance.evi2_raster-1</th>\n",
       "      <th>feature_permutaion_importance.evi2_raster_diff</th>\n",
       "      <th>feature_permutaion_importance.evi2_vegetation_raster</th>\n",
       "      <th>feature_permutaion_importance.evi2_vegetation_raster-1</th>\n",
       "      <th>feature_permutaion_importance.evi2_vegetation_raster_diff</th>\n",
       "      <th>feature_permutaion_importance.ndvi</th>\n",
       "      <th>feature_permutaion_importance.ndvi-1</th>\n",
       "      <th>feature_permutaion_importance.ndvi_diff</th>\n",
       "      <th>metrics.auc</th>\n",
       "      <th>metrics.roc.threshold</th>\n",
       "      <th>metrics.roc.cohen_kappa</th>\n",
       "      <th>metrics.roc.f1</th>\n",
       "      <th>metrics.roc.recall</th>\n",
       "      <th>metrics.roc.precision</th>\n",
       "      <th>metrics.roc.tn</th>\n",
       "      <th>metrics.roc.fp</th>\n",
       "      <th>metrics.roc.fn</th>\n",
       "      <th>metrics.roc.tp</th>\n",
       "      <th>metrics.prc.threshold</th>\n",
       "      <th>metrics.prc.cohen_kappa</th>\n",
       "      <th>metrics.prc.f1</th>\n",
       "      <th>metrics.prc.recall</th>\n",
       "      <th>metrics.prc.precision</th>\n",
       "      <th>metrics.prc.tn</th>\n",
       "      <th>metrics.prc.fp</th>\n",
       "      <th>metrics.prc.fn</th>\n",
       "      <th>metrics.prc.tp</th>\n",
       "      <th>metrics.tuning.threshold</th>\n",
       "      <th>metrics.tuning.cohen_kappa</th>\n",
       "      <th>metrics.tuning.f1</th>\n",
       "      <th>metrics.tuning.recall</th>\n",
       "      <th>metrics.tuning.precision</th>\n",
       "      <th>metrics.tuning.tn</th>\n",
       "      <th>metrics.tuning.fp</th>\n",
       "      <th>metrics.tuning.fn</th>\n",
       "      <th>metrics.tuning.tp</th>\n",
       "      <th>params.splitter</th>\n",
       "      <th>params.min_weight_fraction_leaf</th>\n",
       "      <th>params.min_impurity_decrease</th>\n",
       "      <th>params.max_leaf_nodes</th>\n",
       "      <th>params.criterion</th>\n",
       "      <th>params.ccp_alpha</th>\n",
       "      <th>params.weights</th>\n",
       "      <th>params.p</th>\n",
       "      <th>params.n_neighbors</th>\n",
       "      <th>params.metric</th>\n",
       "      <th>params.leaf_size</th>\n",
       "      <th>params.algorithm</th>\n",
       "      <th>params.tol</th>\n",
       "      <th>params.shrinking</th>\n",
       "      <th>params.probability</th>\n",
       "      <th>params.kernel</th>\n",
       "      <th>params.gamma</th>\n",
       "      <th>params.decision_function_shape</th>\n",
       "      <th>params.C</th>\n",
       "      <th>params.replacement</th>\n",
       "      <th>params.learning_rate</th>\n",
       "      <th>params.subsample</th>\n",
       "      <th>params.seed</th>\n",
       "      <th>params.scale_pos_weight</th>\n",
       "      <th>params.objective</th>\n",
       "      <th>params.lambda</th>\n",
       "      <th>params.eval_metric</th>\n",
       "      <th>params.colsample_bytree</th>\n",
       "      <th>params.scoring</th>\n",
       "      <th>params.max_iter</th>\n",
       "      <th>params.loss</th>\n",
       "      <th>params.l2_regularization</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>RandomForestClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_0, location_cluster_3, locat...</td>\n",
       "      <td>False</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.728614</td>\n",
       "      <td>1.593548</td>\n",
       "      <td>-0.009623</td>\n",
       "      <td>-0.007627</td>\n",
       "      <td>0.008533</td>\n",
       "      <td>-0.007199</td>\n",
       "      <td>-0.007663</td>\n",
       "      <td>-0.004926</td>\n",
       "      <td>-0.002634</td>\n",
       "      <td>0.009967</td>\n",
       "      <td>-0.008624</td>\n",
       "      <td>-0.000128</td>\n",
       "      <td>0.000165</td>\n",
       "      <td>-0.002375</td>\n",
       "      <td>0.002788</td>\n",
       "      <td>-0.004263</td>\n",
       "      <td>-0.003967</td>\n",
       "      <td>-0.005509</td>\n",
       "      <td>-0.005954</td>\n",
       "      <td>-0.001174</td>\n",
       "      <td>0.003391</td>\n",
       "      <td>0.007321</td>\n",
       "      <td>0.001498</td>\n",
       "      <td>-0.006466</td>\n",
       "      <td>-0.004845</td>\n",
       "      <td>0.011868</td>\n",
       "      <td>-0.013125</td>\n",
       "      <td>-0.002672</td>\n",
       "      <td>-0.003207</td>\n",
       "      <td>0.001084</td>\n",
       "      <td>0.641390</td>\n",
       "      <td>0.378521</td>\n",
       "      <td>0.129621</td>\n",
       "      <td>0.295129</td>\n",
       "      <td>0.817460</td>\n",
       "      <td>0.180070</td>\n",
       "      <td>491</td>\n",
       "      <td>469</td>\n",
       "      <td>23</td>\n",
       "      <td>103</td>\n",
       "      <td>0.378521</td>\n",
       "      <td>0.129621</td>\n",
       "      <td>0.295129</td>\n",
       "      <td>0.817460</td>\n",
       "      <td>0.180070</td>\n",
       "      <td>491</td>\n",
       "      <td>469</td>\n",
       "      <td>23</td>\n",
       "      <td>103</td>\n",
       "      <td>0.378</td>\n",
       "      <td>0.127868</td>\n",
       "      <td>0.293866</td>\n",
       "      <td>0.817460</td>\n",
       "      <td>0.179130</td>\n",
       "      <td>488</td>\n",
       "      <td>472</td>\n",
       "      <td>23</td>\n",
       "      <td>103</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>BalancedRandomForestClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_0, location_cluster_1, locat...</td>\n",
       "      <td>True</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>224.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>192.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.010253</td>\n",
       "      <td>0.010497</td>\n",
       "      <td>0.004653</td>\n",
       "      <td>0.029545</td>\n",
       "      <td>-0.010675</td>\n",
       "      <td>-0.005051</td>\n",
       "      <td>0.029605</td>\n",
       "      <td>-0.010120</td>\n",
       "      <td>0.016160</td>\n",
       "      <td>-0.000769</td>\n",
       "      <td>-0.015100</td>\n",
       "      <td>0.014696</td>\n",
       "      <td>0.002013</td>\n",
       "      <td>-0.004992</td>\n",
       "      <td>0.005815</td>\n",
       "      <td>0.001291</td>\n",
       "      <td>0.001557</td>\n",
       "      <td>0.001105</td>\n",
       "      <td>0.012319</td>\n",
       "      <td>0.022568</td>\n",
       "      <td>0.006764</td>\n",
       "      <td>0.002972</td>\n",
       "      <td>-0.005225</td>\n",
       "      <td>0.010537</td>\n",
       "      <td>-0.008534</td>\n",
       "      <td>-0.007698</td>\n",
       "      <td>0.018076</td>\n",
       "      <td>0.020837</td>\n",
       "      <td>0.674024</td>\n",
       "      <td>0.533274</td>\n",
       "      <td>0.172253</td>\n",
       "      <td>0.320721</td>\n",
       "      <td>0.706349</td>\n",
       "      <td>0.207459</td>\n",
       "      <td>620</td>\n",
       "      <td>340</td>\n",
       "      <td>37</td>\n",
       "      <td>89</td>\n",
       "      <td>0.533274</td>\n",
       "      <td>0.172253</td>\n",
       "      <td>0.320721</td>\n",
       "      <td>0.706349</td>\n",
       "      <td>0.207459</td>\n",
       "      <td>620</td>\n",
       "      <td>340</td>\n",
       "      <td>37</td>\n",
       "      <td>89</td>\n",
       "      <td>0.533</td>\n",
       "      <td>0.172253</td>\n",
       "      <td>0.320721</td>\n",
       "      <td>0.706349</td>\n",
       "      <td>0.207459</td>\n",
       "      <td>620</td>\n",
       "      <td>340</td>\n",
       "      <td>37</td>\n",
       "      <td>89</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>DecisionTreeClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_8, location_cluster_9, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.728614</td>\n",
       "      <td>1.593548</td>\n",
       "      <td>0.001742</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.016219</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.011919</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.015103</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.006035</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.007150</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.464674</td>\n",
       "      <td>0.528543</td>\n",
       "      <td>0.004576</td>\n",
       "      <td>0.188312</td>\n",
       "      <td>0.460317</td>\n",
       "      <td>0.118367</td>\n",
       "      <td>528</td>\n",
       "      <td>432</td>\n",
       "      <td>68</td>\n",
       "      <td>58</td>\n",
       "      <td>0.453294</td>\n",
       "      <td>0.031864</td>\n",
       "      <td>0.227273</td>\n",
       "      <td>0.873016</td>\n",
       "      <td>0.130641</td>\n",
       "      <td>228</td>\n",
       "      <td>732</td>\n",
       "      <td>16</td>\n",
       "      <td>110</td>\n",
       "      <td>0.453</td>\n",
       "      <td>0.031864</td>\n",
       "      <td>0.227273</td>\n",
       "      <td>0.873016</td>\n",
       "      <td>0.130641</td>\n",
       "      <td>228</td>\n",
       "      <td>732</td>\n",
       "      <td>16</td>\n",
       "      <td>110</td>\n",
       "      <td>best</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.05</td>\n",
       "      <td>1217.0</td>\n",
       "      <td>entropy</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>KNeighborsClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_4, location_cluster_5, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.005432</td>\n",
       "      <td>0.001893</td>\n",
       "      <td>-0.004555</td>\n",
       "      <td>-0.001864</td>\n",
       "      <td>-0.003264</td>\n",
       "      <td>-0.003010</td>\n",
       "      <td>-0.002222</td>\n",
       "      <td>-0.002207</td>\n",
       "      <td>0.001837</td>\n",
       "      <td>0.001239</td>\n",
       "      <td>0.002009</td>\n",
       "      <td>-0.000226</td>\n",
       "      <td>0.000714</td>\n",
       "      <td>-0.000231</td>\n",
       "      <td>-0.001834</td>\n",
       "      <td>0.000769</td>\n",
       "      <td>0.001691</td>\n",
       "      <td>0.004495</td>\n",
       "      <td>-0.000563</td>\n",
       "      <td>0.011778</td>\n",
       "      <td>0.004007</td>\n",
       "      <td>-0.003161</td>\n",
       "      <td>0.003965</td>\n",
       "      <td>0.008486</td>\n",
       "      <td>-0.002563</td>\n",
       "      <td>0.000043</td>\n",
       "      <td>0.003666</td>\n",
       "      <td>-0.002881</td>\n",
       "      <td>0.551455</td>\n",
       "      <td>0.204477</td>\n",
       "      <td>0.078088</td>\n",
       "      <td>0.259615</td>\n",
       "      <td>0.857143</td>\n",
       "      <td>0.152975</td>\n",
       "      <td>362</td>\n",
       "      <td>598</td>\n",
       "      <td>18</td>\n",
       "      <td>108</td>\n",
       "      <td>0.667871</td>\n",
       "      <td>-0.014048</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>952</td>\n",
       "      <td>8</td>\n",
       "      <td>126</td>\n",
       "      <td>0</td>\n",
       "      <td>0.197</td>\n",
       "      <td>0.077044</td>\n",
       "      <td>0.259649</td>\n",
       "      <td>0.880952</td>\n",
       "      <td>0.152263</td>\n",
       "      <td>342</td>\n",
       "      <td>618</td>\n",
       "      <td>15</td>\n",
       "      <td>111</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>distance</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>minkowski</td>\n",
       "      <td>44.0</td>\n",
       "      <td>kd_tree</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>SVM</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_0, location_cluster_1, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.728614</td>\n",
       "      <td>1.593548</td>\n",
       "      <td>0.012402</td>\n",
       "      <td>0.034887</td>\n",
       "      <td>0.011077</td>\n",
       "      <td>0.033593</td>\n",
       "      <td>0.006749</td>\n",
       "      <td>-0.000796</td>\n",
       "      <td>0.005038</td>\n",
       "      <td>0.002318</td>\n",
       "      <td>0.004610</td>\n",
       "      <td>0.016172</td>\n",
       "      <td>-0.001796</td>\n",
       "      <td>0.005044</td>\n",
       "      <td>0.013049</td>\n",
       "      <td>0.007353</td>\n",
       "      <td>0.002930</td>\n",
       "      <td>0.001417</td>\n",
       "      <td>0.005484</td>\n",
       "      <td>0.003188</td>\n",
       "      <td>0.003458</td>\n",
       "      <td>0.012180</td>\n",
       "      <td>0.000766</td>\n",
       "      <td>0.003485</td>\n",
       "      <td>0.020210</td>\n",
       "      <td>0.009306</td>\n",
       "      <td>0.007000</td>\n",
       "      <td>0.005620</td>\n",
       "      <td>0.015632</td>\n",
       "      <td>0.008043</td>\n",
       "      <td>0.678191</td>\n",
       "      <td>0.314825</td>\n",
       "      <td>0.138927</td>\n",
       "      <td>0.295918</td>\n",
       "      <td>0.690476</td>\n",
       "      <td>0.188312</td>\n",
       "      <td>585</td>\n",
       "      <td>375</td>\n",
       "      <td>39</td>\n",
       "      <td>87</td>\n",
       "      <td>0.392481</td>\n",
       "      <td>0.183955</td>\n",
       "      <td>0.310526</td>\n",
       "      <td>0.468254</td>\n",
       "      <td>0.232283</td>\n",
       "      <td>765</td>\n",
       "      <td>195</td>\n",
       "      <td>67</td>\n",
       "      <td>59</td>\n",
       "      <td>0.386</td>\n",
       "      <td>0.179597</td>\n",
       "      <td>0.310000</td>\n",
       "      <td>0.492063</td>\n",
       "      <td>0.226277</td>\n",
       "      <td>748</td>\n",
       "      <td>212</td>\n",
       "      <td>64</td>\n",
       "      <td>62</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.003</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>poly</td>\n",
       "      <td>0.506</td>\n",
       "      <td>ovo</td>\n",
       "      <td>4.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>RUSBoostClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_4, location_cluster_5, tree_...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>440.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.014078</td>\n",
       "      <td>0.037537</td>\n",
       "      <td>0.007360</td>\n",
       "      <td>-0.001523</td>\n",
       "      <td>0.000047</td>\n",
       "      <td>-0.004974</td>\n",
       "      <td>0.011592</td>\n",
       "      <td>-0.001871</td>\n",
       "      <td>0.007838</td>\n",
       "      <td>-0.001094</td>\n",
       "      <td>-0.004589</td>\n",
       "      <td>-0.000443</td>\n",
       "      <td>0.000569</td>\n",
       "      <td>0.009953</td>\n",
       "      <td>-0.004732</td>\n",
       "      <td>-0.003094</td>\n",
       "      <td>0.020105</td>\n",
       "      <td>-0.000750</td>\n",
       "      <td>-0.004825</td>\n",
       "      <td>0.001393</td>\n",
       "      <td>0.009503</td>\n",
       "      <td>0.000383</td>\n",
       "      <td>0.018092</td>\n",
       "      <td>-0.013455</td>\n",
       "      <td>-0.006951</td>\n",
       "      <td>-0.002193</td>\n",
       "      <td>0.023288</td>\n",
       "      <td>0.000946</td>\n",
       "      <td>0.711756</td>\n",
       "      <td>0.486876</td>\n",
       "      <td>0.165773</td>\n",
       "      <td>0.320635</td>\n",
       "      <td>0.801587</td>\n",
       "      <td>0.200397</td>\n",
       "      <td>557</td>\n",
       "      <td>403</td>\n",
       "      <td>25</td>\n",
       "      <td>101</td>\n",
       "      <td>0.560297</td>\n",
       "      <td>-0.007191</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>956</td>\n",
       "      <td>4</td>\n",
       "      <td>126</td>\n",
       "      <td>0</td>\n",
       "      <td>0.505</td>\n",
       "      <td>0.236344</td>\n",
       "      <td>0.349570</td>\n",
       "      <td>0.484127</td>\n",
       "      <td>0.273543</td>\n",
       "      <td>798</td>\n",
       "      <td>162</td>\n",
       "      <td>65</td>\n",
       "      <td>61</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAMME.R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>0.0850</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>AdaBoostClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_3, location_cluster_5, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>350.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.018116</td>\n",
       "      <td>0.037088</td>\n",
       "      <td>0.006209</td>\n",
       "      <td>0.014031</td>\n",
       "      <td>0.000513</td>\n",
       "      <td>-0.003982</td>\n",
       "      <td>-0.000432</td>\n",
       "      <td>0.012043</td>\n",
       "      <td>0.004054</td>\n",
       "      <td>0.002104</td>\n",
       "      <td>0.000764</td>\n",
       "      <td>0.000352</td>\n",
       "      <td>-0.001710</td>\n",
       "      <td>0.009771</td>\n",
       "      <td>0.008974</td>\n",
       "      <td>0.000826</td>\n",
       "      <td>0.014866</td>\n",
       "      <td>-0.007647</td>\n",
       "      <td>0.014754</td>\n",
       "      <td>0.000311</td>\n",
       "      <td>0.031377</td>\n",
       "      <td>0.018623</td>\n",
       "      <td>0.001073</td>\n",
       "      <td>0.007597</td>\n",
       "      <td>0.009525</td>\n",
       "      <td>-0.006595</td>\n",
       "      <td>0.011596</td>\n",
       "      <td>0.000348</td>\n",
       "      <td>0.732870</td>\n",
       "      <td>0.494553</td>\n",
       "      <td>0.208683</td>\n",
       "      <td>0.348485</td>\n",
       "      <td>0.730159</td>\n",
       "      <td>0.228856</td>\n",
       "      <td>650</td>\n",
       "      <td>310</td>\n",
       "      <td>34</td>\n",
       "      <td>92</td>\n",
       "      <td>0.496340</td>\n",
       "      <td>0.231447</td>\n",
       "      <td>0.355769</td>\n",
       "      <td>0.587302</td>\n",
       "      <td>0.255172</td>\n",
       "      <td>744</td>\n",
       "      <td>216</td>\n",
       "      <td>52</td>\n",
       "      <td>74</td>\n",
       "      <td>0.497</td>\n",
       "      <td>0.228367</td>\n",
       "      <td>0.350877</td>\n",
       "      <td>0.555556</td>\n",
       "      <td>0.256410</td>\n",
       "      <td>757</td>\n",
       "      <td>203</td>\n",
       "      <td>56</td>\n",
       "      <td>70</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAMME.R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.4000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>XGBClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_0, location_cluster_1, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>485.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.000819</td>\n",
       "      <td>0.011509</td>\n",
       "      <td>0.004160</td>\n",
       "      <td>0.010624</td>\n",
       "      <td>0.017140</td>\n",
       "      <td>0.000570</td>\n",
       "      <td>0.000385</td>\n",
       "      <td>0.001797</td>\n",
       "      <td>0.002029</td>\n",
       "      <td>0.000570</td>\n",
       "      <td>0.001723</td>\n",
       "      <td>0.003354</td>\n",
       "      <td>0.002696</td>\n",
       "      <td>0.000873</td>\n",
       "      <td>0.004209</td>\n",
       "      <td>0.006256</td>\n",
       "      <td>-0.000820</td>\n",
       "      <td>0.009846</td>\n",
       "      <td>0.007644</td>\n",
       "      <td>0.015346</td>\n",
       "      <td>0.003461</td>\n",
       "      <td>0.007660</td>\n",
       "      <td>0.002754</td>\n",
       "      <td>0.006217</td>\n",
       "      <td>0.004338</td>\n",
       "      <td>0.001396</td>\n",
       "      <td>0.004489</td>\n",
       "      <td>0.005575</td>\n",
       "      <td>0.720693</td>\n",
       "      <td>0.363225</td>\n",
       "      <td>0.209951</td>\n",
       "      <td>0.346232</td>\n",
       "      <td>0.674603</td>\n",
       "      <td>0.232877</td>\n",
       "      <td>680</td>\n",
       "      <td>280</td>\n",
       "      <td>41</td>\n",
       "      <td>85</td>\n",
       "      <td>0.363225</td>\n",
       "      <td>0.209951</td>\n",
       "      <td>0.346232</td>\n",
       "      <td>0.674603</td>\n",
       "      <td>0.232877</td>\n",
       "      <td>680</td>\n",
       "      <td>280</td>\n",
       "      <td>41</td>\n",
       "      <td>85</td>\n",
       "      <td>0.363</td>\n",
       "      <td>0.209951</td>\n",
       "      <td>0.346232</td>\n",
       "      <td>0.674603</td>\n",
       "      <td>0.232877</td>\n",
       "      <td>680</td>\n",
       "      <td>280</td>\n",
       "      <td>41</td>\n",
       "      <td>85</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.650</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0090</td>\n",
       "      <td>0.85</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>2.187097</td>\n",
       "      <td>binary:logistic</td>\n",
       "      <td>0.4</td>\n",
       "      <td>aucpr</td>\n",
       "      <td>0.70</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Deciduous</td>\n",
       "      <td>HistGradientBoostingClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_0, location_cluster_4, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>120.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.003170</td>\n",
       "      <td>0.014441</td>\n",
       "      <td>0.040797</td>\n",
       "      <td>-0.000773</td>\n",
       "      <td>0.000926</td>\n",
       "      <td>-0.004550</td>\n",
       "      <td>-0.004454</td>\n",
       "      <td>0.002789</td>\n",
       "      <td>0.001560</td>\n",
       "      <td>-0.003742</td>\n",
       "      <td>0.001234</td>\n",
       "      <td>-0.006778</td>\n",
       "      <td>-0.008393</td>\n",
       "      <td>0.001308</td>\n",
       "      <td>-0.002052</td>\n",
       "      <td>-0.001852</td>\n",
       "      <td>0.009396</td>\n",
       "      <td>-0.006035</td>\n",
       "      <td>-0.000919</td>\n",
       "      <td>0.000380</td>\n",
       "      <td>0.003760</td>\n",
       "      <td>-0.005909</td>\n",
       "      <td>-0.003948</td>\n",
       "      <td>0.005468</td>\n",
       "      <td>0.000634</td>\n",
       "      <td>-0.005135</td>\n",
       "      <td>-0.003448</td>\n",
       "      <td>-0.003040</td>\n",
       "      <td>0.717890</td>\n",
       "      <td>0.354555</td>\n",
       "      <td>0.218823</td>\n",
       "      <td>0.347826</td>\n",
       "      <td>0.603175</td>\n",
       "      <td>0.244373</td>\n",
       "      <td>725</td>\n",
       "      <td>235</td>\n",
       "      <td>50</td>\n",
       "      <td>76</td>\n",
       "      <td>0.366990</td>\n",
       "      <td>0.229222</td>\n",
       "      <td>0.353511</td>\n",
       "      <td>0.579365</td>\n",
       "      <td>0.254355</td>\n",
       "      <td>746</td>\n",
       "      <td>214</td>\n",
       "      <td>53</td>\n",
       "      <td>73</td>\n",
       "      <td>0.366</td>\n",
       "      <td>0.229222</td>\n",
       "      <td>0.353511</td>\n",
       "      <td>0.579365</td>\n",
       "      <td>0.254355</td>\n",
       "      <td>746</td>\n",
       "      <td>214</td>\n",
       "      <td>53</td>\n",
       "      <td>73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0325</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>roc_auc</td>\n",
       "      <td>375.0</td>\n",
       "      <td>binary_crossentropy</td>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>RandomForestClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_0, location_cluster_2, locat...</td>\n",
       "      <td>False</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>432.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>192.0</td>\n",
       "      <td>0.708477</td>\n",
       "      <td>1.699173</td>\n",
       "      <td>-0.005334</td>\n",
       "      <td>-0.012223</td>\n",
       "      <td>-0.000348</td>\n",
       "      <td>0.016131</td>\n",
       "      <td>-0.008569</td>\n",
       "      <td>-0.003661</td>\n",
       "      <td>0.008769</td>\n",
       "      <td>-0.005302</td>\n",
       "      <td>0.011446</td>\n",
       "      <td>-0.013587</td>\n",
       "      <td>0.002335</td>\n",
       "      <td>-0.012694</td>\n",
       "      <td>0.000113</td>\n",
       "      <td>-0.003891</td>\n",
       "      <td>-0.014547</td>\n",
       "      <td>-0.002047</td>\n",
       "      <td>-0.017787</td>\n",
       "      <td>-0.002699</td>\n",
       "      <td>-0.016218</td>\n",
       "      <td>-0.000804</td>\n",
       "      <td>-0.005617</td>\n",
       "      <td>0.003914</td>\n",
       "      <td>0.003962</td>\n",
       "      <td>0.003577</td>\n",
       "      <td>0.012375</td>\n",
       "      <td>0.000383</td>\n",
       "      <td>-0.002875</td>\n",
       "      <td>-0.000148</td>\n",
       "      <td>0.749343</td>\n",
       "      <td>0.513832</td>\n",
       "      <td>0.369009</td>\n",
       "      <td>0.460292</td>\n",
       "      <td>0.508961</td>\n",
       "      <td>0.420118</td>\n",
       "      <td>1638</td>\n",
       "      <td>196</td>\n",
       "      <td>137</td>\n",
       "      <td>142</td>\n",
       "      <td>0.549672</td>\n",
       "      <td>0.428086</td>\n",
       "      <td>0.495010</td>\n",
       "      <td>0.444444</td>\n",
       "      <td>0.558559</td>\n",
       "      <td>1736</td>\n",
       "      <td>98</td>\n",
       "      <td>155</td>\n",
       "      <td>124</td>\n",
       "      <td>0.551</td>\n",
       "      <td>0.426177</td>\n",
       "      <td>0.492986</td>\n",
       "      <td>0.440860</td>\n",
       "      <td>0.559091</td>\n",
       "      <td>1737</td>\n",
       "      <td>97</td>\n",
       "      <td>156</td>\n",
       "      <td>123</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>BalancedRandomForestClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_1, location_cluster_4, locat...</td>\n",
       "      <td>True</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>448.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>224.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.007055</td>\n",
       "      <td>0.007502</td>\n",
       "      <td>0.000204</td>\n",
       "      <td>-0.009835</td>\n",
       "      <td>0.006992</td>\n",
       "      <td>0.005970</td>\n",
       "      <td>0.005560</td>\n",
       "      <td>-0.012768</td>\n",
       "      <td>0.006902</td>\n",
       "      <td>0.010415</td>\n",
       "      <td>0.002801</td>\n",
       "      <td>0.010132</td>\n",
       "      <td>-0.000902</td>\n",
       "      <td>0.004740</td>\n",
       "      <td>0.000729</td>\n",
       "      <td>0.007236</td>\n",
       "      <td>0.015471</td>\n",
       "      <td>0.012705</td>\n",
       "      <td>-0.000464</td>\n",
       "      <td>0.000429</td>\n",
       "      <td>0.014182</td>\n",
       "      <td>0.024113</td>\n",
       "      <td>0.008706</td>\n",
       "      <td>0.006652</td>\n",
       "      <td>0.003237</td>\n",
       "      <td>0.013587</td>\n",
       "      <td>0.002303</td>\n",
       "      <td>-0.004371</td>\n",
       "      <td>0.722115</td>\n",
       "      <td>0.623499</td>\n",
       "      <td>0.330298</td>\n",
       "      <td>0.434269</td>\n",
       "      <td>0.526882</td>\n",
       "      <td>0.369347</td>\n",
       "      <td>1583</td>\n",
       "      <td>251</td>\n",
       "      <td>132</td>\n",
       "      <td>147</td>\n",
       "      <td>0.669772</td>\n",
       "      <td>0.448559</td>\n",
       "      <td>0.502262</td>\n",
       "      <td>0.397849</td>\n",
       "      <td>0.680982</td>\n",
       "      <td>1782</td>\n",
       "      <td>52</td>\n",
       "      <td>168</td>\n",
       "      <td>111</td>\n",
       "      <td>0.669</td>\n",
       "      <td>0.442646</td>\n",
       "      <td>0.497758</td>\n",
       "      <td>0.397849</td>\n",
       "      <td>0.664671</td>\n",
       "      <td>1778</td>\n",
       "      <td>56</td>\n",
       "      <td>168</td>\n",
       "      <td>111</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>DecisionTreeClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_3, location_cluster_4, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>31.0</td>\n",
       "      <td>0.708477</td>\n",
       "      <td>1.699173</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.011310</td>\n",
       "      <td>0.000278</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.003001</td>\n",
       "      <td>-0.003968</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.002724</td>\n",
       "      <td>-0.000640</td>\n",
       "      <td>-0.004629</td>\n",
       "      <td>0.003360</td>\n",
       "      <td>-0.002416</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.011971</td>\n",
       "      <td>-0.006722</td>\n",
       "      <td>0.007502</td>\n",
       "      <td>-0.002745</td>\n",
       "      <td>0.001613</td>\n",
       "      <td>0.000248</td>\n",
       "      <td>0.003632</td>\n",
       "      <td>0.012929</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.000670</td>\n",
       "      <td>0.028260</td>\n",
       "      <td>0.014941</td>\n",
       "      <td>0.005240</td>\n",
       "      <td>0.041562</td>\n",
       "      <td>0.017070</td>\n",
       "      <td>0.636317</td>\n",
       "      <td>0.517291</td>\n",
       "      <td>0.113169</td>\n",
       "      <td>0.294498</td>\n",
       "      <td>0.652330</td>\n",
       "      <td>0.190178</td>\n",
       "      <td>1059</td>\n",
       "      <td>775</td>\n",
       "      <td>97</td>\n",
       "      <td>182</td>\n",
       "      <td>0.572528</td>\n",
       "      <td>0.152982</td>\n",
       "      <td>0.295720</td>\n",
       "      <td>0.408602</td>\n",
       "      <td>0.231707</td>\n",
       "      <td>1456</td>\n",
       "      <td>378</td>\n",
       "      <td>165</td>\n",
       "      <td>114</td>\n",
       "      <td>0.572</td>\n",
       "      <td>0.152396</td>\n",
       "      <td>0.295337</td>\n",
       "      <td>0.408602</td>\n",
       "      <td>0.231237</td>\n",
       "      <td>1455</td>\n",
       "      <td>379</td>\n",
       "      <td>165</td>\n",
       "      <td>114</td>\n",
       "      <td>random</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1473.0</td>\n",
       "      <td>entropy</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>KNeighborsClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_2, location_cluster_3, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.001024</td>\n",
       "      <td>-0.002132</td>\n",
       "      <td>-0.012222</td>\n",
       "      <td>-0.005263</td>\n",
       "      <td>-0.003147</td>\n",
       "      <td>-0.001781</td>\n",
       "      <td>-0.000759</td>\n",
       "      <td>0.000417</td>\n",
       "      <td>-0.014405</td>\n",
       "      <td>-0.010001</td>\n",
       "      <td>-0.001928</td>\n",
       "      <td>-0.006387</td>\n",
       "      <td>-0.004936</td>\n",
       "      <td>-0.012951</td>\n",
       "      <td>-0.015707</td>\n",
       "      <td>-0.009835</td>\n",
       "      <td>-0.007052</td>\n",
       "      <td>-0.019037</td>\n",
       "      <td>-0.002020</td>\n",
       "      <td>-0.010866</td>\n",
       "      <td>-0.005781</td>\n",
       "      <td>-0.012416</td>\n",
       "      <td>-0.014962</td>\n",
       "      <td>-0.000152</td>\n",
       "      <td>-0.014405</td>\n",
       "      <td>-0.005424</td>\n",
       "      <td>-0.010672</td>\n",
       "      <td>-0.004008</td>\n",
       "      <td>0.706515</td>\n",
       "      <td>0.372403</td>\n",
       "      <td>0.190979</td>\n",
       "      <td>0.351687</td>\n",
       "      <td>0.709677</td>\n",
       "      <td>0.233766</td>\n",
       "      <td>1185</td>\n",
       "      <td>649</td>\n",
       "      <td>81</td>\n",
       "      <td>198</td>\n",
       "      <td>0.843738</td>\n",
       "      <td>-0.006506</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1827</td>\n",
       "      <td>7</td>\n",
       "      <td>279</td>\n",
       "      <td>0</td>\n",
       "      <td>0.384</td>\n",
       "      <td>0.198282</td>\n",
       "      <td>0.352483</td>\n",
       "      <td>0.648746</td>\n",
       "      <td>0.241979</td>\n",
       "      <td>1267</td>\n",
       "      <td>567</td>\n",
       "      <td>98</td>\n",
       "      <td>181</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>distance</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>minkowski</td>\n",
       "      <td>24.0</td>\n",
       "      <td>ball_tree</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>SVM</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_1, location_cluster_4, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.708477</td>\n",
       "      <td>1.699173</td>\n",
       "      <td>0.009836</td>\n",
       "      <td>0.019159</td>\n",
       "      <td>-0.009174</td>\n",
       "      <td>0.023366</td>\n",
       "      <td>0.015876</td>\n",
       "      <td>0.012591</td>\n",
       "      <td>-0.001169</td>\n",
       "      <td>0.009276</td>\n",
       "      <td>0.011726</td>\n",
       "      <td>0.042705</td>\n",
       "      <td>0.004469</td>\n",
       "      <td>0.012806</td>\n",
       "      <td>0.005170</td>\n",
       "      <td>0.019353</td>\n",
       "      <td>0.037936</td>\n",
       "      <td>0.009005</td>\n",
       "      <td>0.031622</td>\n",
       "      <td>0.006200</td>\n",
       "      <td>0.012891</td>\n",
       "      <td>0.011837</td>\n",
       "      <td>0.023127</td>\n",
       "      <td>0.043149</td>\n",
       "      <td>0.025528</td>\n",
       "      <td>0.003766</td>\n",
       "      <td>0.024912</td>\n",
       "      <td>0.012259</td>\n",
       "      <td>0.003196</td>\n",
       "      <td>0.015633</td>\n",
       "      <td>0.713136</td>\n",
       "      <td>0.390597</td>\n",
       "      <td>0.221698</td>\n",
       "      <td>0.364629</td>\n",
       "      <td>0.598566</td>\n",
       "      <td>0.262166</td>\n",
       "      <td>1364</td>\n",
       "      <td>470</td>\n",
       "      <td>112</td>\n",
       "      <td>167</td>\n",
       "      <td>0.528404</td>\n",
       "      <td>0.343055</td>\n",
       "      <td>0.421260</td>\n",
       "      <td>0.383513</td>\n",
       "      <td>0.467249</td>\n",
       "      <td>1712</td>\n",
       "      <td>122</td>\n",
       "      <td>172</td>\n",
       "      <td>107</td>\n",
       "      <td>0.535</td>\n",
       "      <td>0.343203</td>\n",
       "      <td>0.420635</td>\n",
       "      <td>0.379928</td>\n",
       "      <td>0.471111</td>\n",
       "      <td>1715</td>\n",
       "      <td>119</td>\n",
       "      <td>173</td>\n",
       "      <td>106</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.002</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>poly</td>\n",
       "      <td>0.686</td>\n",
       "      <td>ovo</td>\n",
       "      <td>1.85</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>RUSBoostClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_1, location_cluster_4, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>425.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.004158</td>\n",
       "      <td>-0.000669</td>\n",
       "      <td>-0.004385</td>\n",
       "      <td>-0.006291</td>\n",
       "      <td>-0.010338</td>\n",
       "      <td>0.001144</td>\n",
       "      <td>-0.001198</td>\n",
       "      <td>-0.004153</td>\n",
       "      <td>-0.010500</td>\n",
       "      <td>-0.005415</td>\n",
       "      <td>-0.004372</td>\n",
       "      <td>-0.003787</td>\n",
       "      <td>-0.002056</td>\n",
       "      <td>-0.007383</td>\n",
       "      <td>-0.002537</td>\n",
       "      <td>-0.010505</td>\n",
       "      <td>-0.002798</td>\n",
       "      <td>-0.007649</td>\n",
       "      <td>0.000812</td>\n",
       "      <td>0.011015</td>\n",
       "      <td>0.015369</td>\n",
       "      <td>-0.002685</td>\n",
       "      <td>0.007332</td>\n",
       "      <td>-0.006928</td>\n",
       "      <td>0.004222</td>\n",
       "      <td>0.003831</td>\n",
       "      <td>-0.009872</td>\n",
       "      <td>-0.001132</td>\n",
       "      <td>0.725069</td>\n",
       "      <td>0.503334</td>\n",
       "      <td>0.201413</td>\n",
       "      <td>0.354105</td>\n",
       "      <td>0.641577</td>\n",
       "      <td>0.244536</td>\n",
       "      <td>1281</td>\n",
       "      <td>553</td>\n",
       "      <td>100</td>\n",
       "      <td>179</td>\n",
       "      <td>0.518682</td>\n",
       "      <td>0.319594</td>\n",
       "      <td>0.400786</td>\n",
       "      <td>0.365591</td>\n",
       "      <td>0.443478</td>\n",
       "      <td>1706</td>\n",
       "      <td>128</td>\n",
       "      <td>177</td>\n",
       "      <td>102</td>\n",
       "      <td>0.518</td>\n",
       "      <td>0.306666</td>\n",
       "      <td>0.393195</td>\n",
       "      <td>0.372760</td>\n",
       "      <td>0.416000</td>\n",
       "      <td>1688</td>\n",
       "      <td>146</td>\n",
       "      <td>175</td>\n",
       "      <td>104</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAMME.R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>0.0710</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>AdaBoostClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_0, location_cluster_1, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>440.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.008131</td>\n",
       "      <td>-0.005727</td>\n",
       "      <td>0.004640</td>\n",
       "      <td>0.000404</td>\n",
       "      <td>0.005330</td>\n",
       "      <td>0.017965</td>\n",
       "      <td>-0.003737</td>\n",
       "      <td>-0.001709</td>\n",
       "      <td>0.001024</td>\n",
       "      <td>-0.000194</td>\n",
       "      <td>0.008188</td>\n",
       "      <td>0.017694</td>\n",
       "      <td>0.028373</td>\n",
       "      <td>0.005340</td>\n",
       "      <td>-0.005204</td>\n",
       "      <td>-0.002049</td>\n",
       "      <td>0.001077</td>\n",
       "      <td>-0.001032</td>\n",
       "      <td>0.012903</td>\n",
       "      <td>-0.004375</td>\n",
       "      <td>0.000384</td>\n",
       "      <td>0.000694</td>\n",
       "      <td>0.010010</td>\n",
       "      <td>-0.013112</td>\n",
       "      <td>0.011424</td>\n",
       "      <td>0.001052</td>\n",
       "      <td>0.016180</td>\n",
       "      <td>0.024779</td>\n",
       "      <td>0.692472</td>\n",
       "      <td>0.499732</td>\n",
       "      <td>0.212807</td>\n",
       "      <td>0.354023</td>\n",
       "      <td>0.551971</td>\n",
       "      <td>0.260575</td>\n",
       "      <td>1397</td>\n",
       "      <td>437</td>\n",
       "      <td>125</td>\n",
       "      <td>154</td>\n",
       "      <td>0.502236</td>\n",
       "      <td>0.321829</td>\n",
       "      <td>0.402367</td>\n",
       "      <td>0.365591</td>\n",
       "      <td>0.447368</td>\n",
       "      <td>1708</td>\n",
       "      <td>126</td>\n",
       "      <td>177</td>\n",
       "      <td>102</td>\n",
       "      <td>0.502</td>\n",
       "      <td>0.298169</td>\n",
       "      <td>0.386492</td>\n",
       "      <td>0.369176</td>\n",
       "      <td>0.405512</td>\n",
       "      <td>1683</td>\n",
       "      <td>151</td>\n",
       "      <td>176</td>\n",
       "      <td>103</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAMME.R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.4250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>XGBClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_0, location_cluster_2, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>410.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.009148</td>\n",
       "      <td>-0.012580</td>\n",
       "      <td>-0.004463</td>\n",
       "      <td>-0.004508</td>\n",
       "      <td>-0.002042</td>\n",
       "      <td>0.002383</td>\n",
       "      <td>-0.011040</td>\n",
       "      <td>0.014338</td>\n",
       "      <td>-0.003511</td>\n",
       "      <td>0.006440</td>\n",
       "      <td>-0.003773</td>\n",
       "      <td>0.004782</td>\n",
       "      <td>-0.008708</td>\n",
       "      <td>0.001294</td>\n",
       "      <td>-0.002539</td>\n",
       "      <td>0.003123</td>\n",
       "      <td>0.008655</td>\n",
       "      <td>-0.002338</td>\n",
       "      <td>0.001120</td>\n",
       "      <td>-0.000850</td>\n",
       "      <td>-0.005885</td>\n",
       "      <td>0.002175</td>\n",
       "      <td>-0.005007</td>\n",
       "      <td>0.033393</td>\n",
       "      <td>-0.005767</td>\n",
       "      <td>0.000018</td>\n",
       "      <td>-0.005524</td>\n",
       "      <td>0.000569</td>\n",
       "      <td>0.733764</td>\n",
       "      <td>0.550839</td>\n",
       "      <td>0.263806</td>\n",
       "      <td>0.391089</td>\n",
       "      <td>0.566308</td>\n",
       "      <td>0.298677</td>\n",
       "      <td>1463</td>\n",
       "      <td>371</td>\n",
       "      <td>121</td>\n",
       "      <td>158</td>\n",
       "      <td>0.665856</td>\n",
       "      <td>0.392674</td>\n",
       "      <td>0.455142</td>\n",
       "      <td>0.372760</td>\n",
       "      <td>0.584270</td>\n",
       "      <td>1760</td>\n",
       "      <td>74</td>\n",
       "      <td>175</td>\n",
       "      <td>104</td>\n",
       "      <td>0.653</td>\n",
       "      <td>0.384579</td>\n",
       "      <td>0.453608</td>\n",
       "      <td>0.394265</td>\n",
       "      <td>0.533981</td>\n",
       "      <td>1738</td>\n",
       "      <td>96</td>\n",
       "      <td>169</td>\n",
       "      <td>110</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.950</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0090</td>\n",
       "      <td>0.70</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>2.398345</td>\n",
       "      <td>binary:logistic</td>\n",
       "      <td>0.9</td>\n",
       "      <td>auc</td>\n",
       "      <td>0.50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Conifer</td>\n",
       "      <td>HistGradientBoostingClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_1, location_cluster_2, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>64.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.004952</td>\n",
       "      <td>-0.002039</td>\n",
       "      <td>-0.001278</td>\n",
       "      <td>0.010660</td>\n",
       "      <td>-0.001597</td>\n",
       "      <td>0.029173</td>\n",
       "      <td>-0.004411</td>\n",
       "      <td>0.003750</td>\n",
       "      <td>0.002403</td>\n",
       "      <td>-0.001107</td>\n",
       "      <td>0.000818</td>\n",
       "      <td>-0.005608</td>\n",
       "      <td>0.001399</td>\n",
       "      <td>-0.003725</td>\n",
       "      <td>0.004231</td>\n",
       "      <td>-0.011548</td>\n",
       "      <td>0.011381</td>\n",
       "      <td>0.002610</td>\n",
       "      <td>-0.000578</td>\n",
       "      <td>0.004305</td>\n",
       "      <td>0.043426</td>\n",
       "      <td>0.002570</td>\n",
       "      <td>-0.001512</td>\n",
       "      <td>-0.007779</td>\n",
       "      <td>0.003083</td>\n",
       "      <td>-0.003248</td>\n",
       "      <td>0.018239</td>\n",
       "      <td>0.001785</td>\n",
       "      <td>0.755642</td>\n",
       "      <td>0.226930</td>\n",
       "      <td>0.197024</td>\n",
       "      <td>0.357268</td>\n",
       "      <td>0.731183</td>\n",
       "      <td>0.236385</td>\n",
       "      <td>1175</td>\n",
       "      <td>659</td>\n",
       "      <td>75</td>\n",
       "      <td>204</td>\n",
       "      <td>0.636827</td>\n",
       "      <td>0.396947</td>\n",
       "      <td>0.466801</td>\n",
       "      <td>0.415771</td>\n",
       "      <td>0.532110</td>\n",
       "      <td>1732</td>\n",
       "      <td>102</td>\n",
       "      <td>163</td>\n",
       "      <td>116</td>\n",
       "      <td>0.636</td>\n",
       "      <td>0.396947</td>\n",
       "      <td>0.466801</td>\n",
       "      <td>0.415771</td>\n",
       "      <td>0.532110</td>\n",
       "      <td>1732</td>\n",
       "      <td>102</td>\n",
       "      <td>163</td>\n",
       "      <td>116</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0400</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>roc_auc</td>\n",
       "      <td>400.0</td>\n",
       "      <td>binary_crossentropy</td>\n",
       "      <td>0.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>RandomForestClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_0, location_cluster_4, locat...</td>\n",
       "      <td>False</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>224.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>240.0</td>\n",
       "      <td>0.733673</td>\n",
       "      <td>1.569873</td>\n",
       "      <td>-0.003100</td>\n",
       "      <td>0.001680</td>\n",
       "      <td>0.034502</td>\n",
       "      <td>-0.003416</td>\n",
       "      <td>-0.007307</td>\n",
       "      <td>-0.001653</td>\n",
       "      <td>-0.001652</td>\n",
       "      <td>-0.004078</td>\n",
       "      <td>-0.001076</td>\n",
       "      <td>0.020222</td>\n",
       "      <td>-0.001336</td>\n",
       "      <td>0.010726</td>\n",
       "      <td>-0.000136</td>\n",
       "      <td>-0.004826</td>\n",
       "      <td>0.012742</td>\n",
       "      <td>-0.004046</td>\n",
       "      <td>-0.003226</td>\n",
       "      <td>0.006845</td>\n",
       "      <td>0.000192</td>\n",
       "      <td>-0.010574</td>\n",
       "      <td>0.002477</td>\n",
       "      <td>-0.001851</td>\n",
       "      <td>0.001723</td>\n",
       "      <td>-0.002634</td>\n",
       "      <td>-0.010502</td>\n",
       "      <td>-0.004168</td>\n",
       "      <td>0.000849</td>\n",
       "      <td>-0.003656</td>\n",
       "      <td>0.729471</td>\n",
       "      <td>0.437365</td>\n",
       "      <td>0.198772</td>\n",
       "      <td>0.322581</td>\n",
       "      <td>0.714286</td>\n",
       "      <td>0.208333</td>\n",
       "      <td>927</td>\n",
       "      <td>399</td>\n",
       "      <td>42</td>\n",
       "      <td>105</td>\n",
       "      <td>0.928224</td>\n",
       "      <td>-0.004008</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1323</td>\n",
       "      <td>3</td>\n",
       "      <td>147</td>\n",
       "      <td>0</td>\n",
       "      <td>0.565</td>\n",
       "      <td>0.289882</td>\n",
       "      <td>0.375000</td>\n",
       "      <td>0.469388</td>\n",
       "      <td>0.312217</td>\n",
       "      <td>1174</td>\n",
       "      <td>152</td>\n",
       "      <td>78</td>\n",
       "      <td>69</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>BalancedRandomForestClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_3, location_cluster_4, locat...</td>\n",
       "      <td>True</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>144.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>192.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.012119</td>\n",
       "      <td>0.041914</td>\n",
       "      <td>0.025683</td>\n",
       "      <td>-0.004559</td>\n",
       "      <td>-0.008496</td>\n",
       "      <td>-0.000937</td>\n",
       "      <td>0.011076</td>\n",
       "      <td>-0.014568</td>\n",
       "      <td>0.021403</td>\n",
       "      <td>0.014761</td>\n",
       "      <td>0.000678</td>\n",
       "      <td>0.021582</td>\n",
       "      <td>0.041499</td>\n",
       "      <td>0.005514</td>\n",
       "      <td>0.001439</td>\n",
       "      <td>-0.002793</td>\n",
       "      <td>0.007609</td>\n",
       "      <td>0.025472</td>\n",
       "      <td>0.004774</td>\n",
       "      <td>0.035429</td>\n",
       "      <td>0.013205</td>\n",
       "      <td>0.008932</td>\n",
       "      <td>0.011743</td>\n",
       "      <td>0.049686</td>\n",
       "      <td>-0.001364</td>\n",
       "      <td>0.053682</td>\n",
       "      <td>0.024517</td>\n",
       "      <td>0.018583</td>\n",
       "      <td>0.706064</td>\n",
       "      <td>0.592515</td>\n",
       "      <td>0.136929</td>\n",
       "      <td>0.271787</td>\n",
       "      <td>0.625850</td>\n",
       "      <td>0.173585</td>\n",
       "      <td>888</td>\n",
       "      <td>438</td>\n",
       "      <td>55</td>\n",
       "      <td>92</td>\n",
       "      <td>0.938072</td>\n",
       "      <td>-0.004008</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1323</td>\n",
       "      <td>3</td>\n",
       "      <td>147</td>\n",
       "      <td>0</td>\n",
       "      <td>0.740</td>\n",
       "      <td>0.430895</td>\n",
       "      <td>0.467890</td>\n",
       "      <td>0.346939</td>\n",
       "      <td>0.718310</td>\n",
       "      <td>1306</td>\n",
       "      <td>20</td>\n",
       "      <td>96</td>\n",
       "      <td>51</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>DecisionTreeClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_5, location_cluster_7, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>log2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.733673</td>\n",
       "      <td>1.569873</td>\n",
       "      <td>0.009225</td>\n",
       "      <td>-0.027538</td>\n",
       "      <td>-0.015193</td>\n",
       "      <td>-0.002538</td>\n",
       "      <td>0.032492</td>\n",
       "      <td>-0.017350</td>\n",
       "      <td>0.010480</td>\n",
       "      <td>0.026397</td>\n",
       "      <td>-0.009828</td>\n",
       "      <td>0.008493</td>\n",
       "      <td>0.002710</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.003883</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.007883</td>\n",
       "      <td>0.000380</td>\n",
       "      <td>0.007173</td>\n",
       "      <td>-0.003815</td>\n",
       "      <td>0.013718</td>\n",
       "      <td>0.007517</td>\n",
       "      <td>-0.005724</td>\n",
       "      <td>-0.000491</td>\n",
       "      <td>0.010981</td>\n",
       "      <td>0.011515</td>\n",
       "      <td>0.001286</td>\n",
       "      <td>0.013351</td>\n",
       "      <td>-0.004969</td>\n",
       "      <td>0.016454</td>\n",
       "      <td>0.617832</td>\n",
       "      <td>0.549839</td>\n",
       "      <td>0.066691</td>\n",
       "      <td>0.224742</td>\n",
       "      <td>0.741497</td>\n",
       "      <td>0.132442</td>\n",
       "      <td>612</td>\n",
       "      <td>714</td>\n",
       "      <td>38</td>\n",
       "      <td>109</td>\n",
       "      <td>0.831871</td>\n",
       "      <td>-0.004008</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1323</td>\n",
       "      <td>3</td>\n",
       "      <td>147</td>\n",
       "      <td>0</td>\n",
       "      <td>0.728</td>\n",
       "      <td>0.221145</td>\n",
       "      <td>0.272727</td>\n",
       "      <td>0.204082</td>\n",
       "      <td>0.410959</td>\n",
       "      <td>1283</td>\n",
       "      <td>43</td>\n",
       "      <td>117</td>\n",
       "      <td>30</td>\n",
       "      <td>best</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.00</td>\n",
       "      <td>513.0</td>\n",
       "      <td>entropy</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>KNeighborsClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_0, location_cluster_2, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.001631</td>\n",
       "      <td>0.001112</td>\n",
       "      <td>0.005163</td>\n",
       "      <td>-0.001539</td>\n",
       "      <td>0.001054</td>\n",
       "      <td>0.001725</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>-0.000801</td>\n",
       "      <td>0.023813</td>\n",
       "      <td>-0.004405</td>\n",
       "      <td>-0.007138</td>\n",
       "      <td>-0.014636</td>\n",
       "      <td>-0.005722</td>\n",
       "      <td>-0.001050</td>\n",
       "      <td>0.003620</td>\n",
       "      <td>0.005043</td>\n",
       "      <td>-0.010962</td>\n",
       "      <td>-0.007624</td>\n",
       "      <td>0.003317</td>\n",
       "      <td>-0.009519</td>\n",
       "      <td>0.014797</td>\n",
       "      <td>0.001631</td>\n",
       "      <td>-0.006191</td>\n",
       "      <td>0.003516</td>\n",
       "      <td>-0.006518</td>\n",
       "      <td>-0.006845</td>\n",
       "      <td>-0.000083</td>\n",
       "      <td>-0.008338</td>\n",
       "      <td>0.691800</td>\n",
       "      <td>0.420889</td>\n",
       "      <td>0.165328</td>\n",
       "      <td>0.290970</td>\n",
       "      <td>0.591837</td>\n",
       "      <td>0.192905</td>\n",
       "      <td>962</td>\n",
       "      <td>364</td>\n",
       "      <td>60</td>\n",
       "      <td>87</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.006609</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1321</td>\n",
       "      <td>5</td>\n",
       "      <td>147</td>\n",
       "      <td>0</td>\n",
       "      <td>0.711</td>\n",
       "      <td>0.260498</td>\n",
       "      <td>0.324324</td>\n",
       "      <td>0.285714</td>\n",
       "      <td>0.375000</td>\n",
       "      <td>1256</td>\n",
       "      <td>70</td>\n",
       "      <td>105</td>\n",
       "      <td>42</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>distance</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>manhattan</td>\n",
       "      <td>34.0</td>\n",
       "      <td>ball_tree</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>SVM</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_3, location_cluster_4, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.733673</td>\n",
       "      <td>1.569873</td>\n",
       "      <td>-0.001199</td>\n",
       "      <td>0.015604</td>\n",
       "      <td>0.018604</td>\n",
       "      <td>0.003563</td>\n",
       "      <td>0.001395</td>\n",
       "      <td>0.002402</td>\n",
       "      <td>0.018609</td>\n",
       "      <td>-0.004595</td>\n",
       "      <td>-0.006662</td>\n",
       "      <td>-0.012240</td>\n",
       "      <td>0.001058</td>\n",
       "      <td>-0.004530</td>\n",
       "      <td>0.007334</td>\n",
       "      <td>0.002078</td>\n",
       "      <td>-0.006070</td>\n",
       "      <td>0.007855</td>\n",
       "      <td>0.000071</td>\n",
       "      <td>0.004620</td>\n",
       "      <td>-0.008469</td>\n",
       "      <td>0.003645</td>\n",
       "      <td>0.014452</td>\n",
       "      <td>0.001736</td>\n",
       "      <td>-0.000464</td>\n",
       "      <td>-0.003549</td>\n",
       "      <td>0.000872</td>\n",
       "      <td>0.002134</td>\n",
       "      <td>0.010454</td>\n",
       "      <td>-0.007480</td>\n",
       "      <td>0.705213</td>\n",
       "      <td>0.438637</td>\n",
       "      <td>0.193545</td>\n",
       "      <td>0.310280</td>\n",
       "      <td>0.564626</td>\n",
       "      <td>0.213918</td>\n",
       "      <td>1021</td>\n",
       "      <td>305</td>\n",
       "      <td>64</td>\n",
       "      <td>83</td>\n",
       "      <td>0.822694</td>\n",
       "      <td>-0.005315</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1322</td>\n",
       "      <td>4</td>\n",
       "      <td>147</td>\n",
       "      <td>0</td>\n",
       "      <td>0.483</td>\n",
       "      <td>0.254733</td>\n",
       "      <td>0.351544</td>\n",
       "      <td>0.503401</td>\n",
       "      <td>0.270073</td>\n",
       "      <td>1126</td>\n",
       "      <td>200</td>\n",
       "      <td>73</td>\n",
       "      <td>74</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.001</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>rbf</td>\n",
       "      <td>0.951</td>\n",
       "      <td>ovo</td>\n",
       "      <td>7.10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>RUSBoostClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_2, location_cluster_3, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>440.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.001998</td>\n",
       "      <td>-0.002393</td>\n",
       "      <td>0.006545</td>\n",
       "      <td>-0.004498</td>\n",
       "      <td>0.014859</td>\n",
       "      <td>-0.004014</td>\n",
       "      <td>0.002751</td>\n",
       "      <td>0.012037</td>\n",
       "      <td>0.012351</td>\n",
       "      <td>-0.023022</td>\n",
       "      <td>-0.001999</td>\n",
       "      <td>-0.007738</td>\n",
       "      <td>-0.001635</td>\n",
       "      <td>0.010244</td>\n",
       "      <td>-0.012628</td>\n",
       "      <td>0.004641</td>\n",
       "      <td>0.000779</td>\n",
       "      <td>-0.012592</td>\n",
       "      <td>0.001569</td>\n",
       "      <td>0.017085</td>\n",
       "      <td>-0.003218</td>\n",
       "      <td>0.016854</td>\n",
       "      <td>0.019282</td>\n",
       "      <td>0.007125</td>\n",
       "      <td>0.009132</td>\n",
       "      <td>-0.016072</td>\n",
       "      <td>-0.009305</td>\n",
       "      <td>0.004852</td>\n",
       "      <td>0.685425</td>\n",
       "      <td>0.517970</td>\n",
       "      <td>0.361692</td>\n",
       "      <td>0.426667</td>\n",
       "      <td>0.435374</td>\n",
       "      <td>0.418301</td>\n",
       "      <td>1237</td>\n",
       "      <td>89</td>\n",
       "      <td>83</td>\n",
       "      <td>64</td>\n",
       "      <td>0.550553</td>\n",
       "      <td>-0.010409</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1318</td>\n",
       "      <td>8</td>\n",
       "      <td>147</td>\n",
       "      <td>0</td>\n",
       "      <td>0.523</td>\n",
       "      <td>0.419146</td>\n",
       "      <td>0.455814</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.720588</td>\n",
       "      <td>1307</td>\n",
       "      <td>19</td>\n",
       "      <td>98</td>\n",
       "      <td>49</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAMME.R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>0.0870</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>AdaBoostClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_3, location_cluster_4, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>485.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.001341</td>\n",
       "      <td>-0.026840</td>\n",
       "      <td>-0.011634</td>\n",
       "      <td>-0.009201</td>\n",
       "      <td>-0.012421</td>\n",
       "      <td>-0.003134</td>\n",
       "      <td>-0.015180</td>\n",
       "      <td>0.007063</td>\n",
       "      <td>0.000298</td>\n",
       "      <td>0.002471</td>\n",
       "      <td>-0.003242</td>\n",
       "      <td>-0.003930</td>\n",
       "      <td>-0.008939</td>\n",
       "      <td>-0.003120</td>\n",
       "      <td>0.000137</td>\n",
       "      <td>-0.013802</td>\n",
       "      <td>-0.001213</td>\n",
       "      <td>-0.006124</td>\n",
       "      <td>-0.004584</td>\n",
       "      <td>-0.020043</td>\n",
       "      <td>-0.007330</td>\n",
       "      <td>0.000059</td>\n",
       "      <td>-0.018264</td>\n",
       "      <td>-0.009128</td>\n",
       "      <td>0.002789</td>\n",
       "      <td>-0.008314</td>\n",
       "      <td>-0.006858</td>\n",
       "      <td>-0.004081</td>\n",
       "      <td>0.732716</td>\n",
       "      <td>0.498068</td>\n",
       "      <td>0.158324</td>\n",
       "      <td>0.293651</td>\n",
       "      <td>0.755102</td>\n",
       "      <td>0.182266</td>\n",
       "      <td>828</td>\n",
       "      <td>498</td>\n",
       "      <td>36</td>\n",
       "      <td>111</td>\n",
       "      <td>0.510328</td>\n",
       "      <td>-0.007889</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1320</td>\n",
       "      <td>6</td>\n",
       "      <td>147</td>\n",
       "      <td>0</td>\n",
       "      <td>0.503</td>\n",
       "      <td>0.351177</td>\n",
       "      <td>0.398268</td>\n",
       "      <td>0.312925</td>\n",
       "      <td>0.547619</td>\n",
       "      <td>1288</td>\n",
       "      <td>38</td>\n",
       "      <td>101</td>\n",
       "      <td>46</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SAMME.R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.4500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>XGBClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_2, location_cluster_3, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.003251</td>\n",
       "      <td>-0.002447</td>\n",
       "      <td>0.001196</td>\n",
       "      <td>0.028808</td>\n",
       "      <td>0.000295</td>\n",
       "      <td>0.004188</td>\n",
       "      <td>0.001824</td>\n",
       "      <td>-0.005687</td>\n",
       "      <td>0.000138</td>\n",
       "      <td>0.062084</td>\n",
       "      <td>-0.010561</td>\n",
       "      <td>0.002644</td>\n",
       "      <td>0.002762</td>\n",
       "      <td>-0.003330</td>\n",
       "      <td>-0.006506</td>\n",
       "      <td>-0.000667</td>\n",
       "      <td>0.003587</td>\n",
       "      <td>0.026742</td>\n",
       "      <td>-0.004655</td>\n",
       "      <td>0.001865</td>\n",
       "      <td>-0.007679</td>\n",
       "      <td>0.018951</td>\n",
       "      <td>-0.002724</td>\n",
       "      <td>0.010269</td>\n",
       "      <td>0.003719</td>\n",
       "      <td>-0.001137</td>\n",
       "      <td>-0.008170</td>\n",
       "      <td>0.004011</td>\n",
       "      <td>0.785271</td>\n",
       "      <td>0.400697</td>\n",
       "      <td>0.249622</td>\n",
       "      <td>0.364501</td>\n",
       "      <td>0.782313</td>\n",
       "      <td>0.237603</td>\n",
       "      <td>957</td>\n",
       "      <td>369</td>\n",
       "      <td>32</td>\n",
       "      <td>115</td>\n",
       "      <td>0.950562</td>\n",
       "      <td>-0.002686</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1324</td>\n",
       "      <td>2</td>\n",
       "      <td>147</td>\n",
       "      <td>0</td>\n",
       "      <td>0.546</td>\n",
       "      <td>0.398056</td>\n",
       "      <td>0.469945</td>\n",
       "      <td>0.585034</td>\n",
       "      <td>0.392694</td>\n",
       "      <td>1193</td>\n",
       "      <td>133</td>\n",
       "      <td>61</td>\n",
       "      <td>86</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.95</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>2.139746</td>\n",
       "      <td>binary:logistic</td>\n",
       "      <td>0.1</td>\n",
       "      <td>auc</td>\n",
       "      <td>0.75</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Mixed</td>\n",
       "      <td>HistGradientBoostingClassifier</td>\n",
       "      <td>is_healthy</td>\n",
       "      <td>[location_cluster_0, location_cluster_2, locat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>78.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.001712</td>\n",
       "      <td>0.003856</td>\n",
       "      <td>-0.006560</td>\n",
       "      <td>0.005334</td>\n",
       "      <td>0.004961</td>\n",
       "      <td>0.000284</td>\n",
       "      <td>0.007719</td>\n",
       "      <td>-0.005659</td>\n",
       "      <td>0.036834</td>\n",
       "      <td>-0.000950</td>\n",
       "      <td>0.026069</td>\n",
       "      <td>-0.009534</td>\n",
       "      <td>-0.004854</td>\n",
       "      <td>0.013433</td>\n",
       "      <td>-0.005779</td>\n",
       "      <td>0.000345</td>\n",
       "      <td>0.011184</td>\n",
       "      <td>0.007203</td>\n",
       "      <td>-0.005174</td>\n",
       "      <td>-0.003246</td>\n",
       "      <td>0.006659</td>\n",
       "      <td>0.002010</td>\n",
       "      <td>-0.000734</td>\n",
       "      <td>-0.004951</td>\n",
       "      <td>0.009014</td>\n",
       "      <td>-0.017360</td>\n",
       "      <td>-0.012958</td>\n",
       "      <td>0.000885</td>\n",
       "      <td>0.800315</td>\n",
       "      <td>0.419454</td>\n",
       "      <td>0.301121</td>\n",
       "      <td>0.404255</td>\n",
       "      <td>0.775510</td>\n",
       "      <td>0.273381</td>\n",
       "      <td>1023</td>\n",
       "      <td>303</td>\n",
       "      <td>33</td>\n",
       "      <td>114</td>\n",
       "      <td>0.999936</td>\n",
       "      <td>-0.004008</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1323</td>\n",
       "      <td>3</td>\n",
       "      <td>147</td>\n",
       "      <td>0</td>\n",
       "      <td>0.584</td>\n",
       "      <td>0.360580</td>\n",
       "      <td>0.429022</td>\n",
       "      <td>0.462585</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>1224</td>\n",
       "      <td>102</td>\n",
       "      <td>79</td>\n",
       "      <td>68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0400</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>roc_auc</td>\n",
       "      <td>475.0</td>\n",
       "      <td>binary_crossentropy</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      species                           model      target  \\\n",
       "0   Deciduous          RandomForestClassifier  is_healthy   \n",
       "1   Deciduous  BalancedRandomForestClassifier  is_healthy   \n",
       "2   Deciduous          DecisionTreeClassifier  is_healthy   \n",
       "3   Deciduous            KNeighborsClassifier  is_healthy   \n",
       "4   Deciduous                             SVM  is_healthy   \n",
       "5   Deciduous              RUSBoostClassifier  is_healthy   \n",
       "6   Deciduous              AdaBoostClassifier  is_healthy   \n",
       "7   Deciduous                   XGBClassifier  is_healthy   \n",
       "8   Deciduous  HistGradientBoostingClassifier  is_healthy   \n",
       "9     Conifer          RandomForestClassifier  is_healthy   \n",
       "10    Conifer  BalancedRandomForestClassifier  is_healthy   \n",
       "11    Conifer          DecisionTreeClassifier  is_healthy   \n",
       "12    Conifer            KNeighborsClassifier  is_healthy   \n",
       "13    Conifer                             SVM  is_healthy   \n",
       "14    Conifer              RUSBoostClassifier  is_healthy   \n",
       "15    Conifer              AdaBoostClassifier  is_healthy   \n",
       "16    Conifer                   XGBClassifier  is_healthy   \n",
       "17    Conifer  HistGradientBoostingClassifier  is_healthy   \n",
       "18      Mixed          RandomForestClassifier  is_healthy   \n",
       "19      Mixed  BalancedRandomForestClassifier  is_healthy   \n",
       "20      Mixed          DecisionTreeClassifier  is_healthy   \n",
       "21      Mixed            KNeighborsClassifier  is_healthy   \n",
       "22      Mixed                             SVM  is_healthy   \n",
       "23      Mixed              RUSBoostClassifier  is_healthy   \n",
       "24      Mixed              AdaBoostClassifier  is_healthy   \n",
       "25      Mixed                   XGBClassifier  is_healthy   \n",
       "26      Mixed  HistGradientBoostingClassifier  is_healthy   \n",
       "\n",
       "                                    relevant_features params.warm_start  \\\n",
       "0   [location_cluster_0, location_cluster_3, locat...             False   \n",
       "1   [location_cluster_0, location_cluster_1, locat...              True   \n",
       "2   [location_cluster_8, location_cluster_9, locat...               NaN   \n",
       "3   [location_cluster_4, location_cluster_5, locat...               NaN   \n",
       "4   [location_cluster_0, location_cluster_1, locat...               NaN   \n",
       "5   [location_cluster_4, location_cluster_5, tree_...               NaN   \n",
       "6   [location_cluster_3, location_cluster_5, locat...               NaN   \n",
       "7   [location_cluster_0, location_cluster_1, locat...               NaN   \n",
       "8   [location_cluster_0, location_cluster_4, locat...               NaN   \n",
       "9   [location_cluster_0, location_cluster_2, locat...             False   \n",
       "10  [location_cluster_1, location_cluster_4, locat...              True   \n",
       "11  [location_cluster_3, location_cluster_4, locat...               NaN   \n",
       "12  [location_cluster_2, location_cluster_3, locat...               NaN   \n",
       "13  [location_cluster_1, location_cluster_4, locat...               NaN   \n",
       "14  [location_cluster_1, location_cluster_4, locat...               NaN   \n",
       "15  [location_cluster_0, location_cluster_1, locat...               NaN   \n",
       "16  [location_cluster_0, location_cluster_2, locat...               NaN   \n",
       "17  [location_cluster_1, location_cluster_2, locat...               NaN   \n",
       "18  [location_cluster_0, location_cluster_4, locat...             False   \n",
       "19  [location_cluster_3, location_cluster_4, locat...              True   \n",
       "20  [location_cluster_5, location_cluster_7, locat...               NaN   \n",
       "21  [location_cluster_0, location_cluster_2, locat...               NaN   \n",
       "22  [location_cluster_3, location_cluster_4, locat...               NaN   \n",
       "23  [location_cluster_2, location_cluster_3, locat...               NaN   \n",
       "24  [location_cluster_3, location_cluster_4, locat...               NaN   \n",
       "25  [location_cluster_2, location_cluster_3, locat...               NaN   \n",
       "26  [location_cluster_0, location_cluster_2, locat...               NaN   \n",
       "\n",
       "    params.random_state  params.n_jobs  params.n_estimators  \\\n",
       "0                2022.0           58.0                160.0   \n",
       "1                2022.0           58.0                224.0   \n",
       "2                2022.0            NaN                  NaN   \n",
       "3                   NaN           58.0                  NaN   \n",
       "4                2022.0            NaN                  NaN   \n",
       "5                2022.0            NaN                440.0   \n",
       "6                2022.0            NaN                350.0   \n",
       "7                   NaN           58.0                485.0   \n",
       "8                2022.0            NaN                  NaN   \n",
       "9                2022.0           58.0                432.0   \n",
       "10               2022.0           58.0                448.0   \n",
       "11               2022.0            NaN                  NaN   \n",
       "12                  NaN           58.0                  NaN   \n",
       "13               2022.0            NaN                  NaN   \n",
       "14               2022.0            NaN                425.0   \n",
       "15               2022.0            NaN                440.0   \n",
       "16                  NaN           58.0                410.0   \n",
       "17               2022.0            NaN                  NaN   \n",
       "18               2022.0           58.0                224.0   \n",
       "19               2022.0           58.0                144.0   \n",
       "20               2022.0            NaN                  NaN   \n",
       "21                  NaN           58.0                  NaN   \n",
       "22               2022.0            NaN                  NaN   \n",
       "23               2022.0            NaN                440.0   \n",
       "24               2022.0            NaN                485.0   \n",
       "25                  NaN           58.0                380.0   \n",
       "26               2022.0            NaN                  NaN   \n",
       "\n",
       "    params.min_samples_split  params.min_samples_leaf params.max_features  \\\n",
       "0                        2.0                      2.0                sqrt   \n",
       "1                        4.0                      2.0                sqrt   \n",
       "2                        2.0                      9.0                sqrt   \n",
       "3                        NaN                      NaN                 NaN   \n",
       "4                        NaN                      NaN                 NaN   \n",
       "5                        NaN                      NaN                 NaN   \n",
       "6                        NaN                      NaN                 NaN   \n",
       "7                        NaN                      NaN                 NaN   \n",
       "8                        NaN                     25.0                 NaN   \n",
       "9                        4.0                      2.0                sqrt   \n",
       "10                       2.0                      2.0                sqrt   \n",
       "11                      20.0                      2.0                sqrt   \n",
       "12                       NaN                      NaN                 NaN   \n",
       "13                       NaN                      NaN                 NaN   \n",
       "14                       NaN                      NaN                 NaN   \n",
       "15                       NaN                      NaN                 NaN   \n",
       "16                       NaN                      NaN                 NaN   \n",
       "17                       NaN                      5.0                 NaN   \n",
       "18                       4.0                      2.0                sqrt   \n",
       "19                       4.0                      2.0                sqrt   \n",
       "20                      28.0                      6.0                log2   \n",
       "21                       NaN                      NaN                 NaN   \n",
       "22                       NaN                      NaN                 NaN   \n",
       "23                       NaN                      NaN                 NaN   \n",
       "24                       NaN                      NaN                 NaN   \n",
       "25                       NaN                      NaN                 NaN   \n",
       "26                       NaN                     13.0                 NaN   \n",
       "\n",
       "    params.max_depth  params.class_weight.0  params.class_weight.1  \\\n",
       "0               32.0               0.728614               1.593548   \n",
       "1              192.0                    NaN                    NaN   \n",
       "2                6.0               0.728614               1.593548   \n",
       "3                NaN                    NaN                    NaN   \n",
       "4                NaN               0.728614               1.593548   \n",
       "5                NaN                    NaN                    NaN   \n",
       "6                NaN                    NaN                    NaN   \n",
       "7                5.0                    NaN                    NaN   \n",
       "8              120.0                    NaN                    NaN   \n",
       "9              192.0               0.708477               1.699173   \n",
       "10             224.0                    NaN                    NaN   \n",
       "11              31.0               0.708477               1.699173   \n",
       "12               NaN                    NaN                    NaN   \n",
       "13               NaN               0.708477               1.699173   \n",
       "14               NaN                    NaN                    NaN   \n",
       "15               NaN                    NaN                    NaN   \n",
       "16               7.0                    NaN                    NaN   \n",
       "17              64.0                    NaN                    NaN   \n",
       "18             240.0               0.733673               1.569873   \n",
       "19             192.0                    NaN                    NaN   \n",
       "20               3.0               0.733673               1.569873   \n",
       "21               NaN                    NaN                    NaN   \n",
       "22               NaN               0.733673               1.569873   \n",
       "23               NaN                    NaN                    NaN   \n",
       "24               NaN                    NaN                    NaN   \n",
       "25               7.0                    NaN                    NaN   \n",
       "26              78.0                    NaN                    NaN   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_0  \\\n",
       "0                                          -0.009623   \n",
       "1                                          -0.010253   \n",
       "2                                           0.001742   \n",
       "3                                           0.005432   \n",
       "4                                           0.012402   \n",
       "5                                           0.014078   \n",
       "6                                           0.018116   \n",
       "7                                          -0.000819   \n",
       "8                                           0.003170   \n",
       "9                                          -0.005334   \n",
       "10                                         -0.007055   \n",
       "11                                          0.000000   \n",
       "12                                         -0.001024   \n",
       "13                                          0.009836   \n",
       "14                                         -0.004158   \n",
       "15                                          0.008131   \n",
       "16                                         -0.009148   \n",
       "17                                          0.004952   \n",
       "18                                         -0.003100   \n",
       "19                                          0.012119   \n",
       "20                                          0.009225   \n",
       "21                                         -0.001631   \n",
       "22                                         -0.001199   \n",
       "23                                          0.001998   \n",
       "24                                          0.001341   \n",
       "25                                          0.003251   \n",
       "26                                         -0.001712   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_1  \\\n",
       "0                                          -0.007627   \n",
       "1                                           0.010497   \n",
       "2                                           0.000000   \n",
       "3                                           0.001893   \n",
       "4                                           0.034887   \n",
       "5                                           0.037537   \n",
       "6                                           0.037088   \n",
       "7                                           0.011509   \n",
       "8                                           0.014441   \n",
       "9                                          -0.012223   \n",
       "10                                          0.007502   \n",
       "11                                         -0.011310   \n",
       "12                                         -0.002132   \n",
       "13                                          0.019159   \n",
       "14                                         -0.000669   \n",
       "15                                         -0.005727   \n",
       "16                                         -0.012580   \n",
       "17                                         -0.002039   \n",
       "18                                          0.001680   \n",
       "19                                          0.041914   \n",
       "20                                         -0.027538   \n",
       "21                                          0.001112   \n",
       "22                                          0.015604   \n",
       "23                                         -0.002393   \n",
       "24                                         -0.026840   \n",
       "25                                         -0.002447   \n",
       "26                                          0.003856   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_2  \\\n",
       "0                                           0.008533   \n",
       "1                                           0.004653   \n",
       "2                                           0.000000   \n",
       "3                                          -0.004555   \n",
       "4                                           0.011077   \n",
       "5                                           0.007360   \n",
       "6                                           0.006209   \n",
       "7                                           0.004160   \n",
       "8                                           0.040797   \n",
       "9                                          -0.000348   \n",
       "10                                          0.000204   \n",
       "11                                          0.000278   \n",
       "12                                         -0.012222   \n",
       "13                                         -0.009174   \n",
       "14                                         -0.004385   \n",
       "15                                          0.004640   \n",
       "16                                         -0.004463   \n",
       "17                                         -0.001278   \n",
       "18                                          0.034502   \n",
       "19                                          0.025683   \n",
       "20                                         -0.015193   \n",
       "21                                          0.005163   \n",
       "22                                          0.018604   \n",
       "23                                          0.006545   \n",
       "24                                         -0.011634   \n",
       "25                                          0.001196   \n",
       "26                                         -0.006560   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_3  \\\n",
       "0                                          -0.007199   \n",
       "1                                           0.029545   \n",
       "2                                           0.000000   \n",
       "3                                          -0.001864   \n",
       "4                                           0.033593   \n",
       "5                                          -0.001523   \n",
       "6                                           0.014031   \n",
       "7                                           0.010624   \n",
       "8                                          -0.000773   \n",
       "9                                           0.016131   \n",
       "10                                         -0.009835   \n",
       "11                                          0.000000   \n",
       "12                                         -0.005263   \n",
       "13                                          0.023366   \n",
       "14                                         -0.006291   \n",
       "15                                          0.000404   \n",
       "16                                         -0.004508   \n",
       "17                                          0.010660   \n",
       "18                                         -0.003416   \n",
       "19                                         -0.004559   \n",
       "20                                         -0.002538   \n",
       "21                                         -0.001539   \n",
       "22                                          0.003563   \n",
       "23                                         -0.004498   \n",
       "24                                         -0.009201   \n",
       "25                                          0.028808   \n",
       "26                                          0.005334   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_4  \\\n",
       "0                                          -0.007663   \n",
       "1                                          -0.010675   \n",
       "2                                           0.000000   \n",
       "3                                          -0.003264   \n",
       "4                                           0.006749   \n",
       "5                                           0.000047   \n",
       "6                                           0.000513   \n",
       "7                                           0.017140   \n",
       "8                                           0.000926   \n",
       "9                                          -0.008569   \n",
       "10                                          0.006992   \n",
       "11                                         -0.003001   \n",
       "12                                         -0.003147   \n",
       "13                                          0.015876   \n",
       "14                                         -0.010338   \n",
       "15                                          0.005330   \n",
       "16                                         -0.002042   \n",
       "17                                         -0.001597   \n",
       "18                                         -0.007307   \n",
       "19                                         -0.008496   \n",
       "20                                          0.032492   \n",
       "21                                          0.001054   \n",
       "22                                          0.001395   \n",
       "23                                          0.014859   \n",
       "24                                         -0.012421   \n",
       "25                                          0.000295   \n",
       "26                                          0.004961   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_5  \\\n",
       "0                                          -0.004926   \n",
       "1                                          -0.005051   \n",
       "2                                           0.000000   \n",
       "3                                          -0.003010   \n",
       "4                                          -0.000796   \n",
       "5                                          -0.004974   \n",
       "6                                          -0.003982   \n",
       "7                                           0.000570   \n",
       "8                                          -0.004550   \n",
       "9                                          -0.003661   \n",
       "10                                          0.005970   \n",
       "11                                         -0.003968   \n",
       "12                                         -0.001781   \n",
       "13                                          0.012591   \n",
       "14                                          0.001144   \n",
       "15                                          0.017965   \n",
       "16                                          0.002383   \n",
       "17                                          0.029173   \n",
       "18                                         -0.001653   \n",
       "19                                         -0.000937   \n",
       "20                                         -0.017350   \n",
       "21                                          0.001725   \n",
       "22                                          0.002402   \n",
       "23                                         -0.004014   \n",
       "24                                         -0.003134   \n",
       "25                                          0.004188   \n",
       "26                                          0.000284   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_6  \\\n",
       "0                                          -0.002634   \n",
       "1                                           0.029605   \n",
       "2                                           0.000000   \n",
       "3                                          -0.002222   \n",
       "4                                           0.005038   \n",
       "5                                           0.011592   \n",
       "6                                          -0.000432   \n",
       "7                                           0.000385   \n",
       "8                                          -0.004454   \n",
       "9                                           0.008769   \n",
       "10                                          0.005560   \n",
       "11                                          0.000000   \n",
       "12                                         -0.000759   \n",
       "13                                         -0.001169   \n",
       "14                                         -0.001198   \n",
       "15                                         -0.003737   \n",
       "16                                         -0.011040   \n",
       "17                                         -0.004411   \n",
       "18                                         -0.001652   \n",
       "19                                          0.011076   \n",
       "20                                          0.010480   \n",
       "21                                          0.000010   \n",
       "22                                          0.018609   \n",
       "23                                          0.002751   \n",
       "24                                         -0.015180   \n",
       "25                                          0.001824   \n",
       "26                                          0.007719   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_7  \\\n",
       "0                                           0.009967   \n",
       "1                                          -0.010120   \n",
       "2                                           0.000000   \n",
       "3                                          -0.002207   \n",
       "4                                           0.002318   \n",
       "5                                          -0.001871   \n",
       "6                                           0.012043   \n",
       "7                                           0.001797   \n",
       "8                                           0.002789   \n",
       "9                                          -0.005302   \n",
       "10                                         -0.012768   \n",
       "11                                          0.002724   \n",
       "12                                          0.000417   \n",
       "13                                          0.009276   \n",
       "14                                         -0.004153   \n",
       "15                                         -0.001709   \n",
       "16                                          0.014338   \n",
       "17                                          0.003750   \n",
       "18                                         -0.004078   \n",
       "19                                         -0.014568   \n",
       "20                                          0.026397   \n",
       "21                                         -0.000801   \n",
       "22                                         -0.004595   \n",
       "23                                          0.012037   \n",
       "24                                          0.007063   \n",
       "25                                         -0.005687   \n",
       "26                                         -0.005659   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_8  \\\n",
       "0                                          -0.008624   \n",
       "1                                           0.016160   \n",
       "2                                           0.000000   \n",
       "3                                           0.001837   \n",
       "4                                           0.004610   \n",
       "5                                           0.007838   \n",
       "6                                           0.004054   \n",
       "7                                           0.002029   \n",
       "8                                           0.001560   \n",
       "9                                           0.011446   \n",
       "10                                          0.006902   \n",
       "11                                         -0.000640   \n",
       "12                                         -0.014405   \n",
       "13                                          0.011726   \n",
       "14                                         -0.010500   \n",
       "15                                          0.001024   \n",
       "16                                         -0.003511   \n",
       "17                                          0.002403   \n",
       "18                                         -0.001076   \n",
       "19                                          0.021403   \n",
       "20                                         -0.009828   \n",
       "21                                          0.023813   \n",
       "22                                         -0.006662   \n",
       "23                                          0.012351   \n",
       "24                                          0.000298   \n",
       "25                                          0.000138   \n",
       "26                                          0.036834   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_9  \\\n",
       "0                                          -0.000128   \n",
       "1                                          -0.000769   \n",
       "2                                           0.000000   \n",
       "3                                           0.001239   \n",
       "4                                           0.016172   \n",
       "5                                          -0.001094   \n",
       "6                                           0.002104   \n",
       "7                                           0.000570   \n",
       "8                                          -0.003742   \n",
       "9                                          -0.013587   \n",
       "10                                          0.010415   \n",
       "11                                         -0.004629   \n",
       "12                                         -0.010001   \n",
       "13                                          0.042705   \n",
       "14                                         -0.005415   \n",
       "15                                         -0.000194   \n",
       "16                                          0.006440   \n",
       "17                                         -0.001107   \n",
       "18                                          0.020222   \n",
       "19                                          0.014761   \n",
       "20                                          0.008493   \n",
       "21                                         -0.004405   \n",
       "22                                         -0.012240   \n",
       "23                                         -0.023022   \n",
       "24                                          0.002471   \n",
       "25                                          0.062084   \n",
       "26                                         -0.000950   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_10  \\\n",
       "0                                            0.000165   \n",
       "1                                           -0.015100   \n",
       "2                                           -0.016219   \n",
       "3                                            0.002009   \n",
       "4                                           -0.001796   \n",
       "5                                           -0.004589   \n",
       "6                                            0.000764   \n",
       "7                                            0.001723   \n",
       "8                                            0.001234   \n",
       "9                                            0.002335   \n",
       "10                                           0.002801   \n",
       "11                                           0.003360   \n",
       "12                                          -0.001928   \n",
       "13                                           0.004469   \n",
       "14                                          -0.004372   \n",
       "15                                           0.008188   \n",
       "16                                          -0.003773   \n",
       "17                                           0.000818   \n",
       "18                                          -0.001336   \n",
       "19                                           0.000678   \n",
       "20                                           0.002710   \n",
       "21                                          -0.007138   \n",
       "22                                           0.001058   \n",
       "23                                          -0.001999   \n",
       "24                                          -0.003242   \n",
       "25                                          -0.010561   \n",
       "26                                           0.026069   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_11  \\\n",
       "0                                           -0.002375   \n",
       "1                                            0.014696   \n",
       "2                                            0.000000   \n",
       "3                                           -0.000226   \n",
       "4                                            0.005044   \n",
       "5                                           -0.000443   \n",
       "6                                            0.000352   \n",
       "7                                            0.003354   \n",
       "8                                           -0.006778   \n",
       "9                                           -0.012694   \n",
       "10                                           0.010132   \n",
       "11                                          -0.002416   \n",
       "12                                          -0.006387   \n",
       "13                                           0.012806   \n",
       "14                                          -0.003787   \n",
       "15                                           0.017694   \n",
       "16                                           0.004782   \n",
       "17                                          -0.005608   \n",
       "18                                           0.010726   \n",
       "19                                           0.021582   \n",
       "20                                           0.000000   \n",
       "21                                          -0.014636   \n",
       "22                                          -0.004530   \n",
       "23                                          -0.007738   \n",
       "24                                          -0.003930   \n",
       "25                                           0.002644   \n",
       "26                                          -0.009534   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_12  \\\n",
       "0                                            0.002788   \n",
       "1                                            0.002013   \n",
       "2                                            0.000000   \n",
       "3                                            0.000714   \n",
       "4                                            0.013049   \n",
       "5                                            0.000569   \n",
       "6                                           -0.001710   \n",
       "7                                            0.002696   \n",
       "8                                           -0.008393   \n",
       "9                                            0.000113   \n",
       "10                                          -0.000902   \n",
       "11                                           0.000000   \n",
       "12                                          -0.004936   \n",
       "13                                           0.005170   \n",
       "14                                          -0.002056   \n",
       "15                                           0.028373   \n",
       "16                                          -0.008708   \n",
       "17                                           0.001399   \n",
       "18                                          -0.000136   \n",
       "19                                           0.041499   \n",
       "20                                          -0.003883   \n",
       "21                                          -0.005722   \n",
       "22                                           0.007334   \n",
       "23                                          -0.001635   \n",
       "24                                          -0.008939   \n",
       "25                                           0.002762   \n",
       "26                                          -0.004854   \n",
       "\n",
       "    feature_permutaion_importance.location_cluster_13  \\\n",
       "0                                           -0.004263   \n",
       "1                                           -0.004992   \n",
       "2                                            0.000000   \n",
       "3                                           -0.000231   \n",
       "4                                            0.007353   \n",
       "5                                            0.009953   \n",
       "6                                            0.009771   \n",
       "7                                            0.000873   \n",
       "8                                            0.001308   \n",
       "9                                           -0.003891   \n",
       "10                                           0.004740   \n",
       "11                                           0.011971   \n",
       "12                                          -0.012951   \n",
       "13                                           0.019353   \n",
       "14                                          -0.007383   \n",
       "15                                           0.005340   \n",
       "16                                           0.001294   \n",
       "17                                          -0.003725   \n",
       "18                                          -0.004826   \n",
       "19                                           0.005514   \n",
       "20                                           0.000000   \n",
       "21                                          -0.001050   \n",
       "22                                           0.002078   \n",
       "23                                           0.010244   \n",
       "24                                          -0.003120   \n",
       "25                                          -0.003330   \n",
       "26                                           0.013433   \n",
       "\n",
       "    feature_permutaion_importance.tree_1  feature_permutaion_importance.evi2  \\\n",
       "0                              -0.003967                           -0.005509   \n",
       "1                               0.005815                            0.001291   \n",
       "2                               0.000000                           -0.011919   \n",
       "3                              -0.001834                            0.000769   \n",
       "4                               0.002930                            0.001417   \n",
       "5                              -0.004732                           -0.003094   \n",
       "6                               0.008974                            0.000826   \n",
       "7                               0.004209                            0.006256   \n",
       "8                              -0.002052                           -0.001852   \n",
       "9                              -0.014547                           -0.002047   \n",
       "10                              0.000729                            0.007236   \n",
       "11                             -0.006722                            0.007502   \n",
       "12                             -0.015707                           -0.009835   \n",
       "13                              0.037936                            0.009005   \n",
       "14                             -0.002537                           -0.010505   \n",
       "15                             -0.005204                           -0.002049   \n",
       "16                             -0.002539                            0.003123   \n",
       "17                              0.004231                           -0.011548   \n",
       "18                              0.012742                           -0.004046   \n",
       "19                              0.001439                           -0.002793   \n",
       "20                              0.007883                            0.000380   \n",
       "21                              0.003620                            0.005043   \n",
       "22                             -0.006070                            0.007855   \n",
       "23                             -0.012628                            0.004641   \n",
       "24                              0.000137                           -0.013802   \n",
       "25                             -0.006506                           -0.000667   \n",
       "26                             -0.005779                            0.000345   \n",
       "\n",
       "    feature_permutaion_importance.evi2-1  \\\n",
       "0                              -0.005954   \n",
       "1                               0.001557   \n",
       "2                               0.000000   \n",
       "3                               0.001691   \n",
       "4                               0.005484   \n",
       "5                               0.020105   \n",
       "6                               0.014866   \n",
       "7                              -0.000820   \n",
       "8                               0.009396   \n",
       "9                              -0.017787   \n",
       "10                              0.015471   \n",
       "11                             -0.002745   \n",
       "12                             -0.007052   \n",
       "13                              0.031622   \n",
       "14                             -0.002798   \n",
       "15                              0.001077   \n",
       "16                              0.008655   \n",
       "17                              0.011381   \n",
       "18                             -0.003226   \n",
       "19                              0.007609   \n",
       "20                              0.007173   \n",
       "21                             -0.010962   \n",
       "22                              0.000071   \n",
       "23                              0.000779   \n",
       "24                             -0.001213   \n",
       "25                              0.003587   \n",
       "26                              0.011184   \n",
       "\n",
       "    feature_permutaion_importance.evi2_diff  \\\n",
       "0                                 -0.001174   \n",
       "1                                  0.001105   \n",
       "2                                 -0.015103   \n",
       "3                                  0.004495   \n",
       "4                                  0.003188   \n",
       "5                                 -0.000750   \n",
       "6                                 -0.007647   \n",
       "7                                  0.009846   \n",
       "8                                 -0.006035   \n",
       "9                                 -0.002699   \n",
       "10                                 0.012705   \n",
       "11                                 0.001613   \n",
       "12                                -0.019037   \n",
       "13                                 0.006200   \n",
       "14                                -0.007649   \n",
       "15                                -0.001032   \n",
       "16                                -0.002338   \n",
       "17                                 0.002610   \n",
       "18                                 0.006845   \n",
       "19                                 0.025472   \n",
       "20                                -0.003815   \n",
       "21                                -0.007624   \n",
       "22                                 0.004620   \n",
       "23                                -0.012592   \n",
       "24                                -0.006124   \n",
       "25                                 0.026742   \n",
       "26                                 0.007203   \n",
       "\n",
       "    feature_permutaion_importance.evi2_max_diff  \\\n",
       "0                                      0.003391   \n",
       "1                                      0.012319   \n",
       "2                                      0.000000   \n",
       "3                                     -0.000563   \n",
       "4                                      0.003458   \n",
       "5                                     -0.004825   \n",
       "6                                      0.014754   \n",
       "7                                      0.007644   \n",
       "8                                     -0.000919   \n",
       "9                                     -0.016218   \n",
       "10                                    -0.000464   \n",
       "11                                     0.000248   \n",
       "12                                    -0.002020   \n",
       "13                                     0.012891   \n",
       "14                                     0.000812   \n",
       "15                                     0.012903   \n",
       "16                                     0.001120   \n",
       "17                                    -0.000578   \n",
       "18                                     0.000192   \n",
       "19                                     0.004774   \n",
       "20                                     0.013718   \n",
       "21                                     0.003317   \n",
       "22                                    -0.008469   \n",
       "23                                     0.001569   \n",
       "24                                    -0.004584   \n",
       "25                                    -0.004655   \n",
       "26                                    -0.005174   \n",
       "\n",
       "    feature_permutaion_importance.evi2_raster  \\\n",
       "0                                    0.007321   \n",
       "1                                    0.022568   \n",
       "2                                    0.000000   \n",
       "3                                    0.011778   \n",
       "4                                    0.012180   \n",
       "5                                    0.001393   \n",
       "6                                    0.000311   \n",
       "7                                    0.015346   \n",
       "8                                    0.000380   \n",
       "9                                   -0.000804   \n",
       "10                                   0.000429   \n",
       "11                                   0.003632   \n",
       "12                                  -0.010866   \n",
       "13                                   0.011837   \n",
       "14                                   0.011015   \n",
       "15                                  -0.004375   \n",
       "16                                  -0.000850   \n",
       "17                                   0.004305   \n",
       "18                                  -0.010574   \n",
       "19                                   0.035429   \n",
       "20                                   0.007517   \n",
       "21                                  -0.009519   \n",
       "22                                   0.003645   \n",
       "23                                   0.017085   \n",
       "24                                  -0.020043   \n",
       "25                                   0.001865   \n",
       "26                                  -0.003246   \n",
       "\n",
       "    feature_permutaion_importance.evi2_raster-1  \\\n",
       "0                                      0.001498   \n",
       "1                                      0.006764   \n",
       "2                                      0.000000   \n",
       "3                                      0.004007   \n",
       "4                                      0.000766   \n",
       "5                                      0.009503   \n",
       "6                                      0.031377   \n",
       "7                                      0.003461   \n",
       "8                                      0.003760   \n",
       "9                                     -0.005617   \n",
       "10                                     0.014182   \n",
       "11                                     0.012929   \n",
       "12                                    -0.005781   \n",
       "13                                     0.023127   \n",
       "14                                     0.015369   \n",
       "15                                     0.000384   \n",
       "16                                    -0.005885   \n",
       "17                                     0.043426   \n",
       "18                                     0.002477   \n",
       "19                                     0.013205   \n",
       "20                                    -0.005724   \n",
       "21                                     0.014797   \n",
       "22                                     0.014452   \n",
       "23                                    -0.003218   \n",
       "24                                    -0.007330   \n",
       "25                                    -0.007679   \n",
       "26                                     0.006659   \n",
       "\n",
       "    feature_permutaion_importance.evi2_raster_diff  \\\n",
       "0                                        -0.006466   \n",
       "1                                         0.002972   \n",
       "2                                         0.000000   \n",
       "3                                        -0.003161   \n",
       "4                                         0.003485   \n",
       "5                                         0.000383   \n",
       "6                                         0.018623   \n",
       "7                                         0.007660   \n",
       "8                                        -0.005909   \n",
       "9                                         0.003914   \n",
       "10                                        0.024113   \n",
       "11                                        0.000000   \n",
       "12                                       -0.012416   \n",
       "13                                        0.043149   \n",
       "14                                       -0.002685   \n",
       "15                                        0.000694   \n",
       "16                                        0.002175   \n",
       "17                                        0.002570   \n",
       "18                                       -0.001851   \n",
       "19                                        0.008932   \n",
       "20                                       -0.000491   \n",
       "21                                        0.001631   \n",
       "22                                        0.001736   \n",
       "23                                        0.016854   \n",
       "24                                        0.000059   \n",
       "25                                        0.018951   \n",
       "26                                        0.002010   \n",
       "\n",
       "    feature_permutaion_importance.evi2_vegetation_raster  \\\n",
       "0                                           -0.004845      \n",
       "1                                           -0.005225      \n",
       "2                                           -0.006035      \n",
       "3                                            0.003965      \n",
       "4                                            0.020210      \n",
       "5                                            0.018092      \n",
       "6                                            0.001073      \n",
       "7                                            0.002754      \n",
       "8                                           -0.003948      \n",
       "9                                            0.003962      \n",
       "10                                           0.008706      \n",
       "11                                          -0.000670      \n",
       "12                                          -0.014962      \n",
       "13                                           0.025528      \n",
       "14                                           0.007332      \n",
       "15                                           0.010010      \n",
       "16                                          -0.005007      \n",
       "17                                          -0.001512      \n",
       "18                                           0.001723      \n",
       "19                                           0.011743      \n",
       "20                                           0.010981      \n",
       "21                                          -0.006191      \n",
       "22                                          -0.000464      \n",
       "23                                           0.019282      \n",
       "24                                          -0.018264      \n",
       "25                                          -0.002724      \n",
       "26                                          -0.000734      \n",
       "\n",
       "    feature_permutaion_importance.evi2_vegetation_raster-1  \\\n",
       "0                                            0.011868        \n",
       "1                                            0.010537        \n",
       "2                                            0.000000        \n",
       "3                                            0.008486        \n",
       "4                                            0.009306        \n",
       "5                                           -0.013455        \n",
       "6                                            0.007597        \n",
       "7                                            0.006217        \n",
       "8                                            0.005468        \n",
       "9                                            0.003577        \n",
       "10                                           0.006652        \n",
       "11                                           0.028260        \n",
       "12                                          -0.000152        \n",
       "13                                           0.003766        \n",
       "14                                          -0.006928        \n",
       "15                                          -0.013112        \n",
       "16                                           0.033393        \n",
       "17                                          -0.007779        \n",
       "18                                          -0.002634        \n",
       "19                                           0.049686        \n",
       "20                                           0.011515        \n",
       "21                                           0.003516        \n",
       "22                                          -0.003549        \n",
       "23                                           0.007125        \n",
       "24                                          -0.009128        \n",
       "25                                           0.010269        \n",
       "26                                          -0.004951        \n",
       "\n",
       "    feature_permutaion_importance.evi2_vegetation_raster_diff  \\\n",
       "0                                           -0.013125           \n",
       "1                                           -0.008534           \n",
       "2                                            0.000000           \n",
       "3                                           -0.002563           \n",
       "4                                            0.007000           \n",
       "5                                           -0.006951           \n",
       "6                                            0.009525           \n",
       "7                                            0.004338           \n",
       "8                                            0.000634           \n",
       "9                                            0.012375           \n",
       "10                                           0.003237           \n",
       "11                                           0.014941           \n",
       "12                                          -0.014405           \n",
       "13                                           0.024912           \n",
       "14                                           0.004222           \n",
       "15                                           0.011424           \n",
       "16                                          -0.005767           \n",
       "17                                           0.003083           \n",
       "18                                          -0.010502           \n",
       "19                                          -0.001364           \n",
       "20                                           0.001286           \n",
       "21                                          -0.006518           \n",
       "22                                           0.000872           \n",
       "23                                           0.009132           \n",
       "24                                           0.002789           \n",
       "25                                           0.003719           \n",
       "26                                           0.009014           \n",
       "\n",
       "    feature_permutaion_importance.ndvi  feature_permutaion_importance.ndvi-1  \\\n",
       "0                            -0.002672                             -0.003207   \n",
       "1                            -0.007698                              0.018076   \n",
       "2                             0.000000                             -0.007150   \n",
       "3                             0.000043                              0.003666   \n",
       "4                             0.005620                              0.015632   \n",
       "5                            -0.002193                              0.023288   \n",
       "6                            -0.006595                              0.011596   \n",
       "7                             0.001396                              0.004489   \n",
       "8                            -0.005135                             -0.003448   \n",
       "9                             0.000383                             -0.002875   \n",
       "10                            0.013587                              0.002303   \n",
       "11                            0.005240                              0.041562   \n",
       "12                           -0.005424                             -0.010672   \n",
       "13                            0.012259                              0.003196   \n",
       "14                            0.003831                             -0.009872   \n",
       "15                            0.001052                              0.016180   \n",
       "16                            0.000018                             -0.005524   \n",
       "17                           -0.003248                              0.018239   \n",
       "18                           -0.004168                              0.000849   \n",
       "19                            0.053682                              0.024517   \n",
       "20                            0.013351                             -0.004969   \n",
       "21                           -0.006845                             -0.000083   \n",
       "22                            0.002134                              0.010454   \n",
       "23                           -0.016072                             -0.009305   \n",
       "24                           -0.008314                             -0.006858   \n",
       "25                           -0.001137                             -0.008170   \n",
       "26                           -0.017360                             -0.012958   \n",
       "\n",
       "    feature_permutaion_importance.ndvi_diff  metrics.auc  \\\n",
       "0                                  0.001084     0.641390   \n",
       "1                                  0.020837     0.674024   \n",
       "2                                  0.000000     0.464674   \n",
       "3                                 -0.002881     0.551455   \n",
       "4                                  0.008043     0.678191   \n",
       "5                                  0.000946     0.711756   \n",
       "6                                  0.000348     0.732870   \n",
       "7                                  0.005575     0.720693   \n",
       "8                                 -0.003040     0.717890   \n",
       "9                                 -0.000148     0.749343   \n",
       "10                                -0.004371     0.722115   \n",
       "11                                 0.017070     0.636317   \n",
       "12                                -0.004008     0.706515   \n",
       "13                                 0.015633     0.713136   \n",
       "14                                -0.001132     0.725069   \n",
       "15                                 0.024779     0.692472   \n",
       "16                                 0.000569     0.733764   \n",
       "17                                 0.001785     0.755642   \n",
       "18                                -0.003656     0.729471   \n",
       "19                                 0.018583     0.706064   \n",
       "20                                 0.016454     0.617832   \n",
       "21                                -0.008338     0.691800   \n",
       "22                                -0.007480     0.705213   \n",
       "23                                 0.004852     0.685425   \n",
       "24                                -0.004081     0.732716   \n",
       "25                                 0.004011     0.785271   \n",
       "26                                 0.000885     0.800315   \n",
       "\n",
       "    metrics.roc.threshold  metrics.roc.cohen_kappa  metrics.roc.f1  \\\n",
       "0                0.378521                 0.129621        0.295129   \n",
       "1                0.533274                 0.172253        0.320721   \n",
       "2                0.528543                 0.004576        0.188312   \n",
       "3                0.204477                 0.078088        0.259615   \n",
       "4                0.314825                 0.138927        0.295918   \n",
       "5                0.486876                 0.165773        0.320635   \n",
       "6                0.494553                 0.208683        0.348485   \n",
       "7                0.363225                 0.209951        0.346232   \n",
       "8                0.354555                 0.218823        0.347826   \n",
       "9                0.513832                 0.369009        0.460292   \n",
       "10               0.623499                 0.330298        0.434269   \n",
       "11               0.517291                 0.113169        0.294498   \n",
       "12               0.372403                 0.190979        0.351687   \n",
       "13               0.390597                 0.221698        0.364629   \n",
       "14               0.503334                 0.201413        0.354105   \n",
       "15               0.499732                 0.212807        0.354023   \n",
       "16               0.550839                 0.263806        0.391089   \n",
       "17               0.226930                 0.197024        0.357268   \n",
       "18               0.437365                 0.198772        0.322581   \n",
       "19               0.592515                 0.136929        0.271787   \n",
       "20               0.549839                 0.066691        0.224742   \n",
       "21               0.420889                 0.165328        0.290970   \n",
       "22               0.438637                 0.193545        0.310280   \n",
       "23               0.517970                 0.361692        0.426667   \n",
       "24               0.498068                 0.158324        0.293651   \n",
       "25               0.400697                 0.249622        0.364501   \n",
       "26               0.419454                 0.301121        0.404255   \n",
       "\n",
       "    metrics.roc.recall  metrics.roc.precision  metrics.roc.tn  metrics.roc.fp  \\\n",
       "0             0.817460               0.180070             491             469   \n",
       "1             0.706349               0.207459             620             340   \n",
       "2             0.460317               0.118367             528             432   \n",
       "3             0.857143               0.152975             362             598   \n",
       "4             0.690476               0.188312             585             375   \n",
       "5             0.801587               0.200397             557             403   \n",
       "6             0.730159               0.228856             650             310   \n",
       "7             0.674603               0.232877             680             280   \n",
       "8             0.603175               0.244373             725             235   \n",
       "9             0.508961               0.420118            1638             196   \n",
       "10            0.526882               0.369347            1583             251   \n",
       "11            0.652330               0.190178            1059             775   \n",
       "12            0.709677               0.233766            1185             649   \n",
       "13            0.598566               0.262166            1364             470   \n",
       "14            0.641577               0.244536            1281             553   \n",
       "15            0.551971               0.260575            1397             437   \n",
       "16            0.566308               0.298677            1463             371   \n",
       "17            0.731183               0.236385            1175             659   \n",
       "18            0.714286               0.208333             927             399   \n",
       "19            0.625850               0.173585             888             438   \n",
       "20            0.741497               0.132442             612             714   \n",
       "21            0.591837               0.192905             962             364   \n",
       "22            0.564626               0.213918            1021             305   \n",
       "23            0.435374               0.418301            1237              89   \n",
       "24            0.755102               0.182266             828             498   \n",
       "25            0.782313               0.237603             957             369   \n",
       "26            0.775510               0.273381            1023             303   \n",
       "\n",
       "    metrics.roc.fn  metrics.roc.tp  metrics.prc.threshold  \\\n",
       "0               23             103               0.378521   \n",
       "1               37              89               0.533274   \n",
       "2               68              58               0.453294   \n",
       "3               18             108               0.667871   \n",
       "4               39              87               0.392481   \n",
       "5               25             101               0.560297   \n",
       "6               34              92               0.496340   \n",
       "7               41              85               0.363225   \n",
       "8               50              76               0.366990   \n",
       "9              137             142               0.549672   \n",
       "10             132             147               0.669772   \n",
       "11              97             182               0.572528   \n",
       "12              81             198               0.843738   \n",
       "13             112             167               0.528404   \n",
       "14             100             179               0.518682   \n",
       "15             125             154               0.502236   \n",
       "16             121             158               0.665856   \n",
       "17              75             204               0.636827   \n",
       "18              42             105               0.928224   \n",
       "19              55              92               0.938072   \n",
       "20              38             109               0.831871   \n",
       "21              60              87               1.000000   \n",
       "22              64              83               0.822694   \n",
       "23              83              64               0.550553   \n",
       "24              36             111               0.510328   \n",
       "25              32             115               0.950562   \n",
       "26              33             114               0.999936   \n",
       "\n",
       "    metrics.prc.cohen_kappa  metrics.prc.f1  metrics.prc.recall  \\\n",
       "0                  0.129621        0.295129            0.817460   \n",
       "1                  0.172253        0.320721            0.706349   \n",
       "2                  0.031864        0.227273            0.873016   \n",
       "3                 -0.014048        0.000000            0.000000   \n",
       "4                  0.183955        0.310526            0.468254   \n",
       "5                 -0.007191        0.000000            0.000000   \n",
       "6                  0.231447        0.355769            0.587302   \n",
       "7                  0.209951        0.346232            0.674603   \n",
       "8                  0.229222        0.353511            0.579365   \n",
       "9                  0.428086        0.495010            0.444444   \n",
       "10                 0.448559        0.502262            0.397849   \n",
       "11                 0.152982        0.295720            0.408602   \n",
       "12                -0.006506        0.000000            0.000000   \n",
       "13                 0.343055        0.421260            0.383513   \n",
       "14                 0.319594        0.400786            0.365591   \n",
       "15                 0.321829        0.402367            0.365591   \n",
       "16                 0.392674        0.455142            0.372760   \n",
       "17                 0.396947        0.466801            0.415771   \n",
       "18                -0.004008        0.000000            0.000000   \n",
       "19                -0.004008        0.000000            0.000000   \n",
       "20                -0.004008        0.000000            0.000000   \n",
       "21                -0.006609        0.000000            0.000000   \n",
       "22                -0.005315        0.000000            0.000000   \n",
       "23                -0.010409        0.000000            0.000000   \n",
       "24                -0.007889        0.000000            0.000000   \n",
       "25                -0.002686        0.000000            0.000000   \n",
       "26                -0.004008        0.000000            0.000000   \n",
       "\n",
       "    metrics.prc.precision  metrics.prc.tn  metrics.prc.fp  metrics.prc.fn  \\\n",
       "0                0.180070             491             469              23   \n",
       "1                0.207459             620             340              37   \n",
       "2                0.130641             228             732              16   \n",
       "3                0.000000             952               8             126   \n",
       "4                0.232283             765             195              67   \n",
       "5                0.000000             956               4             126   \n",
       "6                0.255172             744             216              52   \n",
       "7                0.232877             680             280              41   \n",
       "8                0.254355             746             214              53   \n",
       "9                0.558559            1736              98             155   \n",
       "10               0.680982            1782              52             168   \n",
       "11               0.231707            1456             378             165   \n",
       "12               0.000000            1827               7             279   \n",
       "13               0.467249            1712             122             172   \n",
       "14               0.443478            1706             128             177   \n",
       "15               0.447368            1708             126             177   \n",
       "16               0.584270            1760              74             175   \n",
       "17               0.532110            1732             102             163   \n",
       "18               0.000000            1323               3             147   \n",
       "19               0.000000            1323               3             147   \n",
       "20               0.000000            1323               3             147   \n",
       "21               0.000000            1321               5             147   \n",
       "22               0.000000            1322               4             147   \n",
       "23               0.000000            1318               8             147   \n",
       "24               0.000000            1320               6             147   \n",
       "25               0.000000            1324               2             147   \n",
       "26               0.000000            1323               3             147   \n",
       "\n",
       "    metrics.prc.tp  metrics.tuning.threshold  metrics.tuning.cohen_kappa  \\\n",
       "0              103                     0.378                    0.127868   \n",
       "1               89                     0.533                    0.172253   \n",
       "2              110                     0.453                    0.031864   \n",
       "3                0                     0.197                    0.077044   \n",
       "4               59                     0.386                    0.179597   \n",
       "5                0                     0.505                    0.236344   \n",
       "6               74                     0.497                    0.228367   \n",
       "7               85                     0.363                    0.209951   \n",
       "8               73                     0.366                    0.229222   \n",
       "9              124                     0.551                    0.426177   \n",
       "10             111                     0.669                    0.442646   \n",
       "11             114                     0.572                    0.152396   \n",
       "12               0                     0.384                    0.198282   \n",
       "13             107                     0.535                    0.343203   \n",
       "14             102                     0.518                    0.306666   \n",
       "15             102                     0.502                    0.298169   \n",
       "16             104                     0.653                    0.384579   \n",
       "17             116                     0.636                    0.396947   \n",
       "18               0                     0.565                    0.289882   \n",
       "19               0                     0.740                    0.430895   \n",
       "20               0                     0.728                    0.221145   \n",
       "21               0                     0.711                    0.260498   \n",
       "22               0                     0.483                    0.254733   \n",
       "23               0                     0.523                    0.419146   \n",
       "24               0                     0.503                    0.351177   \n",
       "25               0                     0.546                    0.398056   \n",
       "26               0                     0.584                    0.360580   \n",
       "\n",
       "    metrics.tuning.f1  metrics.tuning.recall  metrics.tuning.precision  \\\n",
       "0            0.293866               0.817460                  0.179130   \n",
       "1            0.320721               0.706349                  0.207459   \n",
       "2            0.227273               0.873016                  0.130641   \n",
       "3            0.259649               0.880952                  0.152263   \n",
       "4            0.310000               0.492063                  0.226277   \n",
       "5            0.349570               0.484127                  0.273543   \n",
       "6            0.350877               0.555556                  0.256410   \n",
       "7            0.346232               0.674603                  0.232877   \n",
       "8            0.353511               0.579365                  0.254355   \n",
       "9            0.492986               0.440860                  0.559091   \n",
       "10           0.497758               0.397849                  0.664671   \n",
       "11           0.295337               0.408602                  0.231237   \n",
       "12           0.352483               0.648746                  0.241979   \n",
       "13           0.420635               0.379928                  0.471111   \n",
       "14           0.393195               0.372760                  0.416000   \n",
       "15           0.386492               0.369176                  0.405512   \n",
       "16           0.453608               0.394265                  0.533981   \n",
       "17           0.466801               0.415771                  0.532110   \n",
       "18           0.375000               0.469388                  0.312217   \n",
       "19           0.467890               0.346939                  0.718310   \n",
       "20           0.272727               0.204082                  0.410959   \n",
       "21           0.324324               0.285714                  0.375000   \n",
       "22           0.351544               0.503401                  0.270073   \n",
       "23           0.455814               0.333333                  0.720588   \n",
       "24           0.398268               0.312925                  0.547619   \n",
       "25           0.469945               0.585034                  0.392694   \n",
       "26           0.429022               0.462585                  0.400000   \n",
       "\n",
       "    metrics.tuning.tn  metrics.tuning.fp  metrics.tuning.fn  \\\n",
       "0                 488                472                 23   \n",
       "1                 620                340                 37   \n",
       "2                 228                732                 16   \n",
       "3                 342                618                 15   \n",
       "4                 748                212                 64   \n",
       "5                 798                162                 65   \n",
       "6                 757                203                 56   \n",
       "7                 680                280                 41   \n",
       "8                 746                214                 53   \n",
       "9                1737                 97                156   \n",
       "10               1778                 56                168   \n",
       "11               1455                379                165   \n",
       "12               1267                567                 98   \n",
       "13               1715                119                173   \n",
       "14               1688                146                175   \n",
       "15               1683                151                176   \n",
       "16               1738                 96                169   \n",
       "17               1732                102                163   \n",
       "18               1174                152                 78   \n",
       "19               1306                 20                 96   \n",
       "20               1283                 43                117   \n",
       "21               1256                 70                105   \n",
       "22               1126                200                 73   \n",
       "23               1307                 19                 98   \n",
       "24               1288                 38                101   \n",
       "25               1193                133                 61   \n",
       "26               1224                102                 79   \n",
       "\n",
       "    metrics.tuning.tp params.splitter  params.min_weight_fraction_leaf  \\\n",
       "0                 103             NaN                              NaN   \n",
       "1                  89             NaN                              NaN   \n",
       "2                 110            best                             0.40   \n",
       "3                 111             NaN                              NaN   \n",
       "4                  62             NaN                              NaN   \n",
       "5                  61             NaN                              NaN   \n",
       "6                  70             NaN                              NaN   \n",
       "7                  85             NaN                              NaN   \n",
       "8                  73             NaN                              NaN   \n",
       "9                 123             NaN                              NaN   \n",
       "10                111             NaN                              NaN   \n",
       "11                114          random                             0.10   \n",
       "12                181             NaN                              NaN   \n",
       "13                106             NaN                              NaN   \n",
       "14                104             NaN                              NaN   \n",
       "15                103             NaN                              NaN   \n",
       "16                110             NaN                              NaN   \n",
       "17                116             NaN                              NaN   \n",
       "18                 69             NaN                              NaN   \n",
       "19                 51             NaN                              NaN   \n",
       "20                 30            best                             0.05   \n",
       "21                 42             NaN                              NaN   \n",
       "22                 74             NaN                              NaN   \n",
       "23                 49             NaN                              NaN   \n",
       "24                 46             NaN                              NaN   \n",
       "25                 86             NaN                              NaN   \n",
       "26                 68             NaN                              NaN   \n",
       "\n",
       "    params.min_impurity_decrease  params.max_leaf_nodes params.criterion  \\\n",
       "0                            NaN                    NaN              NaN   \n",
       "1                            NaN                    NaN              NaN   \n",
       "2                           0.05                 1217.0          entropy   \n",
       "3                            NaN                    NaN              NaN   \n",
       "4                            NaN                    NaN              NaN   \n",
       "5                            NaN                    NaN              NaN   \n",
       "6                            NaN                    NaN              NaN   \n",
       "7                            NaN                    NaN              NaN   \n",
       "8                            NaN                   36.0              NaN   \n",
       "9                            NaN                    NaN              NaN   \n",
       "10                           NaN                    NaN              NaN   \n",
       "11                          0.00                 1473.0          entropy   \n",
       "12                           NaN                    NaN              NaN   \n",
       "13                           NaN                    NaN              NaN   \n",
       "14                           NaN                    NaN              NaN   \n",
       "15                           NaN                    NaN              NaN   \n",
       "16                           NaN                    NaN              NaN   \n",
       "17                           NaN                   36.0              NaN   \n",
       "18                           NaN                    NaN              NaN   \n",
       "19                           NaN                    NaN              NaN   \n",
       "20                          0.00                  513.0          entropy   \n",
       "21                           NaN                    NaN              NaN   \n",
       "22                           NaN                    NaN              NaN   \n",
       "23                           NaN                    NaN              NaN   \n",
       "24                           NaN                    NaN              NaN   \n",
       "25                           NaN                    NaN              NaN   \n",
       "26                           NaN                   43.0              NaN   \n",
       "\n",
       "    params.ccp_alpha params.weights  params.p  params.n_neighbors  \\\n",
       "0                NaN            NaN       NaN                 NaN   \n",
       "1                NaN            NaN       NaN                 NaN   \n",
       "2                0.0            NaN       NaN                 NaN   \n",
       "3                NaN       distance       1.0                16.0   \n",
       "4                NaN            NaN       NaN                 NaN   \n",
       "5                NaN            NaN       NaN                 NaN   \n",
       "6                NaN            NaN       NaN                 NaN   \n",
       "7                NaN            NaN       NaN                 NaN   \n",
       "8                NaN            NaN       NaN                 NaN   \n",
       "9                NaN            NaN       NaN                 NaN   \n",
       "10               NaN            NaN       NaN                 NaN   \n",
       "11               0.0            NaN       NaN                 NaN   \n",
       "12               NaN       distance       1.0                10.0   \n",
       "13               NaN            NaN       NaN                 NaN   \n",
       "14               NaN            NaN       NaN                 NaN   \n",
       "15               NaN            NaN       NaN                 NaN   \n",
       "16               NaN            NaN       NaN                 NaN   \n",
       "17               NaN            NaN       NaN                 NaN   \n",
       "18               NaN            NaN       NaN                 NaN   \n",
       "19               NaN            NaN       NaN                 NaN   \n",
       "20               0.0            NaN       NaN                 NaN   \n",
       "21               NaN       distance       2.0                 3.0   \n",
       "22               NaN            NaN       NaN                 NaN   \n",
       "23               NaN            NaN       NaN                 NaN   \n",
       "24               NaN            NaN       NaN                 NaN   \n",
       "25               NaN            NaN       NaN                 NaN   \n",
       "26               NaN            NaN       NaN                 NaN   \n",
       "\n",
       "   params.metric  params.leaf_size params.algorithm  params.tol  \\\n",
       "0            NaN               NaN              NaN         NaN   \n",
       "1            NaN               NaN              NaN         NaN   \n",
       "2            NaN               NaN              NaN         NaN   \n",
       "3      minkowski              44.0          kd_tree         NaN   \n",
       "4            NaN               NaN              NaN       0.003   \n",
       "5            NaN               NaN          SAMME.R         NaN   \n",
       "6            NaN               NaN          SAMME.R         NaN   \n",
       "7            NaN               NaN              NaN         NaN   \n",
       "8            NaN               NaN              NaN         NaN   \n",
       "9            NaN               NaN              NaN         NaN   \n",
       "10           NaN               NaN              NaN         NaN   \n",
       "11           NaN               NaN              NaN         NaN   \n",
       "12     minkowski              24.0        ball_tree         NaN   \n",
       "13           NaN               NaN              NaN       0.002   \n",
       "14           NaN               NaN          SAMME.R         NaN   \n",
       "15           NaN               NaN          SAMME.R         NaN   \n",
       "16           NaN               NaN              NaN         NaN   \n",
       "17           NaN               NaN              NaN         NaN   \n",
       "18           NaN               NaN              NaN         NaN   \n",
       "19           NaN               NaN              NaN         NaN   \n",
       "20           NaN               NaN              NaN         NaN   \n",
       "21     manhattan              34.0        ball_tree         NaN   \n",
       "22           NaN               NaN              NaN       0.001   \n",
       "23           NaN               NaN          SAMME.R         NaN   \n",
       "24           NaN               NaN          SAMME.R         NaN   \n",
       "25           NaN               NaN              NaN         NaN   \n",
       "26           NaN               NaN              NaN         NaN   \n",
       "\n",
       "   params.shrinking params.probability params.kernel  params.gamma  \\\n",
       "0               NaN                NaN           NaN           NaN   \n",
       "1               NaN                NaN           NaN           NaN   \n",
       "2               NaN                NaN           NaN           NaN   \n",
       "3               NaN                NaN           NaN           NaN   \n",
       "4              True               True          poly         0.506   \n",
       "5               NaN                NaN           NaN           NaN   \n",
       "6               NaN                NaN           NaN           NaN   \n",
       "7               NaN                NaN           NaN         0.650   \n",
       "8               NaN                NaN           NaN           NaN   \n",
       "9               NaN                NaN           NaN           NaN   \n",
       "10              NaN                NaN           NaN           NaN   \n",
       "11              NaN                NaN           NaN           NaN   \n",
       "12              NaN                NaN           NaN           NaN   \n",
       "13            False               True          poly         0.686   \n",
       "14              NaN                NaN           NaN           NaN   \n",
       "15              NaN                NaN           NaN           NaN   \n",
       "16              NaN                NaN           NaN         0.950   \n",
       "17              NaN                NaN           NaN           NaN   \n",
       "18              NaN                NaN           NaN           NaN   \n",
       "19              NaN                NaN           NaN           NaN   \n",
       "20              NaN                NaN           NaN           NaN   \n",
       "21              NaN                NaN           NaN           NaN   \n",
       "22             True               True           rbf         0.951   \n",
       "23              NaN                NaN           NaN           NaN   \n",
       "24              NaN                NaN           NaN           NaN   \n",
       "25              NaN                NaN           NaN         0.200   \n",
       "26              NaN                NaN           NaN           NaN   \n",
       "\n",
       "   params.decision_function_shape  params.C params.replacement  \\\n",
       "0                             NaN       NaN                NaN   \n",
       "1                             NaN       NaN                NaN   \n",
       "2                             NaN       NaN                NaN   \n",
       "3                             NaN       NaN                NaN   \n",
       "4                             ovo      4.35                NaN   \n",
       "5                             NaN       NaN               True   \n",
       "6                             NaN       NaN                NaN   \n",
       "7                             NaN       NaN                NaN   \n",
       "8                             NaN       NaN                NaN   \n",
       "9                             NaN       NaN                NaN   \n",
       "10                            NaN       NaN                NaN   \n",
       "11                            NaN       NaN                NaN   \n",
       "12                            NaN       NaN                NaN   \n",
       "13                            ovo      1.85                NaN   \n",
       "14                            NaN       NaN               True   \n",
       "15                            NaN       NaN                NaN   \n",
       "16                            NaN       NaN                NaN   \n",
       "17                            NaN       NaN                NaN   \n",
       "18                            NaN       NaN                NaN   \n",
       "19                            NaN       NaN                NaN   \n",
       "20                            NaN       NaN                NaN   \n",
       "21                            NaN       NaN                NaN   \n",
       "22                            ovo      7.10                NaN   \n",
       "23                            NaN       NaN               True   \n",
       "24                            NaN       NaN                NaN   \n",
       "25                            NaN       NaN                NaN   \n",
       "26                            NaN       NaN                NaN   \n",
       "\n",
       "    params.learning_rate  params.subsample  params.seed  \\\n",
       "0                    NaN               NaN          NaN   \n",
       "1                    NaN               NaN          NaN   \n",
       "2                    NaN               NaN          NaN   \n",
       "3                    NaN               NaN          NaN   \n",
       "4                    NaN               NaN          NaN   \n",
       "5                 0.0850               NaN          NaN   \n",
       "6                 0.4000               NaN          NaN   \n",
       "7                 0.0090              0.85       2022.0   \n",
       "8                 0.0325               NaN          NaN   \n",
       "9                    NaN               NaN          NaN   \n",
       "10                   NaN               NaN          NaN   \n",
       "11                   NaN               NaN          NaN   \n",
       "12                   NaN               NaN          NaN   \n",
       "13                   NaN               NaN          NaN   \n",
       "14                0.0710               NaN          NaN   \n",
       "15                0.4250               NaN          NaN   \n",
       "16                0.0090              0.70       2022.0   \n",
       "17                0.0400               NaN          NaN   \n",
       "18                   NaN               NaN          NaN   \n",
       "19                   NaN               NaN          NaN   \n",
       "20                   NaN               NaN          NaN   \n",
       "21                   NaN               NaN          NaN   \n",
       "22                   NaN               NaN          NaN   \n",
       "23                0.0870               NaN          NaN   \n",
       "24                0.4500               NaN          NaN   \n",
       "25                0.0070              0.95       2022.0   \n",
       "26                0.0400               NaN          NaN   \n",
       "\n",
       "    params.scale_pos_weight params.objective  params.lambda  \\\n",
       "0                       NaN              NaN            NaN   \n",
       "1                       NaN              NaN            NaN   \n",
       "2                       NaN              NaN            NaN   \n",
       "3                       NaN              NaN            NaN   \n",
       "4                       NaN              NaN            NaN   \n",
       "5                       NaN              NaN            NaN   \n",
       "6                       NaN              NaN            NaN   \n",
       "7                  2.187097  binary:logistic            0.4   \n",
       "8                       NaN              NaN            NaN   \n",
       "9                       NaN              NaN            NaN   \n",
       "10                      NaN              NaN            NaN   \n",
       "11                      NaN              NaN            NaN   \n",
       "12                      NaN              NaN            NaN   \n",
       "13                      NaN              NaN            NaN   \n",
       "14                      NaN              NaN            NaN   \n",
       "15                      NaN              NaN            NaN   \n",
       "16                 2.398345  binary:logistic            0.9   \n",
       "17                      NaN              NaN            NaN   \n",
       "18                      NaN              NaN            NaN   \n",
       "19                      NaN              NaN            NaN   \n",
       "20                      NaN              NaN            NaN   \n",
       "21                      NaN              NaN            NaN   \n",
       "22                      NaN              NaN            NaN   \n",
       "23                      NaN              NaN            NaN   \n",
       "24                      NaN              NaN            NaN   \n",
       "25                 2.139746  binary:logistic            0.1   \n",
       "26                      NaN              NaN            NaN   \n",
       "\n",
       "   params.eval_metric  params.colsample_bytree params.scoring  \\\n",
       "0                 NaN                      NaN            NaN   \n",
       "1                 NaN                      NaN            NaN   \n",
       "2                 NaN                      NaN            NaN   \n",
       "3                 NaN                      NaN            NaN   \n",
       "4                 NaN                      NaN            NaN   \n",
       "5                 NaN                      NaN            NaN   \n",
       "6                 NaN                      NaN            NaN   \n",
       "7               aucpr                     0.70            NaN   \n",
       "8                 NaN                      NaN        roc_auc   \n",
       "9                 NaN                      NaN            NaN   \n",
       "10                NaN                      NaN            NaN   \n",
       "11                NaN                      NaN            NaN   \n",
       "12                NaN                      NaN            NaN   \n",
       "13                NaN                      NaN            NaN   \n",
       "14                NaN                      NaN            NaN   \n",
       "15                NaN                      NaN            NaN   \n",
       "16                auc                     0.50            NaN   \n",
       "17                NaN                      NaN        roc_auc   \n",
       "18                NaN                      NaN            NaN   \n",
       "19                NaN                      NaN            NaN   \n",
       "20                NaN                      NaN            NaN   \n",
       "21                NaN                      NaN            NaN   \n",
       "22                NaN                      NaN            NaN   \n",
       "23                NaN                      NaN            NaN   \n",
       "24                NaN                      NaN            NaN   \n",
       "25                auc                     0.75            NaN   \n",
       "26                NaN                      NaN        roc_auc   \n",
       "\n",
       "    params.max_iter          params.loss  params.l2_regularization  \n",
       "0               NaN                  NaN                       NaN  \n",
       "1               NaN                  NaN                       NaN  \n",
       "2               NaN                  NaN                       NaN  \n",
       "3               NaN                  NaN                       NaN  \n",
       "4               NaN                  NaN                       NaN  \n",
       "5               NaN                  NaN                       NaN  \n",
       "6               NaN                  NaN                       NaN  \n",
       "7               NaN                  NaN                       NaN  \n",
       "8             375.0  binary_crossentropy                      0.80  \n",
       "9               NaN                  NaN                       NaN  \n",
       "10              NaN                  NaN                       NaN  \n",
       "11              NaN                  NaN                       NaN  \n",
       "12              NaN                  NaN                       NaN  \n",
       "13              NaN                  NaN                       NaN  \n",
       "14              NaN                  NaN                       NaN  \n",
       "15              NaN                  NaN                       NaN  \n",
       "16              NaN                  NaN                       NaN  \n",
       "17            400.0  binary_crossentropy                      0.25  \n",
       "18              NaN                  NaN                       NaN  \n",
       "19              NaN                  NaN                       NaN  \n",
       "20              NaN                  NaN                       NaN  \n",
       "21              NaN                  NaN                       NaN  \n",
       "22              NaN                  NaN                       NaN  \n",
       "23              NaN                  NaN                       NaN  \n",
       "24              NaN                  NaN                       NaN  \n",
       "25              NaN                  NaN                       NaN  \n",
       "26            475.0  binary_crossentropy                      0.00  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SPECIESES = [\"1\", \"2\", \"1 2\"]\n",
    "MODELS = [\"RandomForestClassifier\", \"BalancedRandomForestClassifier\", \"DecisionTreeClassifier\", \"KNeighborsClassifier\", \"SVM\", \"RUSBoostClassifier\" , \"AdaBoostClassifier\", \"XGBClassifier\", \"HistGradientBoostingClassifier\"]\n",
    "TARGET = \"is_healthy\"\n",
    "\n",
    "binary_classifcation_results = list()\n",
    "\n",
    "for SPECIES in SPECIESES:\n",
    "    num_cols = [col for col in binned_data[SPECIES][\"train\"].columns if (binned_data[SPECIES][\"train\"][col].dtype != object)]\n",
    "    sampling_strategy_over_sample = {\n",
    "        \"healthy\": dict(Counter(binned_data[SPECIES][\"train\"][\"damage_class_group\"]))[\"healthy\"],\n",
    "        \"damaged\": dict(Counter(binned_data[SPECIES][\"train\"][\"damage_class_group\"]))[\"damaged\"],\n",
    "        \"dead\": dict(Counter(binned_data[SPECIES][\"train\"][\"damage_class_group\"]))[\"healthy\"]\n",
    "    }\n",
    "    sampler = SMOTEENN(sampling_strategy=sampling_strategy_over_sample, smote=SMOTE(random_state=2022, k_neighbors=6, sampling_strategy=sampling_strategy_over_sample), enn=EditedNearestNeighbours(n_neighbors=5, kind_sel=\"mode\", n_jobs=58), random_state=2022, n_jobs=58)\n",
    "    X_resampled, y_resampled = sampler.fit_resample(X=binned_data[SPECIES][\"train\"][num_cols], y=binned_data[SPECIES][\"train\"][\"damage_class_group\"])\n",
    "    \n",
    "    # over sample (TARGET WILL BECOME TWICE NUMBERS)\n",
    "    sampling_strategy_under_sample = {\n",
    "        \"healthy\": dict(Counter(y_resampled))[\"healthy\"],\n",
    "        \"damaged\": dict(Counter(y_resampled))[\"healthy\"],\n",
    "        \"dead\": dict(Counter(y_resampled))[\"dead\"]\n",
    "    }\n",
    "    under_sampler = RandomUnderSampler(random_state=2022, sampling_strategy=sampling_strategy_under_sample)\n",
    "    X_resampled, y_resampled = under_sampler.fit_resample(X=X_resampled[num_cols], y=y_resampled)\n",
    "\n",
    "    for MODEL in MODELS:\n",
    "        if os.path.exists(f\"{EXPORT_PATH}/{MODEL}_{SPECIES_CODE[SPECIES]}_{TARGET}.json\"):\n",
    "            continue\n",
    "        print(\"-\"*100)\n",
    "        print(f\"{MODEL} -> {SPECIES_CODE[SPECIES]}@{TARGET}\")\n",
    "        print(\"\\t performing backward feature elemination...\")\n",
    "        try:\n",
    "            init_model_params = get_model_params(_model=MODEL, _target=TARGET, _species=SPECIES_CODE[SPECIES])\n",
    "        except FileNotFoundError:\n",
    "            init_model_params = {}\n",
    "            \n",
    "        if \"class_weight\" in init_model_params:\n",
    "            init_model_params[\"class_weight\"] = define_class_weight(X_resampled[TARGET])\n",
    "        if \"pos_scale\" in init_model_params:\n",
    "            init_model_params[\"pos_scale\"] = define_pos_scale(X_resampled[TARGET])\n",
    "\n",
    "        skf = StratifiedKFold(n_splits=3, shuffle=True, random_state=2022)\n",
    "        f1_scorer = metrics.make_scorer(metrics.f1_score, **{\"average\": \"weighted\"})\n",
    "\n",
    "        if MODEL == \"RandomForestClassifier\":\n",
    "            model = RandomForestClassifier(**init_model_params)\n",
    "        elif MODEL == \"XGBClassifier\":\n",
    "            model = xgb.XGBClassifier(**init_model_params)\n",
    "        elif MODEL == \"KNeighborsClassifier\":\n",
    "            model = KNeighborsClassifier(**init_model_params)\n",
    "        elif MODEL == \"DecisionTreeClassifier\":\n",
    "            model = DecisionTreeClassifier(**init_model_params)\n",
    "        elif MODEL == \"HistGradientBoostingClassifier\":\n",
    "            model = HistGradientBoostingClassifier(**init_model_params)\n",
    "        elif MODEL == \"BalancedRandomForestClassifier\":\n",
    "            model = BalancedRandomForestClassifier(**init_model_params)\n",
    "        elif MODEL == \"RUSBoostClassifier\":\n",
    "            model = RUSBoostClassifier(**init_model_params)\n",
    "        elif MODEL == \"AdaBoostClassifier\":\n",
    "            model = AdaBoostClassifier(**init_model_params)\n",
    "        else: #SVM\n",
    "            model = SVC(**init_model_params)\n",
    "\n",
    "        sfs = SequentialFeatureSelector(estimator=model, direction=\"backward\", scoring=f1_scorer, cv=skf, n_jobs=58)\n",
    "        sfs.fit(X_resampled[all_features], X_resampled[TARGET])\n",
    "        relevant_features = list(X_resampled[all_features].columns[sfs.get_support()])\n",
    "\n",
    "        # TRAINING DATA\n",
    "        X_train = X_resampled[relevant_features]\n",
    "        y_train = X_resampled[TARGET]\n",
    "        # TEST DATA\n",
    "        X_test = binned_data[SPECIES][\"test\"][relevant_features]\n",
    "        y_test = binned_data[SPECIES][\"test\"][TARGET]\n",
    "\n",
    "        print(\"\\t performing hyperparameter tuning...\")\n",
    "\n",
    "        if MODEL == \"RandomForestClassifier\":\n",
    "            params_rf = PARAMS_RF\n",
    "            params_rf[\"class_weight\"] = [define_class_weight(y_train.values)]\n",
    "            fitted_model_params = parameter_tuning(_model=RandomForestClassifier(), _params=params_rf, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = RandomForestClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"XGBClassifier\":\n",
    "            params_xgb = PARAMS_XGB\n",
    "            params_xgb['scale_pos_weight'] = [define_pos_scale(y_train.values)]\n",
    "            fitted_model_params = parameter_tuning(_model=xgb.XGBClassifier(), _params=params_xgb, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = xgb.XGBClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"KNeighborsClassifier\":\n",
    "            params_kn = PARAMS_KN\n",
    "            fitted_model_params = parameter_tuning(_model=KNeighborsClassifier(), _params=params_kn, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = KNeighborsClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"DecisionTreeClassifier\":\n",
    "            params_dt = PARAMS_DT\n",
    "            params_dt['class_weight'] = [define_class_weight(y_train.values)]\n",
    "            fitted_model_params = parameter_tuning(_model=DecisionTreeClassifier(), _params=params_dt, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = DecisionTreeClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"HistGradientBoostingClassifier\":\n",
    "            params_hgb = PARAMS_HGB\n",
    "            fitted_model_params = parameter_tuning(_model=HistGradientBoostingClassifier(), _params=params_hgb, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = HistGradientBoostingClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"BalancedRandomForestClassifier\":\n",
    "            params_brf = PARAMS_BRF\n",
    "            fitted_model_params = parameter_tuning(_model=BalancedRandomForestClassifier(), _params=params_brf, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = BalancedRandomForestClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"RUSBoostClassifier\":\n",
    "            params_rus = PARAMS_RUS\n",
    "            fitted_model_params = parameter_tuning(_model=RUSBoostClassifier(), _params=params_rus, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = RUSBoostClassifier(**fitted_model_params)\n",
    "        elif MODEL == \"AdaBoostClassifier\":\n",
    "            params_ada = PARAMS_ADA\n",
    "            fitted_model_params = parameter_tuning(_model=AdaBoostClassifier(), _params=params_ada, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = AdaBoostClassifier(**fitted_model_params)\n",
    "        else:\n",
    "            params_svm = PARAMS_SVM\n",
    "            params_svm['class_weight'] = [define_class_weight(y_train.values)]\n",
    "            fitted_model_params = parameter_tuning(_model=SVC(), _params=params_svm, _scoring=f1_scorer, _X=X_train, _y=y_train)\n",
    "            model = SVC(**fitted_model_params)\n",
    "\n",
    "        # CREATING BAGGING CLASSIFIER\n",
    "        model = BaggingClassifier(base_estimator=model, n_estimators=15, max_samples=.2, max_features=1., bootstrap=True, bootstrap_features=True, oob_score=True, n_jobs=16)\n",
    "        print(\"\\t fitting model...\")\n",
    "        model.fit(X_train, y_train)\n",
    "        # save model\n",
    "        pickle.dump(model, open(f\"{EXPORT_PATH}/{MODEL}_{SPECIES_CODE[SPECIES]}_{TARGET}.sav\", 'wb'))\n",
    "\n",
    "        # predict probabilities\n",
    "        y_pred_proba = model.predict_proba(X_test)\n",
    "\n",
    "        print(\"\\t performing permutation feature importance...\")\n",
    "        from sklearn.inspection import permutation_importance\n",
    "        permutation_importance = permutation_importance(model, X_test, y_test, n_repeats=5, random_state=2022, n_jobs=32, scoring=f1_scorer)\n",
    "        permutation_importance_obj = {}\n",
    "        for i, feat_imp in enumerate(permutation_importance.importances_mean):\n",
    "            permutation_importance_obj[all_features[i]] = feat_imp\n",
    "\n",
    "        print(\"\\t evaluating...\")\n",
    "        results = {}\n",
    "        results[\"species\"] = SPECIES_CODE[SPECIES]\n",
    "        results[\"model\"] = MODEL\n",
    "        results[\"target\"] = TARGET\n",
    "        results[\"params\"] = fitted_model_params\n",
    "        results[\"relevant_features\"] = relevant_features\n",
    "        results[\"feature_permutaion_importance\"] = permutation_importance_obj\n",
    "\n",
    "        results[\"metrics\"] = {}\n",
    "        results[\"metrics\"][\"auc\"] = metrics.roc_auc_score(y_test.values, y_pred_proba[:, 1])\n",
    "\n",
    "        ## ROC AUC\n",
    "        results[\"metrics\"][\"roc\"] = {}\n",
    "        threshold_roc, gmean_roc = roc_auc(y_test.values, y_pred_proba[:,1], axes=None)\n",
    "        results[\"metrics\"][\"roc\"][\"threshold\"] = threshold_roc\n",
    "        y_pred_roc = apply_prediction(y_pred_proba[:, 1], threshold_roc)\n",
    "        results[\"metrics\"][\"roc\"][\"cohen_kappa\"] = metrics.cohen_kappa_score(y_test.values, y_pred_roc)\n",
    "        results[\"metrics\"][\"roc\"][\"f1\"] = metrics.f1_score(y_test.values, y_pred_roc)\n",
    "        results[\"metrics\"][\"roc\"][\"recall\"] = metrics.recall_score(y_test.values, y_pred_roc)\n",
    "        results[\"metrics\"][\"roc\"][\"precision\"] = metrics.precision_score(y_test.values, y_pred_roc)\n",
    "        tn, fp, fn, tp = metrics.confusion_matrix(y_test, y_pred_roc).ravel()\n",
    "        results[\"metrics\"][\"roc\"][\"tn\"] = tn\n",
    "        results[\"metrics\"][\"roc\"][\"fp\"] = fp\n",
    "        results[\"metrics\"][\"roc\"][\"fn\"] = fn\n",
    "        results[\"metrics\"][\"roc\"][\"tp\"] = tp\n",
    "\n",
    "        ## PRC\n",
    "        results[\"metrics\"][\"prc\"] = {}\n",
    "        threshold_prc, fscore_prc = prc_rc(y_test.values, y_pred_proba[:,1], axes=None)\n",
    "        results[\"metrics\"][\"prc\"][\"threshold\"] = threshold_prc\n",
    "        y_pred_prc = apply_prediction(y_pred_proba[:, 1], threshold_prc)\n",
    "        results[\"metrics\"][\"prc\"][\"cohen_kappa\"] = metrics.cohen_kappa_score(y_test.values, y_pred_prc)\n",
    "        results[\"metrics\"][\"prc\"][\"f1\"] = metrics.f1_score(y_test.values, y_pred_prc)\n",
    "        results[\"metrics\"][\"prc\"][\"recall\"] = metrics.recall_score(y_test.values, y_pred_prc)\n",
    "        results[\"metrics\"][\"prc\"][\"precision\"] = metrics.precision_score(y_test.values, y_pred_prc)\n",
    "        tn, fp, fn, tp = metrics.confusion_matrix(y_test, y_pred_prc).ravel()\n",
    "        results[\"metrics\"][\"prc\"][\"tn\"] = tn\n",
    "        results[\"metrics\"][\"prc\"][\"fp\"] = fp\n",
    "        results[\"metrics\"][\"prc\"][\"fn\"] = fn\n",
    "        results[\"metrics\"][\"prc\"][\"tp\"] = tp\n",
    "\n",
    "        ## TUNING\n",
    "        results[\"metrics\"][\"tuning\"] = {}\n",
    "        threshold_tuning, fscore_tuneing = tune_threshold(y_test.values, y_pred_proba[:,1], axes=None)\n",
    "        results[\"metrics\"][\"tuning\"][\"threshold\"] = threshold_tuning\n",
    "        y_pred_tuning = apply_prediction(y_pred_proba[:, 1], threshold_tuning)\n",
    "        results[\"metrics\"][\"tuning\"][\"cohen_kappa\"] = metrics.cohen_kappa_score(y_test.values, y_pred_tuning)\n",
    "        results[\"metrics\"][\"tuning\"][\"f1\"] = metrics.f1_score(y_test.values, y_pred_tuning)\n",
    "        results[\"metrics\"][\"tuning\"][\"recall\"] = metrics.recall_score(y_test.values, y_pred_tuning)\n",
    "        results[\"metrics\"][\"tuning\"][\"precision\"] = metrics.precision_score(y_test.values, y_pred_tuning)\n",
    "        tn, fp, fn, tp = metrics.confusion_matrix(y_test, y_pred_tuning).ravel()\n",
    "        results[\"metrics\"][\"tuning\"][\"tn\"] = tn\n",
    "        results[\"metrics\"][\"tuning\"][\"fp\"] = fp\n",
    "        results[\"metrics\"][\"tuning\"][\"fn\"] = fn\n",
    "        results[\"metrics\"][\"tuning\"][\"tp\"] = tp\n",
    "\n",
    "        # quick export to dump data\n",
    "        with open(f\"{EXPORT_PATH}/{MODEL}_{SPECIES_CODE[SPECIES]}_{TARGET}.json\", 'w', encoding='utf-8') as f:\n",
    "            json.dump(str(dict((k, v) for k,v in results.items())), f, ensure_ascii=False, indent=4)\n",
    "        pd.json_normalize(results).to_csv(f\"{EXPORT_PATH}/{MODEL}_{SPECIES_CODE[SPECIES]}_{TARGET}.csv\", index=False)\n",
    "\n",
    "        binary_classifcation_results.append(results)\n",
    "\n",
    "print(\"-\"*75)\n",
    "print(f\"EXPORTING OVERALL RESULTS TO {EXPORT_PATH}/modelling_pipeline_results.csv\")\n",
    "print(\"-\"*75)\n",
    "df_result = pd.json_normalize(binary_classifcation_results)\n",
    "df_result.to_csv(f\"{EXPORT_PATH}/modelling_pipeline_results_healthy.csv\", index=False)\n",
    "df_result"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0e40f5b-eb2d-47e4-974b-4558375805ce",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Ensemble Learning: Base Model Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "0f9895b2-6380-4da5-9860-078c378b6b73",
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    "execution": {
     "iopub.execute_input": "2022-04-09T18:48:11.532003Z",
     "iopub.status.busy": "2022-04-09T18:48:11.532003Z",
     "iopub.status.idle": "2022-04-09T18:48:11.907023Z",
     "shell.execute_reply": "2022-04-09T18:48:11.907023Z",
     "shell.execute_reply.started": "2022-04-09T18:48:11.532003Z"
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>group</th>\n",
       "      <th>model</th>\n",
       "      <th>target</th>\n",
       "      <th>species</th>\n",
       "      <th>auc</th>\n",
       "      <th>threshold</th>\n",
       "      <th>cohen_kappa</th>\n",
       "      <th>f1</th>\n",
       "      <th>recall</th>\n",
       "      <th>precision</th>\n",
       "      <th>tn</th>\n",
       "      <th>fp</th>\n",
       "      <th>fn</th>\n",
       "      <th>tp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>prc</td>\n",
       "      <td>RandomForestClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>Conifer</td>\n",
       "      <td>0.758450</td>\n",
       "      <td>0.339557</td>\n",
       "      <td>0.515887</td>\n",
       "      <td>0.949618</td>\n",
       "      <td>0.984683</td>\n",
       "      <td>0.916964</td>\n",
       "      <td>122</td>\n",
       "      <td>163</td>\n",
       "      <td>28</td>\n",
       "      <td>1800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>prc</td>\n",
       "      <td>RandomForestClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>Mixed</td>\n",
       "      <td>0.738243</td>\n",
       "      <td>0.294460</td>\n",
       "      <td>0.191548</td>\n",
       "      <td>0.948625</td>\n",
       "      <td>0.991679</td>\n",
       "      <td>0.909154</td>\n",
       "      <td>20</td>\n",
       "      <td>131</td>\n",
       "      <td>11</td>\n",
       "      <td>1311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>tuning</td>\n",
       "      <td>AdaBoostClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>Mixed</td>\n",
       "      <td>0.768337</td>\n",
       "      <td>0.493000</td>\n",
       "      <td>0.229014</td>\n",
       "      <td>0.947636</td>\n",
       "      <td>0.985628</td>\n",
       "      <td>0.912465</td>\n",
       "      <td>26</td>\n",
       "      <td>125</td>\n",
       "      <td>19</td>\n",
       "      <td>1303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>tuning</td>\n",
       "      <td>HistGradientBoostingClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>Mixed</td>\n",
       "      <td>0.788438</td>\n",
       "      <td>0.148000</td>\n",
       "      <td>0.272373</td>\n",
       "      <td>0.947368</td>\n",
       "      <td>0.980333</td>\n",
       "      <td>0.916549</td>\n",
       "      <td>33</td>\n",
       "      <td>118</td>\n",
       "      <td>26</td>\n",
       "      <td>1296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>prc</td>\n",
       "      <td>AdaBoostClassifier</td>\n",
       "      <td>is_damaged</td>\n",
       "      <td>Deciduous</td>\n",
       "      <td>0.702559</td>\n",
       "      <td>0.491952</td>\n",
       "      <td>0.434160</td>\n",
       "      <td>0.945547</td>\n",
       "      <td>0.976866</td>\n",
       "      <td>0.916174</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>22</td>\n",
       "      <td>929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>tuning</td>\n",
       "      <td>DecisionTreeClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>Conifer</td>\n",
       "      <td>0.802049</td>\n",
       "      <td>0.616000</td>\n",
       "      <td>0.020506</td>\n",
       "      <td>0.025641</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>0.013889</td>\n",
       "      <td>2036</td>\n",
       "      <td>71</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>roc</td>\n",
       "      <td>SVM</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>Deciduous</td>\n",
       "      <td>0.469308</td>\n",
       "      <td>0.035447</td>\n",
       "      <td>0.007407</td>\n",
       "      <td>0.023609</td>\n",
       "      <td>0.777778</td>\n",
       "      <td>0.011986</td>\n",
       "      <td>500</td>\n",
       "      <td>577</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>roc</td>\n",
       "      <td>DecisionTreeClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>Deciduous</td>\n",
       "      <td>0.431910</td>\n",
       "      <td>0.520115</td>\n",
       "      <td>0.007092</td>\n",
       "      <td>0.023121</td>\n",
       "      <td>0.444444</td>\n",
       "      <td>0.011869</td>\n",
       "      <td>744</td>\n",
       "      <td>333</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>roc</td>\n",
       "      <td>BalancedRandomForestClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>Mixed</td>\n",
       "      <td>0.805140</td>\n",
       "      <td>0.123400</td>\n",
       "      <td>0.016942</td>\n",
       "      <td>0.022222</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.011236</td>\n",
       "      <td>1117</td>\n",
       "      <td>352</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>tuning</td>\n",
       "      <td>BalancedRandomForestClassifier</td>\n",
       "      <td>is_dead</td>\n",
       "      <td>Deciduous</td>\n",
       "      <td>0.471165</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>0.005963</td>\n",
       "      <td>0.021898</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.011321</td>\n",
       "      <td>815</td>\n",
       "      <td>262</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>81 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     group                           model      target    species       auc  \\\n",
       "0      prc          RandomForestClassifier  is_damaged    Conifer  0.758450   \n",
       "1      prc          RandomForestClassifier  is_damaged      Mixed  0.738243   \n",
       "2   tuning              AdaBoostClassifier  is_damaged      Mixed  0.768337   \n",
       "3   tuning  HistGradientBoostingClassifier  is_damaged      Mixed  0.788438   \n",
       "4      prc              AdaBoostClassifier  is_damaged  Deciduous  0.702559   \n",
       "..     ...                             ...         ...        ...       ...   \n",
       "76  tuning          DecisionTreeClassifier     is_dead    Conifer  0.802049   \n",
       "77     roc                             SVM     is_dead  Deciduous  0.469308   \n",
       "78     roc          DecisionTreeClassifier     is_dead  Deciduous  0.431910   \n",
       "79     roc  BalancedRandomForestClassifier     is_dead      Mixed  0.805140   \n",
       "80  tuning  BalancedRandomForestClassifier     is_dead  Deciduous  0.471165   \n",
       "\n",
       "    threshold  cohen_kappa        f1    recall  precision    tn   fp  fn    tp  \n",
       "0    0.339557     0.515887  0.949618  0.984683   0.916964   122  163  28  1800  \n",
       "1    0.294460     0.191548  0.948625  0.991679   0.909154    20  131  11  1311  \n",
       "2    0.493000     0.229014  0.947636  0.985628   0.912465    26  125  19  1303  \n",
       "3    0.148000     0.272373  0.947368  0.980333   0.916549    33  118  26  1296  \n",
       "4    0.491952     0.434160  0.945547  0.976866   0.916174    50   85  22   929  \n",
       "..        ...          ...       ...       ...        ...   ...  ...  ..   ...  \n",
       "76   0.616000     0.020506  0.025641  0.166667   0.013889  2036   71   5     1  \n",
       "77   0.035447     0.007407  0.023609  0.777778   0.011986   500  577   2     7  \n",
       "78   0.520115     0.007092  0.023121  0.444444   0.011869   744  333   5     4  \n",
       "79   0.123400     0.016942  0.022222  1.000000   0.011236  1117  352   0     4  \n",
       "80   0.400000     0.005963  0.021898  0.333333   0.011321   815  262   6     3  \n",
       "\n",
       "[81 rows x 14 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_results = [pd.read_csv(f\"{EXPORT_PATH}/{file}.csv\") for file in [\"modelling_pipeline_results\", \"modelling_pipeline_results_dead\", \"modelling_pipeline_results_healthy\"]]\n",
    "df_results = pd.concat(df_results, ignore_index=True)\n",
    "df_metrics, df_best_metrics, df_parameter, df_feature_importance = parse_results(df_results)\n",
    "df_best_metrics"
   ]
  }
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