pycaret.ipynb

{
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     "start_time": "2021-09-26T11:47:54.461375",
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    "tags": []
   },
   "source": [
    "# Using Pycaret library Tabular Playground Competition! #"
   ]
  },
  {
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       "         f1        f2         f3        f4       f5        f6       f7  \\\n",
       "id                                                                       \n",
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       "\n",
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       "\n",
       "        f113      f114    f115          f116    f117     f118  claim  \n",
       "id                                                                    \n",
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     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from pathlib import Path\n",
    "\n",
    "data_dir = Path('../input/tabular-playground-series-sep-2021/')\n",
    "\n",
    "df_train = pd.read_csv(\n",
    "    data_dir / \"train.csv\",\n",
    "    index_col='id',\n",
    "    nrows=25000,  # comment this row to use the full dataset\n",
    ")\n",
    "\n",
    "FEATURES = df_train.columns[:-1]\n",
    "TARGET = df_train.columns[-1]\n",
    "\n",
    "df_train.head()"
   ]
  },
  {
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     "text": [
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      "\u001b[?25hCollecting isodate>=0.6.0\r\n",
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      "Collecting brotli\r\n",
      "  Downloading Brotli-1.0.9-cp37-cp37m-manylinux1_x86_64.whl (357 kB)\r\n",
      "\u001b[K     |████████████████████████████████| 357 kB 58.9 MB/s \r\n",
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      "Collecting prometheus-flask-exporter\r\n",
      "  Downloading prometheus_flask_exporter-0.18.2.tar.gz (22 kB)\r\n",
      "Collecting databricks-cli>=0.8.7\r\n",
      "  Downloading databricks-cli-0.15.0.tar.gz (56 kB)\r\n",
      "\u001b[K     |████████████████████████████████| 56 kB 4.6 MB/s \r\n",
      "\u001b[?25hCollecting importlib-metadata\r\n",
      "  Downloading importlib_metadata-4.8.1-py3-none-any.whl (17 kB)\r\n",
      "Requirement already satisfied: sqlparse>=0.3.1 in /opt/conda/lib/python3.7/site-packages (from mlflow->pycaret[full]) (0.4.1)\r\n",
      "Collecting gunicorn\r\n",
      "  Downloading gunicorn-20.1.0-py3-none-any.whl (79 kB)\r\n",
      "\u001b[K     |████████████████████████████████| 79 kB 8.2 MB/s \r\n",
      "\u001b[?25hCollecting alembic\r\n",
      "  Downloading alembic-1.4.1.tar.gz (1.1 MB)\r\n",
      "\u001b[K     |████████████████████████████████| 1.1 MB 49.9 MB/s \r\n",
      "\u001b[?25hCollecting querystring-parser\r\n",
      "  Downloading querystring_parser-1.2.4-py2.py3-none-any.whl (7.9 kB)\r\n",
      "Requirement already satisfied: docker>=4.0.0 in /opt/conda/lib/python3.7/site-packages (from mlflow->pycaret[full]) (5.0.0)\r\n",
      "Collecting python-editor>=0.3\r\n",
      "  Downloading python_editor-1.0.4-py3-none-any.whl (4.9 kB)\r\n",
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      "Requirement already satisfied: multiprocess>=0.70.12 in /opt/conda/lib/python3.7/site-packages (from pathos->SALib>=1.3.3->interpret-core[dash,debug,decisiontree,ebm,lime,linear,notebook,plotly,required,sensitivity,shap,skoperules,treeinterpreter]>=0.2.4->interpret<=0.2.4->pycaret[full]) (0.70.12.2)\r\n",
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      "Requirement already satisfied: ppft>=1.6.6.4 in /opt/conda/lib/python3.7/site-packages (from pathos->SALib>=1.3.3->interpret-core[dash,debug,decisiontree,ebm,lime,linear,notebook,plotly,required,sensitivity,shap,skoperules,treeinterpreter]>=0.2.4->interpret<=0.2.4->pycaret[full]) (1.6.6.4)\r\n",
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      "Requirement already satisfied: pynndescent>=0.5 in /opt/conda/lib/python3.7/site-packages (from umap-learn->pycaret[full]) (0.5.4)\r\n",
      "Building wheels for collected packages: dash-core-components, dash-html-components, dash-table, alembic, databricks-cli, prometheus-flask-exporter, pyod\r\n",
      "  Building wheel for dash-core-components (setup.py) ... \u001b[?25l-\b \b\\\b \bdone\r\n",
      "\u001b[?25h  Created wheel for dash-core-components: filename=dash_core_components-2.0.0-py3-none-any.whl size=3821 sha256=615cb6c66306d78b3f46b89613656fb90cb1af8f0bfba4bd8fffb50542c7f899\r\n",
      "  Stored in directory: /root/.cache/pip/wheels/00/f9/c7/1a6437d794ed753ea9bc9079e761d4fc803a1f1f5d3697b9ec\r\n",
      "  Building wheel for dash-html-components (setup.py) ... \u001b[?25l-\b \bdone\r\n",
      "\u001b[?25h  Created wheel for dash-html-components: filename=dash_html_components-2.0.0-py3-none-any.whl size=4089 sha256=af5ba0270a80bc27eb72feab420954849e1a3df9c3d4383158f85ffd53225f19\r\n",
      "  Stored in directory: /root/.cache/pip/wheels/ec/6b/81/05aceabd8b27f724e2c96784016287cc1bfbc349ebfda451de\r\n",
      "  Building wheel for dash-table (setup.py) ... \u001b[?25l-\b \bdone\r\n",
      "\u001b[?25h  Created wheel for dash-table: filename=dash_table-5.0.0-py3-none-any.whl size=3911 sha256=3f5e8f89c6c2eef07c8da1e9e7b5fce0be2030b98d37f7ca09984e98c10b2b28\r\n",
      "  Stored in directory: /root/.cache/pip/wheels/85/5d/4e/7c276b57992951dbe770bf5caad6448d0539c510663aefd2e2\r\n",
      "  Building wheel for alembic (setup.py) ... \u001b[?25l-\b \b\\\b \b|\b \bdone\r\n",
      "\u001b[?25h  Created wheel for alembic: filename=alembic-1.4.1-py2.py3-none-any.whl size=158172 sha256=d852bc5d67d8cc96c8b85601f0a6e3d9d3b28daa9983ef68ba92282e368ea96a\r\n",
      "  Stored in directory: /root/.cache/pip/wheels/be/5d/0a/9e13f53f4f5dfb67cd8d245bb7cdffe12f135846f491a283e3\r\n",
      "  Building wheel for databricks-cli (setup.py) ... \u001b[?25l-\b \b\\\b \bdone\r\n",
      "\u001b[?25h  Created wheel for databricks-cli: filename=databricks_cli-0.15.0-py3-none-any.whl size=105260 sha256=4a1e36e91f5ed2352db658020aa0bec67809020769cb51ffd3f320f53703580a\r\n",
      "  Stored in directory: /root/.cache/pip/wheels/e7/ba/75/284f9a90ff7a010bb23b9798f2e9a19dd9fe619379c917bff4\r\n",
      "  Building wheel for prometheus-flask-exporter (setup.py) ... \u001b[?25l-\b \bdone\r\n",
      "\u001b[?25h  Created wheel for prometheus-flask-exporter: filename=prometheus_flask_exporter-0.18.2-py3-none-any.whl size=17415 sha256=a709d57d8e4fba80fa5a3903d4ca50833779855672a59392032a0eb7ed997a29\r\n",
      "  Stored in directory: /root/.cache/pip/wheels/6a/1e/1c/c765920cb92b2f0343d2dd8b481a407cee2823f9b4bbd2e52a\r\n",
      "  Building wheel for pyod (setup.py) ... \u001b[?25l-\b \b\\\b \bdone\r\n",
      "\u001b[?25h  Created wheel for pyod: filename=pyod-0.9.3-py3-none-any.whl size=130719 sha256=aa79548486d08d15e7c3a739a7f5063e7748950696968eebb8e6e72eab05457b\r\n",
      "  Stored in directory: /root/.cache/pip/wheels/ac/94/65/d29b87d4ad6defcec32686063e9bbaf5907a259eb2d8342174\r\n",
      "Successfully built dash-core-components dash-html-components dash-table alembic databricks-cli prometheus-flask-exporter pyod\r\n",
      "Installing collected packages: importlib-metadata, brotli, scipy, flask-compress, dash-table, dash-html-components, dash-core-components, zope.event, python-editor, dash, treeinterpreter, skope-rules, SALib, querystring-parser, prometheus-flask-exporter, isodate, interpret-core, gunicorn, gevent, databricks-cli, dash-cytoscape, alembic, pyod, msrest, mlflow, imbalanced-learn, gensim, azure-core, tune-sklearn, pycaret, interpret, azure-storage-blob\r\n",
      "  Attempting uninstall: importlib-metadata\r\n",
      "    Found existing installation: importlib-metadata 3.4.0\r\n",
      "    Uninstalling importlib-metadata-3.4.0:\r\n",
      "      Successfully uninstalled importlib-metadata-3.4.0\r\n",
      "  Attempting uninstall: scipy\r\n",
      "    Found existing installation: scipy 1.7.1\r\n",
      "    Uninstalling scipy-1.7.1:\r\n",
      "      Successfully uninstalled scipy-1.7.1\r\n",
      "  Attempting uninstall: alembic\r\n",
      "    Found existing installation: alembic 1.7.3\r\n",
      "    Uninstalling alembic-1.7.3:\r\n",
      "      Successfully uninstalled alembic-1.7.3\r\n",
      "  Attempting uninstall: imbalanced-learn\r\n",
      "    Found existing installation: imbalanced-learn 0.8.0\r\n",
      "    Uninstalling imbalanced-learn-0.8.0:\r\n",
      "      Successfully uninstalled imbalanced-learn-0.8.0\r\n",
      "  Attempting uninstall: gensim\r\n",
      "    Found existing installation: gensim 4.0.1\r\n",
      "    Uninstalling gensim-4.0.1:\r\n",
      "      Successfully uninstalled gensim-4.0.1\r\n",
      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\r\n",
      "scattertext 0.1.4 requires gensim>=4.0.0, but you have gensim 3.8.3 which is incompatible.\r\n",
      "pdpbox 0.2.1 requires matplotlib==3.1.1, but you have matplotlib 3.4.3 which is incompatible.\r\n",
      "matrixprofile 1.1.10 requires protobuf==3.11.2, but you have protobuf 3.18.0 which is incompatible.\u001b[0m\r\n",
      "Successfully installed SALib-1.4.5 alembic-1.4.1 azure-core-1.18.0 azure-storage-blob-12.9.0 brotli-1.0.9 dash-2.0.0 dash-core-components-2.0.0 dash-cytoscape-0.3.0 dash-html-components-2.0.0 dash-table-5.0.0 databricks-cli-0.15.0 flask-compress-1.10.1 gensim-3.8.3 gevent-21.8.0 gunicorn-20.1.0 imbalanced-learn-0.7.0 importlib-metadata-4.8.1 interpret-0.2.4 interpret-core-0.2.7 isodate-0.6.0 mlflow-1.20.2 msrest-0.6.21 prometheus-flask-exporter-0.18.2 pycaret-2.3.4 pyod-0.9.3 python-editor-1.0.4 querystring-parser-1.2.4 scipy-1.5.4 skope-rules-1.0.1 treeinterpreter-0.2.3 tune-sklearn-0.4.1 zope.event-4.5.0\r\n",
      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\r\n"
     ]
    }
   ],
   "source": [
    "!pip install pycaret[full]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "560580fd",
   "metadata": {
    "papermill": {
     "duration": 0.154335,
     "end_time": "2021-09-26T11:48:39.757026",
     "exception": false,
     "start_time": "2021-09-26T11:48:39.602691",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Import Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "67521489",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-09-26T11:48:40.077335Z",
     "iopub.status.busy": "2021-09-26T11:48:40.076538Z",
     "iopub.status.idle": "2021-09-26T11:48:44.794840Z",
     "shell.execute_reply": "2021-09-26T11:48:44.793763Z",
     "shell.execute_reply.started": "2021-09-26T10:46:11.212164Z"
    },
    "papermill": {
     "duration": 4.883668,
     "end_time": "2021-09-26T11:48:44.794997",
     "exception": false,
     "start_time": "2021-09-26T11:48:39.911329",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type='text/css'>\n",
       ".datatable table.frame { margin-bottom: 0; }\n",
       ".datatable table.frame thead { border-bottom: none; }\n",
       ".datatable table.frame tr.coltypes td {  color: #FFFFFF;  line-height: 6px;  padding: 0 0.5em;}\n",
       ".datatable .bool    { background: #DDDD99; }\n",
       ".datatable .object  { background: #565656; }\n",
       ".datatable .int     { background: #5D9E5D; }\n",
       ".datatable .float   { background: #4040CC; }\n",
       ".datatable .str     { background: #CC4040; }\n",
       ".datatable .time    { background: #40CC40; }\n",
       ".datatable .row_index {  background: var(--jp-border-color3);  border-right: 1px solid var(--jp-border-color0);  color: var(--jp-ui-font-color3);  font-size: 9px;}\n",
       ".datatable .frame tbody td { text-align: left; }\n",
       ".datatable .frame tr.coltypes .row_index {  background: var(--jp-border-color0);}\n",
       ".datatable th:nth-child(2) { padding-left: 12px; }\n",
       ".datatable .hellipsis {  color: var(--jp-cell-editor-border-color);}\n",
       ".datatable .vellipsis {  background: var(--jp-layout-color0);  color: var(--jp-cell-editor-border-color);}\n",
       ".datatable .na {  color: var(--jp-cell-editor-border-color);  font-size: 80%;}\n",
       ".datatable .sp {  opacity: 0.25;}\n",
       ".datatable .footer { font-size: 9px; }\n",
       ".datatable .frame_dimensions {  background: var(--jp-border-color3);  border-top: 1px solid var(--jp-border-color0);  color: var(--jp-ui-font-color3);  display: inline-block;  opacity: 0.6;  padding: 1px 10px 1px 5px;}\n",
       "</style>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from pycaret.classification import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8b82221c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-09-26T11:48:44.984023Z",
     "iopub.status.busy": "2021-09-26T11:48:44.983036Z",
     "iopub.status.idle": "2021-09-26T11:49:39.989603Z",
     "shell.execute_reply": "2021-09-26T11:49:39.988554Z",
     "shell.execute_reply.started": "2021-09-26T10:46:15.829946Z"
    },
    "papermill": {
     "duration": 55.103038,
     "end_time": "2021-09-26T11:49:39.989782",
     "exception": false,
     "start_time": "2021-09-26T11:48:44.886744",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "train = pd.read_csv('../input/tabular-playground-series-sep-2021/train.csv')\n",
    "test = pd.read_csv('../input/tabular-playground-series-sep-2021/test.csv')\n",
    "\n",
    "data = pd.concat([train, test])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "45bc9fe7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-09-26T11:49:40.199073Z",
     "iopub.status.busy": "2021-09-26T11:49:40.197808Z",
     "iopub.status.idle": "2021-09-26T11:49:41.465438Z",
     "shell.execute_reply": "2021-09-26T11:49:41.464985Z",
     "shell.execute_reply.started": "2021-09-26T10:46:56.452625Z"
    },
    "papermill": {
     "duration": 1.381726,
     "end_time": "2021-09-26T11:49:41.465564",
     "exception": false,
     "start_time": "2021-09-26T11:49:40.083838",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "df_data = data.drop(columns = 'id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "209ebb21",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-09-26T11:49:41.653047Z",
     "iopub.status.busy": "2021-09-26T11:49:41.652186Z",
     "iopub.status.idle": "2021-09-26T11:49:42.184214Z",
     "shell.execute_reply": "2021-09-26T11:49:42.183462Z",
     "shell.execute_reply.started": "2021-09-26T10:46:57.720556Z"
    },
    "papermill": {
     "duration": 0.628402,
     "end_time": "2021-09-26T11:49:42.184339",
     "exception": false,
     "start_time": "2021-09-26T11:49:41.555937",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (12, 6))\n",
    "missing_values = df_data.isnull().sum()[:-1]\n",
    "sns.histplot(missing_values, color='violet');\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "98b0648f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-09-26T11:49:42.374269Z",
     "iopub.status.busy": "2021-09-26T11:49:42.373721Z",
     "iopub.status.idle": "2021-09-26T11:49:42.376897Z",
     "shell.execute_reply": "2021-09-26T11:49:42.376364Z",
     "shell.execute_reply.started": "2021-09-26T10:46:58.253679Z"
    },
    "papermill": {
     "duration": 0.10132,
     "end_time": "2021-09-26T11:49:42.377008",
     "exception": false,
     "start_time": "2021-09-26T11:49:42.275688",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "-------- Distribution of Missing values --------\n",
      "Min: 22956\n",
      "Max: 23719\n",
      "Mean: 23364.406779661018\n",
      "------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "print('\\n')\n",
    "print('-------- Distribution of Missing values --------')\n",
    "print('Min:', missing_values.min())\n",
    "print('Max:', missing_values.max())\n",
    "print('Mean:', missing_values.mean())\n",
    "print('------------------------------------------------')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e57a445b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-09-26T11:49:42.626239Z",
     "iopub.status.busy": "2021-09-26T11:49:42.590365Z",
     "iopub.status.idle": "2021-09-26T11:49:42.639969Z",
     "shell.execute_reply": "2021-09-26T11:49:42.639552Z",
     "shell.execute_reply.started": "2021-09-26T10:46:58.264877Z"
    },
    "papermill": {
     "duration": 0.17016,
     "end_time": "2021-09-26T11:49:42.640082",
     "exception": false,
     "start_time": "2021-09-26T11:49:42.469922",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method NDFrame.describe of               f1        f2         f3        f4       f5         f6       f7  \\\n",
       "0       0.108590  0.004314    -37.566  0.017364  0.28915 -10.251000   135.12   \n",
       "1       0.100900  0.299610  11822.000  0.276500  0.45970  -0.837330  1721.90   \n",
       "2       0.178030 -0.006980    907.270  0.272140  0.45948   0.173270  2298.00   \n",
       "3       0.152360  0.007259    780.100  0.025179  0.51947   7.491400   112.51   \n",
       "4       0.116230  0.502900   -109.150  0.297910  0.34490  -0.409320  2538.90   \n",
       "...          ...       ...        ...       ...      ...        ...      ...   \n",
       "493469 -0.009112  0.308190    637.640  0.778200  0.41415  -1.068500   651.22   \n",
       "493470  0.088922  0.482650   6924.100  0.025963  0.35540  -0.870200  2514.20   \n",
       "493471  0.140620  0.484750   1797.100  0.147020  0.28803  -1.407100   434.03   \n",
       "493472  0.168000  0.351760    454.790  0.164580  0.16983   0.323850  2331.20   \n",
       "493473  0.093079  0.501860   3322.400       NaN  0.33269   0.056827  2568.70   \n",
       "\n",
       "              f8            f9           f10      f11           f12       f13  \\\n",
       "0       168900.0  3.992400e+14     86.489000  0.59881  1.423200e+09  0.272400   \n",
       "1       119810.0  3.874100e+15   9953.600000  1.20930  3.334100e+09  0.286310   \n",
       "2       360650.0  1.224500e+13  15827.000000  0.38164  1.230300e+09  0.258070   \n",
       "3       259490.0  7.781400e+13    -36.837000  1.10960  1.223100e+09  0.309440   \n",
       "4        65332.0  1.907200e+15    144.120000  1.05310  2.634100e+09  0.297820   \n",
       "...          ...           ...           ...      ...           ...       ...   \n",
       "493469  985000.0  6.079700e+15    508.820000 -1.68040  2.833700e+09  0.274810   \n",
       "493470   18004.0  6.073500e+14     -0.008665  2.14990  5.827800e+06  0.294350   \n",
       "493471  333050.0  2.351000e+15  33492.000000  1.23100  6.030700e+09  0.224030   \n",
       "493472  223980.0 -2.795300e+12     93.561000  7.23190  1.175200e+09  0.129590   \n",
       "493473   39185.0  1.489300e+14   -318.920000 -2.34520  5.552200e+09  0.013716   \n",
       "\n",
       "              f14       f15       f16     f17       f18      f19      f20  \\\n",
       "0        9.455600 -0.050305  1938.300  8.6331  4.060700  26.8670   -1.180   \n",
       "1       -0.012858 -0.019912    10.284  6.1872  1.041900   4.6404   31.877   \n",
       "2        2.455600       NaN    26.873  7.5463  1.996700   1.9526  817.760   \n",
       "3       10.370000 -0.106260   533.840  7.8490  1.037900   8.0030   12.349   \n",
       "4        2.654800       NaN  1808.900  7.2783  3.975700      NaN      NaN   \n",
       "...           ...       ...       ...     ...       ...      ...      ...   \n",
       "493469  11.050000 -0.014169   400.140  5.7628 -0.001073   5.0498   13.743   \n",
       "493470  -0.004783  0.023644   596.510  7.9760  9.435700  21.0210  851.480   \n",
       "493471   0.180100  0.000926   226.660  6.7145  2.931500  13.8390      NaN   \n",
       "493472   6.032200  0.403760   725.680  7.6410  6.632600  24.2630   40.471   \n",
       "493473        NaN       NaN  1229.500  3.0770 -0.036249   2.0722  376.310   \n",
       "\n",
       "              f21     f22       f23      f24        f25           f26  \\\n",
       "0        10961.00  1.5397  135.3200 -1.49650   440.0800  2.590100e+12   \n",
       "1       123620.00  1.3951  125.8100  1.19890   136.4500  9.098100e+09   \n",
       "2        -2948.70  2.0054    1.6826  1.19680    74.6240 -3.273900e+10   \n",
       "3         -195.28  2.5598   92.1420  0.63789  1054.9000 -1.204100e+10   \n",
       "4        29520.00  3.4225   96.7250  0.79725   215.5700  1.732600e+13   \n",
       "...           ...     ...       ...      ...        ...           ...   \n",
       "493469     204.01  2.3786   -2.8254  1.02590   367.5300  1.891800e+10   \n",
       "493470   14510.00  2.4662   89.3290 -0.16624   949.4100  1.270600e+12   \n",
       "493471  128560.00  2.6174  104.0000  1.14650   394.1400  2.181700e+12   \n",
       "493472   -1252.90  2.5204   92.9100  1.47880     2.6615  2.289200e+13   \n",
       "493473     884.18  2.0137   88.7720  1.13980   700.3300  8.834800e+11   \n",
       "\n",
       "                 f27        f28       f29      f30       f31       f32  \\\n",
       "0       2.194200e+09  2968800.0  0.001431  13.3270  0.750500   18509.0   \n",
       "1       4.004100e+10  1564000.0  0.000204   3.1074  1.503300  238000.0   \n",
       "2       5.718900e+10    11058.0 -0.003097   8.0241  1.131800   27940.0   \n",
       "3       5.187300e+12  1475400.0  1.036500   1.1903  0.989410  301200.0   \n",
       "4       2.635200e+12  2161200.0  0.895470   6.8257  0.974130  142620.0   \n",
       "...              ...        ...       ...      ...       ...       ...   \n",
       "493469  9.730300e+11  6252900.0  0.898450   2.9181  0.712160   -3601.1   \n",
       "493470  1.358000e+11  1037100.0 -0.000373   4.4537 -0.007206   40413.0   \n",
       "493471  5.170600e+12  3314200.0 -0.002885   1.1085  1.041000   11661.0   \n",
       "493472  4.518200e+12   136650.0 -0.002484   9.6386  0.879300  507380.0   \n",
       "493473  3.820400e+10  3605800.0  0.094938  25.7170  0.838200   36862.0   \n",
       "\n",
       "              f33       f34           f35       f36      f37     f38  \\\n",
       "0        146820.0 -0.000276  1.090600e+16  1705.400   414.29  3.5392   \n",
       "1         21440.0 -0.001344  3.079400e+16   229.100   844.82  1.4680   \n",
       "2        862460.0 -0.002207  5.849100e+13  -897.840      NaN  1.3561   \n",
       "3             NaN -0.000007 -9.299200e+13   -10.818  1020.30  2.9553   \n",
       "4        231350.0  0.001257  1.012500e+16    51.508   293.76  1.3351   \n",
       "...           ...       ...           ...       ...      ...     ...   \n",
       "493469        NaN -0.002788  8.989500e+16   298.280   451.56  1.5524   \n",
       "493470  1143100.0  0.000631  2.432400e+15  -158.550   244.97  1.3334   \n",
       "493471   -50841.0  0.000345           NaN   -85.664   833.87  1.4733   \n",
       "493472   328640.0  0.002744  1.273900e+17   213.210   302.92  2.0736   \n",
       "493473   -51164.0  0.001486 -5.152300e+13  -325.980   439.93  2.6547   \n",
       "\n",
       "             f39       f40        f41       f42      f43       f44       f45  \\\n",
       "0       1888.000  0.968930    18.3880 -0.001583   7.7059    5.9325  0.025693   \n",
       "1       4726.500  0.915380    -1.5321  0.982600   7.1112    2.0797  0.042321   \n",
       "2       3063.400  0.086232    16.1060  0.001481  11.4760    5.3430  0.012162   \n",
       "3       3342.500 -0.000372    17.0110  0.095268   5.7448   15.8830  0.037934   \n",
       "4       3042.100  0.006791    94.8890  0.917090   8.7369       NaN  0.020281   \n",
       "...          ...       ...        ...       ...      ...       ...       ...   \n",
       "493469  4677.800  0.002761     1.9064 -0.005308   5.2825   15.0020  0.039006   \n",
       "493470  4061.900  0.904380  2034.0000  1.002000   8.9452  106.9600  0.034338   \n",
       "493471    67.176 -0.000486        NaN  0.403010   5.9226  124.4100  0.026442   \n",
       "493472  3682.200  0.916260    12.3700  0.001483   8.5201   20.2640  0.014469   \n",
       "493473   284.100  1.014500    17.4660  0.496280   6.0643       NaN  0.025139   \n",
       "\n",
       "           f46       f47      f48       f49       f50       f51      f52  \\\n",
       "0       4.5604  0.611220  10.7950  0.341930  0.235010       NaN  5237.70   \n",
       "1       4.2523  0.418710   5.4499  0.012737  0.386470    7.3082   283.21   \n",
       "2       4.1018 -0.882700   8.1228 -0.676690  0.337700   -1.0732  4097.00   \n",
       "3       4.4860 -0.889090   8.4384 -1.189800  0.001391       NaN   175.81   \n",
       "4       3.9115  0.656340   6.1410 -1.089600  0.247940    7.9704  2063.10   \n",
       "...        ...       ...      ...       ...       ...       ...      ...   \n",
       "493469  7.1087  1.274900   5.7706  0.476210  0.250880   15.0800   170.71   \n",
       "493470  4.3093 -0.586030   5.6538  0.026041  0.317080  -13.8920   388.66   \n",
       "493471  4.3073 -0.471110      NaN  0.018845  0.493510  191.0500  3749.10   \n",
       "493472  4.2466  1.056900   3.0724 -0.986830  0.387560  152.9600  7638.00   \n",
       "493473  3.5943  0.084528  12.2230  0.604590  0.432340  -19.8280   104.30   \n",
       "\n",
       "             f53     f54       f55       f56       f57       f58     f59  \\\n",
       "0        1.29610  163.66  0.403780  0.188600 -0.001446 -0.354160  6.6432   \n",
       "1       -0.92552  140.80  0.247390 -0.001656 -0.000975 -0.226290  2.4246   \n",
       "2       13.45800  159.24  0.322300  0.560090  0.000455 -0.160830  3.5753   \n",
       "3       67.13300  119.26  0.007034  0.460040 -0.000705 -0.391490  2.0888   \n",
       "4        0.80633  131.77  0.177960  0.989380  0.000344 -0.980270  2.3610   \n",
       "...          ...     ...       ...       ...       ...       ...     ...   \n",
       "493469   0.20867  163.79  0.271720  0.016176  0.000776 -0.081314  4.9563   \n",
       "493470  -0.90778  152.23  0.314990  0.251870  0.001857 -0.297560  5.4251   \n",
       "493471   2.71000  118.64  0.240610  0.103870  0.001757 -0.245520  7.5606   \n",
       "493472   1.11900  140.13  0.185590  0.525850  0.002859 -0.118900  5.6682   \n",
       "493473   2.75040  143.09  0.015164  0.735670 -0.000728 -0.124340  1.4604   \n",
       "\n",
       "             f60       f61           f62       f63       f64      f65  \\\n",
       "0       0.305340  0.514020  1.907300e+09  29.86100  0.965010   1797.2   \n",
       "1       0.771470  0.011613  1.803700e+09  64.60400  0.262650   4455.0   \n",
       "2       0.609700  0.028301  5.271300e+08  14.45400  0.115490  14605.0   \n",
       "3       0.797900  0.135920  4.011100e+09  63.06300  0.033075  75194.0   \n",
       "4       0.580300  0.465770  5.702500e+09  23.73800 -0.000847  75843.0   \n",
       "...          ...       ...           ...       ...       ...      ...   \n",
       "493469  0.564300  0.243220  1.800700e+09  40.73900  0.509600  78305.0   \n",
       "493470  0.149990  0.597710  2.804100e+07   0.44526  0.005371   8058.6   \n",
       "493471  0.555610  0.007351  1.573900e+08  34.59000  0.020350  13178.0   \n",
       "493472  0.024169  0.124910  2.587700e+08   8.64640  0.684810  79834.0   \n",
       "493473  0.512610  0.006379  1.627700e+08  31.90700  0.340740  73658.0   \n",
       "\n",
       "              f66       f67      f68     f69       f70     f71       f72  \\\n",
       "0        72.17800  108.6200   1.9799  1.2907  0.995190  1.3228   827.340   \n",
       "1        78.33900  745.5100   2.9069  1.4826  1.005100  1.4974    84.446   \n",
       "2        36.99200   -9.6391  64.2670     NaN  0.992780  2.5891   430.400   \n",
       "3       103.97000  -15.4820   2.9432  1.1804  1.007000  2.1572  1251.500   \n",
       "4        73.73700       NaN  64.5910  1.1029  0.989850  1.3446   519.200   \n",
       "...           ...       ...      ...     ...       ...     ...       ...   \n",
       "493469   95.20500  471.4200  74.8540  1.2180  0.994570  1.6502    19.104   \n",
       "493470   -0.35459  212.8600   6.8051  1.2022  0.993000  1.5450   436.150   \n",
       "493471  101.02000   43.5600  86.0370  1.3538 -0.003483  1.7268   403.800   \n",
       "493472  132.24000  183.7300  10.2410  1.3437  0.996600  1.7392   397.100   \n",
       "493473   89.50900   97.4900  85.9730  1.1981  0.991390  1.4324   995.750   \n",
       "\n",
       "                 f73           f74       f75     f76       f77        f78  \\\n",
       "0       7.779900e+14  4.129900e+10  0.006994  6.9835  43956.00   1978.200   \n",
       "1       3.505600e+15  2.242300e+09  0.896300  4.6749  17713.00   9003.100   \n",
       "2      -4.453500e+13  5.144900e+12  0.099591  6.5516   1887.50  43319.000   \n",
       "3       1.894700e+15  1.077000e+10  0.992250  4.5331  14348.00   1575.700   \n",
       "4       5.693200e+14  2.869600e+11  0.011649  6.0236   1969.80   1967.600   \n",
       "...              ...           ...       ...     ...       ...        ...   \n",
       "493469  2.240300e+15  1.824400e+10  0.089590  7.2403    215.92   3075.300   \n",
       "493470  4.098900e+15  1.414100e+12  0.964410  4.8847  12826.00  13172.000   \n",
       "493471  7.337800e+12  5.792800e+12  0.020537  9.8688     28.89   5791.800   \n",
       "493472 -3.257100e+12 -6.842900e+09  0.093402  6.5243   3834.00  22383.000   \n",
       "493473  2.823400e+14  6.340900e+12 -0.002091  7.0547    903.15     91.356   \n",
       "\n",
       "             f79       f80     f81           f82        f83        f84  \\\n",
       "0        5.50840 -0.001081  6.1244  1.231800e+11  275.92000  5308500.0   \n",
       "1       -4.35460  0.254100  6.9191  1.832400e+11    9.65100    32800.0   \n",
       "2        4.39310  0.260260  6.1052  1.013300e+11  357.27000  1476600.0   \n",
       "3        9.81050  0.372830  1.5606  1.835400e+10   -3.42980  6485700.0   \n",
       "4            NaN  0.085690  1.5846  3.825200e+10  130.70000   102100.0   \n",
       "...          ...       ...     ...           ...        ...        ...   \n",
       "493469  -1.84160  0.141580  2.4004  6.137600e+09   39.73500    75812.0   \n",
       "493470 -14.27800  0.265390  1.9843  2.423700e+11  676.62000    21457.0   \n",
       "493471   7.77390  0.315980  1.4057  1.027400e+11  285.22000   379880.0   \n",
       "493472  -0.47804  0.245130  3.0052  2.048200e+11   -0.15322   347000.0   \n",
       "493473   4.33650  0.189050  2.9926  6.006600e+09  344.23000    42794.0   \n",
       "\n",
       "             f85           f86      f87       f88      f89      f90      f91  \\\n",
       "0       1704.000  5.022400e+10  53.3980   -2.2012   6871.0   3.8862 -0.00558   \n",
       "1       1480.600  2.300600e+10  44.0510  205.6900   4295.3  13.3880  0.46843   \n",
       "2         90.845  1.306200e+09   2.3731  391.3700   2965.3      NaN  0.49459   \n",
       "3       2120.000  3.081200e+10  34.0560  157.4300   3724.5   8.4211  0.40778   \n",
       "4       1951.800  1.142800e+10  58.5660  176.8300   1279.0   4.9662  0.47912   \n",
       "...          ...           ...      ...       ...      ...      ...      ...   \n",
       "493469  2113.900  7.050100e+10  28.5400   81.6610   4997.2  17.2460  0.31933   \n",
       "493470  2091.900  1.970600e+10  31.5060  188.6700   1569.2   5.4486  0.47033   \n",
       "493471    35.623  6.274400e+10  36.5470  115.3500  10423.0   3.3315  0.39220   \n",
       "493472  2146.800  6.722200e+10   2.5834  451.0500   6128.3   5.2362  0.36444   \n",
       "493473  1928.200  7.394200e+10  69.0480  212.9400      NaN   2.9230  0.28574   \n",
       "\n",
       "              f92       f93       f94       f95        f96      f97  \\\n",
       "0        5252.100  166.6900  1.607400   0.66534   7768.900  0.99662   \n",
       "1         754.610   83.2330  1.189000  29.55000   7343.700  0.99815   \n",
       "2          43.524  138.5200  1.107900   0.91948     47.915      NaN   \n",
       "3        2971.200  204.7000 -0.979980   9.94050  12011.000  0.99898   \n",
       "4         -70.278   10.8870  1.143400   6.19120    197.470      NaN   \n",
       "...           ...       ...       ...       ...        ...      ...   \n",
       "493469  17181.000    7.3211  1.026800  41.03600     60.576  0.99962   \n",
       "493470    169.150  129.9900 -0.286240   1.36920   9618.300  0.99864   \n",
       "493471   4995.600   38.6460 -0.012972  23.89300    342.900  1.00040   \n",
       "493472    594.880   71.7380  0.024923  28.52200  22863.000  0.99832   \n",
       "493473     50.874  296.8300       NaN   9.99580    324.190  1.00090   \n",
       "\n",
       "                 f98     f99      f100      f101       f102     f103  \\\n",
       "0       1.125700e+11  2.2432  0.934160   0.65056    94569.0   21.471   \n",
       "1       4.877700e+13  1.2708 -0.000969   5.29520     6779.0  227.720   \n",
       "2       1.510500e+12  3.4663  0.560950   4.13090    95531.0   39.486   \n",
       "3       5.063400e+13  1.2261  0.250200   0.72974   373690.0  194.650   \n",
       "4       1.574800e+13  1.0083  0.339530  13.48600   201300.0   38.842   \n",
       "...              ...     ...       ...       ...        ...      ...   \n",
       "493469  3.176100e+12  1.1408  0.354360  38.74500     3645.4   21.704   \n",
       "493470 -3.458700e+10  1.3751  0.238700  34.74900   604250.0  -54.677   \n",
       "493471  8.181500e+11  1.4087  0.797330  13.03100  1209100.0   68.528   \n",
       "493472  5.116900e+13  1.2432  0.057941   0.19997   144140.0   30.394   \n",
       "493473 -1.136900e+10  3.1286  0.154810  30.78400   557030.0   84.958   \n",
       "\n",
       "            f104      f105      f106      f107          f108      f109  \\\n",
       "0       8214.100  0.288010  0.097826  0.001071  1.412400e+09  0.110930   \n",
       "1         34.342  0.340300  0.143370  0.049276  1.903200e+09  0.976730   \n",
       "2        -83.148  0.084881  0.032222  0.001668  1.436500e+07  0.201020   \n",
       "3        120.930  0.260710  0.234240 -0.002794  1.442300e+09 -0.011820   \n",
       "4        324.000  0.238250  0.141550  0.002208  5.830700e+09  0.927390   \n",
       "...          ...       ...       ...       ...           ...       ...   \n",
       "493469   907.590  0.040616  0.198570  0.003273  5.782200e+07  0.249550   \n",
       "493470  8563.400  0.073362  0.181930  0.046054  1.503400e+09  0.017970   \n",
       "493471   260.560  0.109100  0.346760  0.000079  1.920600e+09  0.013841   \n",
       "493472   471.920  0.002906  0.197590  0.042522  3.240100e+09  0.858730   \n",
       "493473   176.550  0.258370  0.071935 -0.002442  7.436200e+07  0.889390   \n",
       "\n",
       "           f110    f111       f112      f113      f114    f115          f116  \\\n",
       "0      -12.2280  1.7482    1.90960  -7.11570   4378.80  1.2096  8.613400e+14   \n",
       "1      -56.7580  4.1684    0.34808   4.14200    913.23  1.2464  7.575100e+15   \n",
       "2       -5.7688  1.2042    0.26290   8.13120  45119.00  1.1764  3.218100e+14   \n",
       "3      -34.8580  2.0694    0.79631 -16.33600   4952.40  1.1784  4.533000e+12   \n",
       "4      -13.6410  1.5298    1.14640  -0.43124   3856.50  1.4830 -8.991300e+12   \n",
       "...         ...     ...        ...       ...       ...     ...           ...   \n",
       "493469 -17.5100  2.3325    0.11226  -5.92380       NaN  1.1559  8.163900e+16   \n",
       "493470  -7.8690  1.7005   97.81300   4.37930  -2432.00  1.0707  4.691800e+16   \n",
       "493471  -5.3824  1.6827        NaN   8.06330   2471.40  1.1725  7.900900e+16   \n",
       "493472  -4.2416  1.3531  155.21000  13.96300    -11.44  1.1946 -1.770600e+14   \n",
       "493473 -13.9390  1.4480   -1.51290 -15.43600    662.46  1.1778  2.459300e+15   \n",
       "\n",
       "           f117     f118  claim  \n",
       "0        140.10  1.01770    1.0  \n",
       "1       1861.00  0.28359    0.0  \n",
       "2       3838.20  0.40690    1.0  \n",
       "3       4889.10  0.51486    1.0  \n",
       "4           NaN  0.23049    1.0  \n",
       "...         ...      ...    ...  \n",
       "493469   857.09  1.56330    NaN  \n",
       "493470  7497.10  0.67075    NaN  \n",
       "493471  2904.60  0.18005    NaN  \n",
       "493472  6763.10  0.33223    NaN  \n",
       "493473  8770.00  0.95503    NaN  \n",
       "\n",
       "[1451393 rows x 119 columns]>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_data.describe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "25e00eed",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-09-26T11:49:42.962186Z",
     "iopub.status.busy": "2021-09-26T11:49:42.961282Z",
     "iopub.status.idle": "2021-09-26T11:49:42.964947Z",
     "shell.execute_reply": "2021-09-26T11:49:42.965630Z",
     "shell.execute_reply.started": "2021-09-26T10:46:58.340637Z"
    },
    "papermill": {
     "duration": 0.23135,
     "end_time": "2021-09-26T11:49:42.965795",
     "exception": false,
     "start_time": "2021-09-26T11:49:42.734445",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "train2 = df_data[:len(train)]\n",
    "test2 = df_data[len(train):]\n",
    "test2.drop(columns = 'claim', inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e63c7a38",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-09-26T11:49:43.157346Z",
     "iopub.status.busy": "2021-09-26T11:49:43.156090Z",
     "iopub.status.idle": "2021-09-26T11:51:48.922040Z",
     "shell.execute_reply": "2021-09-26T11:51:48.923418Z",
     "shell.execute_reply.started": "2021-09-26T10:46:58.484772Z"
    },
    "papermill": {
     "duration": 125.866025,
     "end_time": "2021-09-26T11:51:48.923707",
     "exception": false,
     "start_time": "2021-09-26T11:49:43.057682",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "#T_f9c18_row5_col1,#T_f9c18_row18_col1,#T_f9c18_row19_col1,#T_f9c18_row29_col1,#T_f9c18_row44_col1{\n",
       "            background-color:  lightgreen;\n",
       "        }</style><table id=\"T_f9c18_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Description</th>        <th class=\"col_heading level0 col1\" >Value</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_f9c18_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_f9c18_row0_col0\" class=\"data row0 col0\" >session_id</td>\n",
       "                        <td id=\"T_f9c18_row0_col1\" class=\"data row0 col1\" >42</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_f9c18_row1_col0\" class=\"data row1 col0\" >Target</td>\n",
       "                        <td id=\"T_f9c18_row1_col1\" class=\"data row1 col1\" >claim</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_f9c18_row2_col0\" class=\"data row2 col0\" >Target Type</td>\n",
       "                        <td id=\"T_f9c18_row2_col1\" class=\"data row2 col1\" >Binary</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_f9c18_row3_col0\" class=\"data row3 col0\" >Label Encoded</td>\n",
       "                        <td id=\"T_f9c18_row3_col1\" class=\"data row3 col1\" >0.0: 0, 1.0: 1</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_f9c18_row4_col0\" class=\"data row4 col0\" >Original Data</td>\n",
       "                        <td id=\"T_f9c18_row4_col1\" class=\"data row4 col1\" >(957919, 119)</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_f9c18_row5_col0\" class=\"data row5 col0\" >Missing Values</td>\n",
       "                        <td id=\"T_f9c18_row5_col1\" class=\"data row5 col1\" >True</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_f9c18_row6_col0\" class=\"data row6 col0\" >Numeric Features</td>\n",
       "                        <td id=\"T_f9c18_row6_col1\" class=\"data row6 col1\" >118</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_f9c18_row7_col0\" class=\"data row7 col0\" >Categorical Features</td>\n",
       "                        <td id=\"T_f9c18_row7_col1\" class=\"data row7 col1\" >0</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_f9c18_row8_col0\" class=\"data row8 col0\" >Ordinal Features</td>\n",
       "                        <td id=\"T_f9c18_row8_col1\" class=\"data row8 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_f9c18_row9_col0\" class=\"data row9 col0\" >High Cardinality Features</td>\n",
       "                        <td id=\"T_f9c18_row9_col1\" class=\"data row9 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_f9c18_row10_col0\" class=\"data row10 col0\" >High Cardinality Method</td>\n",
       "                        <td id=\"T_f9c18_row10_col1\" class=\"data row10 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_f9c18_row11_col0\" class=\"data row11 col0\" >Transformed Train Set</td>\n",
       "                        <td id=\"T_f9c18_row11_col1\" class=\"data row11 col1\" >(670543, 118)</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_f9c18_row12_col0\" class=\"data row12 col0\" >Transformed Test Set</td>\n",
       "                        <td id=\"T_f9c18_row12_col1\" class=\"data row12 col1\" >(287376, 118)</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_f9c18_row13_col0\" class=\"data row13 col0\" >Shuffle Train-Test</td>\n",
       "                        <td id=\"T_f9c18_row13_col1\" class=\"data row13 col1\" >True</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_f9c18_row14_col0\" class=\"data row14 col0\" >Stratify Train-Test</td>\n",
       "                        <td id=\"T_f9c18_row14_col1\" class=\"data row14 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "                        <td id=\"T_f9c18_row15_col0\" class=\"data row15 col0\" >Fold Generator</td>\n",
       "                        <td id=\"T_f9c18_row15_col1\" class=\"data row15 col1\" >StratifiedKFold</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "                        <td id=\"T_f9c18_row16_col0\" class=\"data row16 col0\" >Fold Number</td>\n",
       "                        <td id=\"T_f9c18_row16_col1\" class=\"data row16 col1\" >3</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "                        <td id=\"T_f9c18_row17_col0\" class=\"data row17 col0\" >CPU Jobs</td>\n",
       "                        <td id=\"T_f9c18_row17_col1\" class=\"data row17 col1\" >-1</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "                        <td id=\"T_f9c18_row18_col0\" class=\"data row18 col0\" >Use GPU</td>\n",
       "                        <td id=\"T_f9c18_row18_col1\" class=\"data row18 col1\" >True</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "                        <td id=\"T_f9c18_row19_col0\" class=\"data row19 col0\" >Log Experiment</td>\n",
       "                        <td id=\"T_f9c18_row19_col1\" class=\"data row19 col1\" >True</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "                        <td id=\"T_f9c18_row20_col0\" class=\"data row20 col0\" >Experiment Name</td>\n",
       "                        <td id=\"T_f9c18_row20_col1\" class=\"data row20 col1\" >clf-default-name</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "                        <td id=\"T_f9c18_row21_col0\" class=\"data row21 col0\" >USI</td>\n",
       "                        <td id=\"T_f9c18_row21_col1\" class=\"data row21 col1\" >63ec</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "                        <td id=\"T_f9c18_row22_col0\" class=\"data row22 col0\" >Imputation Type</td>\n",
       "                        <td id=\"T_f9c18_row22_col1\" class=\"data row22 col1\" >simple</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "                        <td id=\"T_f9c18_row23_col0\" class=\"data row23 col0\" >Iterative Imputation Iteration</td>\n",
       "                        <td id=\"T_f9c18_row23_col1\" class=\"data row23 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "                        <td id=\"T_f9c18_row24_col0\" class=\"data row24 col0\" >Numeric Imputer</td>\n",
       "                        <td id=\"T_f9c18_row24_col1\" class=\"data row24 col1\" >mean</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "                        <td id=\"T_f9c18_row25_col0\" class=\"data row25 col0\" >Iterative Imputation Numeric Model</td>\n",
       "                        <td id=\"T_f9c18_row25_col1\" class=\"data row25 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "                        <td id=\"T_f9c18_row26_col0\" class=\"data row26 col0\" >Categorical Imputer</td>\n",
       "                        <td id=\"T_f9c18_row26_col1\" class=\"data row26 col1\" >constant</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "                        <td id=\"T_f9c18_row27_col0\" class=\"data row27 col0\" >Iterative Imputation Categorical Model</td>\n",
       "                        <td id=\"T_f9c18_row27_col1\" class=\"data row27 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "                        <td id=\"T_f9c18_row28_col0\" class=\"data row28 col0\" >Unknown Categoricals Handling</td>\n",
       "                        <td id=\"T_f9c18_row28_col1\" class=\"data row28 col1\" >least_frequent</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "                        <td id=\"T_f9c18_row29_col0\" class=\"data row29 col0\" >Normalize</td>\n",
       "                        <td id=\"T_f9c18_row29_col1\" class=\"data row29 col1\" >True</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row30\" class=\"row_heading level0 row30\" >30</th>\n",
       "                        <td id=\"T_f9c18_row30_col0\" class=\"data row30 col0\" >Normalize Method</td>\n",
       "                        <td id=\"T_f9c18_row30_col1\" class=\"data row30 col1\" >robust</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row31\" class=\"row_heading level0 row31\" >31</th>\n",
       "                        <td id=\"T_f9c18_row31_col0\" class=\"data row31 col0\" >Transformation</td>\n",
       "                        <td id=\"T_f9c18_row31_col1\" class=\"data row31 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row32\" class=\"row_heading level0 row32\" >32</th>\n",
       "                        <td id=\"T_f9c18_row32_col0\" class=\"data row32 col0\" >Transformation Method</td>\n",
       "                        <td id=\"T_f9c18_row32_col1\" class=\"data row32 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row33\" class=\"row_heading level0 row33\" >33</th>\n",
       "                        <td id=\"T_f9c18_row33_col0\" class=\"data row33 col0\" >PCA</td>\n",
       "                        <td id=\"T_f9c18_row33_col1\" class=\"data row33 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row34\" class=\"row_heading level0 row34\" >34</th>\n",
       "                        <td id=\"T_f9c18_row34_col0\" class=\"data row34 col0\" >PCA Method</td>\n",
       "                        <td id=\"T_f9c18_row34_col1\" class=\"data row34 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row35\" class=\"row_heading level0 row35\" >35</th>\n",
       "                        <td id=\"T_f9c18_row35_col0\" class=\"data row35 col0\" >PCA Components</td>\n",
       "                        <td id=\"T_f9c18_row35_col1\" class=\"data row35 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row36\" class=\"row_heading level0 row36\" >36</th>\n",
       "                        <td id=\"T_f9c18_row36_col0\" class=\"data row36 col0\" >Ignore Low Variance</td>\n",
       "                        <td id=\"T_f9c18_row36_col1\" class=\"data row36 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row37\" class=\"row_heading level0 row37\" >37</th>\n",
       "                        <td id=\"T_f9c18_row37_col0\" class=\"data row37 col0\" >Combine Rare Levels</td>\n",
       "                        <td id=\"T_f9c18_row37_col1\" class=\"data row37 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row38\" class=\"row_heading level0 row38\" >38</th>\n",
       "                        <td id=\"T_f9c18_row38_col0\" class=\"data row38 col0\" >Rare Level Threshold</td>\n",
       "                        <td id=\"T_f9c18_row38_col1\" class=\"data row38 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row39\" class=\"row_heading level0 row39\" >39</th>\n",
       "                        <td id=\"T_f9c18_row39_col0\" class=\"data row39 col0\" >Numeric Binning</td>\n",
       "                        <td id=\"T_f9c18_row39_col1\" class=\"data row39 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row40\" class=\"row_heading level0 row40\" >40</th>\n",
       "                        <td id=\"T_f9c18_row40_col0\" class=\"data row40 col0\" >Remove Outliers</td>\n",
       "                        <td id=\"T_f9c18_row40_col1\" class=\"data row40 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row41\" class=\"row_heading level0 row41\" >41</th>\n",
       "                        <td id=\"T_f9c18_row41_col0\" class=\"data row41 col0\" >Outliers Threshold</td>\n",
       "                        <td id=\"T_f9c18_row41_col1\" class=\"data row41 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row42\" class=\"row_heading level0 row42\" >42</th>\n",
       "                        <td id=\"T_f9c18_row42_col0\" class=\"data row42 col0\" >Remove Multicollinearity</td>\n",
       "                        <td id=\"T_f9c18_row42_col1\" class=\"data row42 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row43\" class=\"row_heading level0 row43\" >43</th>\n",
       "                        <td id=\"T_f9c18_row43_col0\" class=\"data row43 col0\" >Multicollinearity Threshold</td>\n",
       "                        <td id=\"T_f9c18_row43_col1\" class=\"data row43 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row44\" class=\"row_heading level0 row44\" >44</th>\n",
       "                        <td id=\"T_f9c18_row44_col0\" class=\"data row44 col0\" >Remove Perfect Collinearity</td>\n",
       "                        <td id=\"T_f9c18_row44_col1\" class=\"data row44 col1\" >True</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row45\" class=\"row_heading level0 row45\" >45</th>\n",
       "                        <td id=\"T_f9c18_row45_col0\" class=\"data row45 col0\" >Clustering</td>\n",
       "                        <td id=\"T_f9c18_row45_col1\" class=\"data row45 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row46\" class=\"row_heading level0 row46\" >46</th>\n",
       "                        <td id=\"T_f9c18_row46_col0\" class=\"data row46 col0\" >Clustering Iteration</td>\n",
       "                        <td id=\"T_f9c18_row46_col1\" class=\"data row46 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row47\" class=\"row_heading level0 row47\" >47</th>\n",
       "                        <td id=\"T_f9c18_row47_col0\" class=\"data row47 col0\" >Polynomial Features</td>\n",
       "                        <td id=\"T_f9c18_row47_col1\" class=\"data row47 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row48\" class=\"row_heading level0 row48\" >48</th>\n",
       "                        <td id=\"T_f9c18_row48_col0\" class=\"data row48 col0\" >Polynomial Degree</td>\n",
       "                        <td id=\"T_f9c18_row48_col1\" class=\"data row48 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row49\" class=\"row_heading level0 row49\" >49</th>\n",
       "                        <td id=\"T_f9c18_row49_col0\" class=\"data row49 col0\" >Trignometry Features</td>\n",
       "                        <td id=\"T_f9c18_row49_col1\" class=\"data row49 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row50\" class=\"row_heading level0 row50\" >50</th>\n",
       "                        <td id=\"T_f9c18_row50_col0\" class=\"data row50 col0\" >Polynomial Threshold</td>\n",
       "                        <td id=\"T_f9c18_row50_col1\" class=\"data row50 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row51\" class=\"row_heading level0 row51\" >51</th>\n",
       "                        <td id=\"T_f9c18_row51_col0\" class=\"data row51 col0\" >Group Features</td>\n",
       "                        <td id=\"T_f9c18_row51_col1\" class=\"data row51 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row52\" class=\"row_heading level0 row52\" >52</th>\n",
       "                        <td id=\"T_f9c18_row52_col0\" class=\"data row52 col0\" >Feature Selection</td>\n",
       "                        <td id=\"T_f9c18_row52_col1\" class=\"data row52 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row53\" class=\"row_heading level0 row53\" >53</th>\n",
       "                        <td id=\"T_f9c18_row53_col0\" class=\"data row53 col0\" >Feature Selection Method</td>\n",
       "                        <td id=\"T_f9c18_row53_col1\" class=\"data row53 col1\" >classic</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row54\" class=\"row_heading level0 row54\" >54</th>\n",
       "                        <td id=\"T_f9c18_row54_col0\" class=\"data row54 col0\" >Features Selection Threshold</td>\n",
       "                        <td id=\"T_f9c18_row54_col1\" class=\"data row54 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row55\" class=\"row_heading level0 row55\" >55</th>\n",
       "                        <td id=\"T_f9c18_row55_col0\" class=\"data row55 col0\" >Feature Interaction</td>\n",
       "                        <td id=\"T_f9c18_row55_col1\" class=\"data row55 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row56\" class=\"row_heading level0 row56\" >56</th>\n",
       "                        <td id=\"T_f9c18_row56_col0\" class=\"data row56 col0\" >Feature Ratio</td>\n",
       "                        <td id=\"T_f9c18_row56_col1\" class=\"data row56 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row57\" class=\"row_heading level0 row57\" >57</th>\n",
       "                        <td id=\"T_f9c18_row57_col0\" class=\"data row57 col0\" >Interaction Threshold</td>\n",
       "                        <td id=\"T_f9c18_row57_col1\" class=\"data row57 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row58\" class=\"row_heading level0 row58\" >58</th>\n",
       "                        <td id=\"T_f9c18_row58_col0\" class=\"data row58 col0\" >Fix Imbalance</td>\n",
       "                        <td id=\"T_f9c18_row58_col1\" class=\"data row58 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f9c18_level0_row59\" class=\"row_heading level0 row59\" >59</th>\n",
       "                        <td id=\"T_f9c18_row59_col0\" class=\"data row59 col0\" >Fix Imbalance Method</td>\n",
       "                        <td id=\"T_f9c18_row59_col1\" class=\"data row59 col1\" >SMOTE</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f90695bda10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pycaret.classification import *\n",
    "clf = setup(data=train2, target = 'claim', session_id=42, log_experiment=True,numeric_imputation = 'mean',normalize = True,\n",
    "        normalize_method = 'robust',fold = 3,\n",
    "        silent= True,\n",
    "        use_gpu=True,)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "965b5795",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-09-26T11:51:49.349853Z",
     "iopub.status.busy": "2021-09-26T11:51:49.348948Z",
     "iopub.status.idle": "2021-09-26T11:54:28.210885Z",
     "shell.execute_reply": "2021-09-26T11:54:28.210362Z",
     "shell.execute_reply.started": "2021-09-26T10:49:04.297354Z"
    },
    "papermill": {
     "duration": 159.040311,
     "end_time": "2021-09-26T11:54:28.211020",
     "exception": false,
     "start_time": "2021-09-26T11:51:49.170709",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "#T_73cde_row5_col0,#T_73cde_row5_col1,#T_73cde_row5_col2,#T_73cde_row5_col3,#T_73cde_row5_col4,#T_73cde_row5_col5,#T_73cde_row5_col6{\n",
       "            background:  yellow;\n",
       "        }</style><table id=\"T_73cde_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Accuracy</th>        <th class=\"col_heading level0 col1\" >AUC</th>        <th class=\"col_heading level0 col2\" >Recall</th>        <th class=\"col_heading level0 col3\" >Prec.</th>        <th class=\"col_heading level0 col4\" >F1</th>        <th class=\"col_heading level0 col5\" >Kappa</th>        <th class=\"col_heading level0 col6\" >MCC</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_73cde_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_73cde_row0_col0\" class=\"data row0 col0\" >0.6839</td>\n",
       "                        <td id=\"T_73cde_row0_col1\" class=\"data row0 col1\" >0.7412</td>\n",
       "                        <td id=\"T_73cde_row0_col2\" class=\"data row0 col2\" >0.6257</td>\n",
       "                        <td id=\"T_73cde_row0_col3\" class=\"data row0 col3\" >0.7071</td>\n",
       "                        <td id=\"T_73cde_row0_col4\" class=\"data row0 col4\" >0.6639</td>\n",
       "                        <td id=\"T_73cde_row0_col5\" class=\"data row0 col5\" >0.3677</td>\n",
       "                        <td id=\"T_73cde_row0_col6\" class=\"data row0 col6\" >0.3702</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_73cde_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_73cde_row1_col0\" class=\"data row1 col0\" >0.6881</td>\n",
       "                        <td id=\"T_73cde_row1_col1\" class=\"data row1 col1\" >0.7468</td>\n",
       "                        <td id=\"T_73cde_row1_col2\" class=\"data row1 col2\" >0.6251</td>\n",
       "                        <td id=\"T_73cde_row1_col3\" class=\"data row1 col3\" >0.7142</td>\n",
       "                        <td id=\"T_73cde_row1_col4\" class=\"data row1 col4\" >0.6667</td>\n",
       "                        <td id=\"T_73cde_row1_col5\" class=\"data row1 col5\" >0.3761</td>\n",
       "                        <td id=\"T_73cde_row1_col6\" class=\"data row1 col6\" >0.3791</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_73cde_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_73cde_row2_col0\" class=\"data row2 col0\" >0.6865</td>\n",
       "                        <td id=\"T_73cde_row2_col1\" class=\"data row2 col1\" >0.7451</td>\n",
       "                        <td id=\"T_73cde_row2_col2\" class=\"data row2 col2\" >0.6233</td>\n",
       "                        <td id=\"T_73cde_row2_col3\" class=\"data row2 col3\" >0.7125</td>\n",
       "                        <td id=\"T_73cde_row2_col4\" class=\"data row2 col4\" >0.6649</td>\n",
       "                        <td id=\"T_73cde_row2_col5\" class=\"data row2 col5\" >0.3729</td>\n",
       "                        <td id=\"T_73cde_row2_col6\" class=\"data row2 col6\" >0.3759</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_73cde_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_73cde_row3_col0\" class=\"data row3 col0\" >0.6867</td>\n",
       "                        <td id=\"T_73cde_row3_col1\" class=\"data row3 col1\" >0.7451</td>\n",
       "                        <td id=\"T_73cde_row3_col2\" class=\"data row3 col2\" >0.6260</td>\n",
       "                        <td id=\"T_73cde_row3_col3\" class=\"data row3 col3\" >0.7115</td>\n",
       "                        <td id=\"T_73cde_row3_col4\" class=\"data row3 col4\" >0.6660</td>\n",
       "                        <td id=\"T_73cde_row3_col5\" class=\"data row3 col5\" >0.3733</td>\n",
       "                        <td id=\"T_73cde_row3_col6\" class=\"data row3 col6\" >0.3760</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_73cde_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_73cde_row4_col0\" class=\"data row4 col0\" >0.6850</td>\n",
       "                        <td id=\"T_73cde_row4_col1\" class=\"data row4 col1\" >0.7429</td>\n",
       "                        <td id=\"T_73cde_row4_col2\" class=\"data row4 col2\" >0.6239</td>\n",
       "                        <td id=\"T_73cde_row4_col3\" class=\"data row4 col3\" >0.7097</td>\n",
       "                        <td id=\"T_73cde_row4_col4\" class=\"data row4 col4\" >0.6640</td>\n",
       "                        <td id=\"T_73cde_row4_col5\" class=\"data row4 col5\" >0.3698</td>\n",
       "                        <td id=\"T_73cde_row4_col6\" class=\"data row4 col6\" >0.3726</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_73cde_level0_row5\" class=\"row_heading level0 row5\" >Mean</th>\n",
       "                        <td id=\"T_73cde_row5_col0\" class=\"data row5 col0\" >0.6861</td>\n",
       "                        <td id=\"T_73cde_row5_col1\" class=\"data row5 col1\" >0.7442</td>\n",
       "                        <td id=\"T_73cde_row5_col2\" class=\"data row5 col2\" >0.6248</td>\n",
       "                        <td id=\"T_73cde_row5_col3\" class=\"data row5 col3\" >0.7110</td>\n",
       "                        <td id=\"T_73cde_row5_col4\" class=\"data row5 col4\" >0.6651</td>\n",
       "                        <td id=\"T_73cde_row5_col5\" class=\"data row5 col5\" >0.3720</td>\n",
       "                        <td id=\"T_73cde_row5_col6\" class=\"data row5 col6\" >0.3747</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_73cde_level0_row6\" class=\"row_heading level0 row6\" >SD</th>\n",
       "                        <td id=\"T_73cde_row6_col0\" class=\"data row6 col0\" >0.0015</td>\n",
       "                        <td id=\"T_73cde_row6_col1\" class=\"data row6 col1\" >0.0020</td>\n",
       "                        <td id=\"T_73cde_row6_col2\" class=\"data row6 col2\" >0.0010</td>\n",
       "                        <td id=\"T_73cde_row6_col3\" class=\"data row6 col3\" >0.0024</td>\n",
       "                        <td id=\"T_73cde_row6_col4\" class=\"data row6 col4\" >0.0011</td>\n",
       "                        <td id=\"T_73cde_row6_col5\" class=\"data row6 col5\" >0.0029</td>\n",
       "                        <td id=\"T_73cde_row6_col6\" class=\"data row6 col6\" >0.0031</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f906a997e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cat = create_model(estimator = 'catboost', fold = 5)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "7ec30110",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-09-26T11:54:28.428853Z",
     "iopub.status.busy": "2021-09-26T11:54:28.428062Z",
     "iopub.status.idle": "2021-09-26T11:56:19.351078Z",
     "shell.execute_reply": "2021-09-26T11:56:19.351492Z",
     "shell.execute_reply.started": "2021-09-26T10:51:45.193904Z"
    },
    "papermill": {
     "duration": 111.02172,
     "end_time": "2021-09-26T11:56:19.351676",
     "exception": false,
     "start_time": "2021-09-26T11:54:28.329956",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "#T_c829e_row5_col0,#T_c829e_row5_col1,#T_c829e_row5_col2,#T_c829e_row5_col3,#T_c829e_row5_col4,#T_c829e_row5_col5,#T_c829e_row5_col6{\n",
       "            background:  yellow;\n",
       "        }</style><table id=\"T_c829e_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Accuracy</th>        <th class=\"col_heading level0 col1\" >AUC</th>        <th class=\"col_heading level0 col2\" >Recall</th>        <th class=\"col_heading level0 col3\" >Prec.</th>        <th class=\"col_heading level0 col4\" >F1</th>        <th class=\"col_heading level0 col5\" >Kappa</th>        <th class=\"col_heading level0 col6\" >MCC</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_c829e_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_c829e_row0_col0\" class=\"data row0 col0\" >0.7010</td>\n",
       "                        <td id=\"T_c829e_row0_col1\" class=\"data row0 col1\" >0.7612</td>\n",
       "                        <td id=\"T_c829e_row0_col2\" class=\"data row0 col2\" >0.6122</td>\n",
       "                        <td id=\"T_c829e_row0_col3\" class=\"data row0 col3\" >0.7433</td>\n",
       "                        <td id=\"T_c829e_row0_col4\" class=\"data row0 col4\" >0.6714</td>\n",
       "                        <td id=\"T_c829e_row0_col5\" class=\"data row0 col5\" >0.4019</td>\n",
       "                        <td id=\"T_c829e_row0_col6\" class=\"data row0 col6\" >0.4082</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_c829e_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_c829e_row1_col0\" class=\"data row1 col0\" >0.7016</td>\n",
       "                        <td id=\"T_c829e_row1_col1\" class=\"data row1 col1\" >0.7638</td>\n",
       "                        <td id=\"T_c829e_row1_col2\" class=\"data row1 col2\" >0.6142</td>\n",
       "                        <td id=\"T_c829e_row1_col3\" class=\"data row1 col3\" >0.7432</td>\n",
       "                        <td id=\"T_c829e_row1_col4\" class=\"data row1 col4\" >0.6726</td>\n",
       "                        <td id=\"T_c829e_row1_col5\" class=\"data row1 col5\" >0.4030</td>\n",
       "                        <td id=\"T_c829e_row1_col6\" class=\"data row1 col6\" >0.4092</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_c829e_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_c829e_row2_col0\" class=\"data row2 col0\" >0.7027</td>\n",
       "                        <td id=\"T_c829e_row2_col1\" class=\"data row2 col1\" >0.7642</td>\n",
       "                        <td id=\"T_c829e_row2_col2\" class=\"data row2 col2\" >0.6163</td>\n",
       "                        <td id=\"T_c829e_row2_col3\" class=\"data row2 col3\" >0.7440</td>\n",
       "                        <td id=\"T_c829e_row2_col4\" class=\"data row2 col4\" >0.6741</td>\n",
       "                        <td id=\"T_c829e_row2_col5\" class=\"data row2 col5\" >0.4053</td>\n",
       "                        <td id=\"T_c829e_row2_col6\" class=\"data row2 col6\" >0.4113</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_c829e_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_c829e_row3_col0\" class=\"data row3 col0\" >0.7029</td>\n",
       "                        <td id=\"T_c829e_row3_col1\" class=\"data row3 col1\" >0.7639</td>\n",
       "                        <td id=\"T_c829e_row3_col2\" class=\"data row3 col2\" >0.6152</td>\n",
       "                        <td id=\"T_c829e_row3_col3\" class=\"data row3 col3\" >0.7448</td>\n",
       "                        <td id=\"T_c829e_row3_col4\" class=\"data row3 col4\" >0.6738</td>\n",
       "                        <td id=\"T_c829e_row3_col5\" class=\"data row3 col5\" >0.4055</td>\n",
       "                        <td id=\"T_c829e_row3_col6\" class=\"data row3 col6\" >0.4117</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_c829e_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_c829e_row4_col0\" class=\"data row4 col0\" >0.7013</td>\n",
       "                        <td id=\"T_c829e_row4_col1\" class=\"data row4 col1\" >0.7608</td>\n",
       "                        <td id=\"T_c829e_row4_col2\" class=\"data row4 col2\" >0.6141</td>\n",
       "                        <td id=\"T_c829e_row4_col3\" class=\"data row4 col3\" >0.7426</td>\n",
       "                        <td id=\"T_c829e_row4_col4\" class=\"data row4 col4\" >0.6723</td>\n",
       "                        <td id=\"T_c829e_row4_col5\" class=\"data row4 col5\" >0.4023</td>\n",
       "                        <td id=\"T_c829e_row4_col6\" class=\"data row4 col6\" >0.4085</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_c829e_level0_row5\" class=\"row_heading level0 row5\" >Mean</th>\n",
       "                        <td id=\"T_c829e_row5_col0\" class=\"data row5 col0\" >0.7019</td>\n",
       "                        <td id=\"T_c829e_row5_col1\" class=\"data row5 col1\" >0.7628</td>\n",
       "                        <td id=\"T_c829e_row5_col2\" class=\"data row5 col2\" >0.6144</td>\n",
       "                        <td id=\"T_c829e_row5_col3\" class=\"data row5 col3\" >0.7436</td>\n",
       "                        <td id=\"T_c829e_row5_col4\" class=\"data row5 col4\" >0.6728</td>\n",
       "                        <td id=\"T_c829e_row5_col5\" class=\"data row5 col5\" >0.4036</td>\n",
       "                        <td id=\"T_c829e_row5_col6\" class=\"data row5 col6\" >0.4098</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_c829e_level0_row6\" class=\"row_heading level0 row6\" >SD</th>\n",
       "                        <td id=\"T_c829e_row6_col0\" class=\"data row6 col0\" >0.0008</td>\n",
       "                        <td id=\"T_c829e_row6_col1\" class=\"data row6 col1\" >0.0015</td>\n",
       "                        <td id=\"T_c829e_row6_col2\" class=\"data row6 col2\" >0.0014</td>\n",
       "                        <td id=\"T_c829e_row6_col3\" class=\"data row6 col3\" >0.0007</td>\n",
       "                        <td id=\"T_c829e_row6_col4\" class=\"data row6 col4\" >0.0010</td>\n",
       "                        <td id=\"T_c829e_row6_col5\" class=\"data row6 col5\" >0.0015</td>\n",
       "                        <td id=\"T_c829e_row6_col6\" class=\"data row6 col6\" >0.0015</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f906a997610>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lgbm = create_model(estimator = 'lightgbm', fold = 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "94acfda5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-09-26T11:56:19.559157Z",
     "iopub.status.busy": "2021-09-26T11:56:19.558529Z",
     "iopub.status.idle": "2021-09-26T11:57:00.023301Z",
     "shell.execute_reply": "2021-09-26T11:57:00.023792Z",
     "shell.execute_reply.started": "2021-09-26T10:53:36.155372Z"
    },
    "papermill": {
     "duration": 40.570213,
     "end_time": "2021-09-26T11:57:00.023968",
     "exception": false,
     "start_time": "2021-09-26T11:56:19.453755",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "#T_cee1f_row5_col0,#T_cee1f_row5_col1,#T_cee1f_row5_col2,#T_cee1f_row5_col3,#T_cee1f_row5_col4,#T_cee1f_row5_col5,#T_cee1f_row5_col6{\n",
       "            background:  yellow;\n",
       "        }</style><table id=\"T_cee1f_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Accuracy</th>        <th class=\"col_heading level0 col1\" >AUC</th>        <th class=\"col_heading level0 col2\" >Recall</th>        <th class=\"col_heading level0 col3\" >Prec.</th>        <th class=\"col_heading level0 col4\" >F1</th>        <th class=\"col_heading level0 col5\" >Kappa</th>        <th class=\"col_heading level0 col6\" >MCC</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_cee1f_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_cee1f_row0_col0\" class=\"data row0 col0\" >0.7170</td>\n",
       "                        <td id=\"T_cee1f_row0_col1\" class=\"data row0 col1\" >0.7733</td>\n",
       "                        <td id=\"T_cee1f_row0_col2\" class=\"data row0 col2\" >0.6541</td>\n",
       "                        <td id=\"T_cee1f_row0_col3\" class=\"data row0 col3\" >0.7472</td>\n",
       "                        <td id=\"T_cee1f_row0_col4\" class=\"data row0 col4\" >0.6976</td>\n",
       "                        <td id=\"T_cee1f_row0_col5\" class=\"data row0 col5\" >0.4339</td>\n",
       "                        <td id=\"T_cee1f_row0_col6\" class=\"data row0 col6\" >0.4373</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_cee1f_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_cee1f_row1_col0\" class=\"data row1 col0\" >0.7169</td>\n",
       "                        <td id=\"T_cee1f_row1_col1\" class=\"data row1 col1\" >0.7748</td>\n",
       "                        <td id=\"T_cee1f_row1_col2\" class=\"data row1 col2\" >0.6523</td>\n",
       "                        <td id=\"T_cee1f_row1_col3\" class=\"data row1 col3\" >0.7481</td>\n",
       "                        <td id=\"T_cee1f_row1_col4\" class=\"data row1 col4\" >0.6969</td>\n",
       "                        <td id=\"T_cee1f_row1_col5\" class=\"data row1 col5\" >0.4337</td>\n",
       "                        <td id=\"T_cee1f_row1_col6\" class=\"data row1 col6\" >0.4373</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_cee1f_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_cee1f_row2_col0\" class=\"data row2 col0\" >0.7165</td>\n",
       "                        <td id=\"T_cee1f_row2_col1\" class=\"data row2 col1\" >0.7744</td>\n",
       "                        <td id=\"T_cee1f_row2_col2\" class=\"data row2 col2\" >0.6519</td>\n",
       "                        <td id=\"T_cee1f_row2_col3\" class=\"data row2 col3\" >0.7476</td>\n",
       "                        <td id=\"T_cee1f_row2_col4\" class=\"data row2 col4\" >0.6965</td>\n",
       "                        <td id=\"T_cee1f_row2_col5\" class=\"data row2 col5\" >0.4329</td>\n",
       "                        <td id=\"T_cee1f_row2_col6\" class=\"data row2 col6\" >0.4365</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_cee1f_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_cee1f_row3_col0\" class=\"data row3 col0\" >0.7163</td>\n",
       "                        <td id=\"T_cee1f_row3_col1\" class=\"data row3 col1\" >0.7764</td>\n",
       "                        <td id=\"T_cee1f_row3_col2\" class=\"data row3 col2\" >0.6522</td>\n",
       "                        <td id=\"T_cee1f_row3_col3\" class=\"data row3 col3\" >0.7471</td>\n",
       "                        <td id=\"T_cee1f_row3_col4\" class=\"data row3 col4\" >0.6964</td>\n",
       "                        <td id=\"T_cee1f_row3_col5\" class=\"data row3 col5\" >0.4325</td>\n",
       "                        <td id=\"T_cee1f_row3_col6\" class=\"data row3 col6\" >0.4360</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_cee1f_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_cee1f_row4_col0\" class=\"data row4 col0\" >0.7171</td>\n",
       "                        <td id=\"T_cee1f_row4_col1\" class=\"data row4 col1\" >0.7745</td>\n",
       "                        <td id=\"T_cee1f_row4_col2\" class=\"data row4 col2\" >0.6533</td>\n",
       "                        <td id=\"T_cee1f_row4_col3\" class=\"data row4 col3\" >0.7479</td>\n",
       "                        <td id=\"T_cee1f_row4_col4\" class=\"data row4 col4\" >0.6974</td>\n",
       "                        <td id=\"T_cee1f_row4_col5\" class=\"data row4 col5\" >0.4341</td>\n",
       "                        <td id=\"T_cee1f_row4_col6\" class=\"data row4 col6\" >0.4376</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_cee1f_level0_row5\" class=\"row_heading level0 row5\" >Mean</th>\n",
       "                        <td id=\"T_cee1f_row5_col0\" class=\"data row5 col0\" >0.7168</td>\n",
       "                        <td id=\"T_cee1f_row5_col1\" class=\"data row5 col1\" >0.7747</td>\n",
       "                        <td id=\"T_cee1f_row5_col2\" class=\"data row5 col2\" >0.6528</td>\n",
       "                        <td id=\"T_cee1f_row5_col3\" class=\"data row5 col3\" >0.7476</td>\n",
       "                        <td id=\"T_cee1f_row5_col4\" class=\"data row5 col4\" >0.6970</td>\n",
       "                        <td id=\"T_cee1f_row5_col5\" class=\"data row5 col5\" >0.4334</td>\n",
       "                        <td id=\"T_cee1f_row5_col6\" class=\"data row5 col6\" >0.4369</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_cee1f_level0_row6\" class=\"row_heading level0 row6\" >SD</th>\n",
       "                        <td id=\"T_cee1f_row6_col0\" class=\"data row6 col0\" >0.0003</td>\n",
       "                        <td id=\"T_cee1f_row6_col1\" class=\"data row6 col1\" >0.0010</td>\n",
       "                        <td id=\"T_cee1f_row6_col2\" class=\"data row6 col2\" >0.0008</td>\n",
       "                        <td id=\"T_cee1f_row6_col3\" class=\"data row6 col3\" >0.0004</td>\n",
       "                        <td id=\"T_cee1f_row6_col4\" class=\"data row6 col4\" >0.0005</td>\n",
       "                        <td id=\"T_cee1f_row6_col5\" class=\"data row6 col5\" >0.0006</td>\n",
       "                        <td id=\"T_cee1f_row6_col6\" class=\"data row6 col6\" >0.0006</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f906a9ddf10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xgb = create_model(estimator = 'xgboost', fold = 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "20fe9332",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-09-26T11:57:00.238207Z",
     "iopub.status.busy": "2021-09-26T11:57:00.237355Z",
     "iopub.status.idle": "2021-09-26T12:07:21.505614Z",
     "shell.execute_reply": "2021-09-26T12:07:21.505066Z",
     "shell.execute_reply.started": "2021-09-26T10:57:40.301757Z"
    },
    "papermill": {
     "duration": 621.377455,
     "end_time": "2021-09-26T12:07:21.505752",
     "exception": false,
     "start_time": "2021-09-26T11:57:00.128297",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "#T_fa181_row3_col0,#T_fa181_row3_col1,#T_fa181_row3_col2,#T_fa181_row3_col3,#T_fa181_row3_col4,#T_fa181_row3_col5,#T_fa181_row3_col6{\n",
       "            background:  yellow;\n",
       "        }</style><table id=\"T_fa181_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Accuracy</th>        <th class=\"col_heading level0 col1\" >AUC</th>        <th class=\"col_heading level0 col2\" >Recall</th>        <th class=\"col_heading level0 col3\" >Prec.</th>        <th class=\"col_heading level0 col4\" >F1</th>        <th class=\"col_heading level0 col5\" >Kappa</th>        <th class=\"col_heading level0 col6\" >MCC</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_fa181_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_fa181_row0_col0\" class=\"data row0 col0\" >0.7093</td>\n",
       "                        <td id=\"T_fa181_row0_col1\" class=\"data row0 col1\" >0.7698</td>\n",
       "                        <td id=\"T_fa181_row0_col2\" class=\"data row0 col2\" >0.6330</td>\n",
       "                        <td id=\"T_fa181_row0_col3\" class=\"data row0 col3\" >0.7459</td>\n",
       "                        <td id=\"T_fa181_row0_col4\" class=\"data row0 col4\" >0.6849</td>\n",
       "                        <td id=\"T_fa181_row0_col5\" class=\"data row0 col5\" >0.4184</td>\n",
       "                        <td id=\"T_fa181_row0_col6\" class=\"data row0 col6\" >0.4233</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fa181_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_fa181_row1_col0\" class=\"data row1 col0\" >0.7113</td>\n",
       "                        <td id=\"T_fa181_row1_col1\" class=\"data row1 col1\" >0.7727</td>\n",
       "                        <td id=\"T_fa181_row1_col2\" class=\"data row1 col2\" >0.6366</td>\n",
       "                        <td id=\"T_fa181_row1_col3\" class=\"data row1 col3\" >0.7473</td>\n",
       "                        <td id=\"T_fa181_row1_col4\" class=\"data row1 col4\" >0.6875</td>\n",
       "                        <td id=\"T_fa181_row1_col5\" class=\"data row1 col5\" >0.4224</td>\n",
       "                        <td id=\"T_fa181_row1_col6\" class=\"data row1 col6\" >0.4271</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fa181_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_fa181_row2_col0\" class=\"data row2 col0\" >0.7123</td>\n",
       "                        <td id=\"T_fa181_row2_col1\" class=\"data row2 col1\" >0.7717</td>\n",
       "                        <td id=\"T_fa181_row2_col2\" class=\"data row2 col2\" >0.6385</td>\n",
       "                        <td id=\"T_fa181_row2_col3\" class=\"data row2 col3\" >0.7479</td>\n",
       "                        <td id=\"T_fa181_row2_col4\" class=\"data row2 col4\" >0.6889</td>\n",
       "                        <td id=\"T_fa181_row2_col5\" class=\"data row2 col5\" >0.4244</td>\n",
       "                        <td id=\"T_fa181_row2_col6\" class=\"data row2 col6\" >0.4290</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fa181_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
       "                        <td id=\"T_fa181_row3_col0\" class=\"data row3 col0\" >0.7110</td>\n",
       "                        <td id=\"T_fa181_row3_col1\" class=\"data row3 col1\" >0.7714</td>\n",
       "                        <td id=\"T_fa181_row3_col2\" class=\"data row3 col2\" >0.6361</td>\n",
       "                        <td id=\"T_fa181_row3_col3\" class=\"data row3 col3\" >0.7470</td>\n",
       "                        <td id=\"T_fa181_row3_col4\" class=\"data row3 col4\" >0.6871</td>\n",
       "                        <td id=\"T_fa181_row3_col5\" class=\"data row3 col5\" >0.4217</td>\n",
       "                        <td id=\"T_fa181_row3_col6\" class=\"data row3 col6\" >0.4265</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fa181_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
       "                        <td id=\"T_fa181_row4_col0\" class=\"data row4 col0\" >0.0012</td>\n",
       "                        <td id=\"T_fa181_row4_col1\" class=\"data row4 col1\" >0.0012</td>\n",
       "                        <td id=\"T_fa181_row4_col2\" class=\"data row4 col2\" >0.0023</td>\n",
       "                        <td id=\"T_fa181_row4_col3\" class=\"data row4 col3\" >0.0008</td>\n",
       "                        <td id=\"T_fa181_row4_col4\" class=\"data row4 col4\" >0.0017</td>\n",
       "                        <td id=\"T_fa181_row4_col5\" class=\"data row4 col5\" >0.0025</td>\n",
       "                        <td id=\"T_fa181_row4_col6\" class=\"data row4 col6\" >0.0024</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f9099a39f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "boosted_lgbm = ensemble_model(lgbm, method = 'Bagging')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "714dc142",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-09-26T12:07:21.722279Z",
     "iopub.status.busy": "2021-09-26T12:07:21.721407Z",
     "iopub.status.idle": "2021-09-26T12:24:32.913750Z",
     "shell.execute_reply": "2021-09-26T12:24:32.913230Z",
     "shell.execute_reply.started": "2021-09-26T11:09:42.522850Z"
    },
    "papermill": {
     "duration": 1031.302589,
     "end_time": "2021-09-26T12:24:32.913897",
     "exception": false,
     "start_time": "2021-09-26T12:07:21.611308",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "#T_0a747_row5_col0,#T_0a747_row5_col1,#T_0a747_row5_col2,#T_0a747_row5_col3,#T_0a747_row5_col4,#T_0a747_row5_col5,#T_0a747_row5_col6{\n",
       "            background:  yellow;\n",
       "        }</style><table id=\"T_0a747_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Accuracy</th>        <th class=\"col_heading level0 col1\" >AUC</th>        <th class=\"col_heading level0 col2\" >Recall</th>        <th class=\"col_heading level0 col3\" >Prec.</th>        <th class=\"col_heading level0 col4\" >F1</th>        <th class=\"col_heading level0 col5\" >Kappa</th>        <th class=\"col_heading level0 col6\" >MCC</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_0a747_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_0a747_row0_col0\" class=\"data row0 col0\" >0.7189</td>\n",
       "                        <td id=\"T_0a747_row0_col1\" class=\"data row0 col1\" >0.7782</td>\n",
       "                        <td id=\"T_0a747_row0_col2\" class=\"data row0 col2\" >0.6554</td>\n",
       "                        <td id=\"T_0a747_row0_col3\" class=\"data row0 col3\" >0.7497</td>\n",
       "                        <td id=\"T_0a747_row0_col4\" class=\"data row0 col4\" >0.6994</td>\n",
       "                        <td id=\"T_0a747_row0_col5\" class=\"data row0 col5\" >0.4376</td>\n",
       "                        <td id=\"T_0a747_row0_col6\" class=\"data row0 col6\" >0.4411</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0a747_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_0a747_row1_col0\" class=\"data row1 col0\" >0.7196</td>\n",
       "                        <td id=\"T_0a747_row1_col1\" class=\"data row1 col1\" >0.7810</td>\n",
       "                        <td id=\"T_0a747_row1_col2\" class=\"data row1 col2\" >0.6546</td>\n",
       "                        <td id=\"T_0a747_row1_col3\" class=\"data row1 col3\" >0.7514</td>\n",
       "                        <td id=\"T_0a747_row1_col4\" class=\"data row1 col4\" >0.6997</td>\n",
       "                        <td id=\"T_0a747_row1_col5\" class=\"data row1 col5\" >0.4391</td>\n",
       "                        <td id=\"T_0a747_row1_col6\" class=\"data row1 col6\" >0.4428</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0a747_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_0a747_row2_col0\" class=\"data row2 col0\" >0.7194</td>\n",
       "                        <td id=\"T_0a747_row2_col1\" class=\"data row2 col1\" >0.7803</td>\n",
       "                        <td id=\"T_0a747_row2_col2\" class=\"data row2 col2\" >0.6550</td>\n",
       "                        <td id=\"T_0a747_row2_col3\" class=\"data row2 col3\" >0.7508</td>\n",
       "                        <td id=\"T_0a747_row2_col4\" class=\"data row2 col4\" >0.6997</td>\n",
       "                        <td id=\"T_0a747_row2_col5\" class=\"data row2 col5\" >0.4387</td>\n",
       "                        <td id=\"T_0a747_row2_col6\" class=\"data row2 col6\" >0.4423</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0a747_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_0a747_row3_col0\" class=\"data row3 col0\" >0.7198</td>\n",
       "                        <td id=\"T_0a747_row3_col1\" class=\"data row3 col1\" >0.7816</td>\n",
       "                        <td id=\"T_0a747_row3_col2\" class=\"data row3 col2\" >0.6548</td>\n",
       "                        <td id=\"T_0a747_row3_col3\" class=\"data row3 col3\" >0.7516</td>\n",
       "                        <td id=\"T_0a747_row3_col4\" class=\"data row3 col4\" >0.6999</td>\n",
       "                        <td id=\"T_0a747_row3_col5\" class=\"data row3 col5\" >0.4394</td>\n",
       "                        <td id=\"T_0a747_row3_col6\" class=\"data row3 col6\" >0.4431</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0a747_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_0a747_row4_col0\" class=\"data row4 col0\" >0.7199</td>\n",
       "                        <td id=\"T_0a747_row4_col1\" class=\"data row4 col1\" >0.7796</td>\n",
       "                        <td id=\"T_0a747_row4_col2\" class=\"data row4 col2\" >0.6560</td>\n",
       "                        <td id=\"T_0a747_row4_col3\" class=\"data row4 col3\" >0.7511</td>\n",
       "                        <td id=\"T_0a747_row4_col4\" class=\"data row4 col4\" >0.7003</td>\n",
       "                        <td id=\"T_0a747_row4_col5\" class=\"data row4 col5\" >0.4397</td>\n",
       "                        <td id=\"T_0a747_row4_col6\" class=\"data row4 col6\" >0.4432</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0a747_level0_row5\" class=\"row_heading level0 row5\" >Mean</th>\n",
       "                        <td id=\"T_0a747_row5_col0\" class=\"data row5 col0\" >0.7195</td>\n",
       "                        <td id=\"T_0a747_row5_col1\" class=\"data row5 col1\" >0.7801</td>\n",
       "                        <td id=\"T_0a747_row5_col2\" class=\"data row5 col2\" >0.6552</td>\n",
       "                        <td id=\"T_0a747_row5_col3\" class=\"data row5 col3\" >0.7509</td>\n",
       "                        <td id=\"T_0a747_row5_col4\" class=\"data row5 col4\" >0.6998</td>\n",
       "                        <td id=\"T_0a747_row5_col5\" class=\"data row5 col5\" >0.4389</td>\n",
       "                        <td id=\"T_0a747_row5_col6\" class=\"data row5 col6\" >0.4425</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_0a747_level0_row6\" class=\"row_heading level0 row6\" >SD</th>\n",
       "                        <td id=\"T_0a747_row6_col0\" class=\"data row6 col0\" >0.0004</td>\n",
       "                        <td id=\"T_0a747_row6_col1\" class=\"data row6 col1\" >0.0012</td>\n",
       "                        <td id=\"T_0a747_row6_col2\" class=\"data row6 col2\" >0.0005</td>\n",
       "                        <td id=\"T_0a747_row6_col3\" class=\"data row6 col3\" >0.0007</td>\n",
       "                        <td id=\"T_0a747_row6_col4\" class=\"data row6 col4\" >0.0003</td>\n",
       "                        <td id=\"T_0a747_row6_col5\" class=\"data row6 col5\" >0.0007</td>\n",
       "                        <td id=\"T_0a747_row6_col6\" class=\"data row6 col6\" >0.0008</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f9099ad3e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "blender = blend_models(estimator_list = [cat,boosted_lgbm,xgb], fold=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "88f7a734",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-09-26T12:24:33.139229Z",
     "iopub.status.busy": "2021-09-26T12:24:33.138028Z",
     "iopub.status.idle": "2021-09-26T12:25:11.322720Z",
     "shell.execute_reply": "2021-09-26T12:25:11.323130Z",
     "shell.execute_reply.started": "2021-09-26T11:26:56.771559Z"
    },
    "papermill": {
     "duration": 38.304181,
     "end_time": "2021-09-26T12:25:11.323295",
     "exception": false,
     "start_time": "2021-09-26T12:24:33.019114",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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    "pred_holdout = predict_model(blender)"
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    "final_model = finalize_model(blender)"
   ]
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   "id": "3b885717",
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    "prep_pipe = get_config('prep_pipe')\n",
    "prep_pipe.steps.append(['trained_model', final_model])\n",
    "pred = prep_pipe.predict_proba(test2)"
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    "result=pred"
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    "sub['claim'] = result[:, 1]\n",
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