Elo - ML model.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "toc": true
   },
   "source": [
    "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Load-imports-and-dfs\" data-toc-modified-id=\"Load-imports-and-dfs-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Load imports and dfs</a></span></li></ul></div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "IPython.notebook.set_autosave_interval(120000)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autosaving every 120 seconds\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "%load_ext autoreload\n",
    "%autoreload 4\n",
    "%autosave 120"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Load imports & test, train DFs\n",
    "2. Apply stratified kfold & traing with lgbm and submit to kaggle\n",
    "3. Check for missing data feature engineering parts missed if score > 3.7\n",
    "4. Split the training set to train & validation\n",
    "5. Train over RF to get a benchmark of the dataset\n",
    "6. Drop irrelevant features by sorting on feature importance\n",
    "7. Drop redundant features by plotting a Dendogram and removing the redundancy\n",
    "8. Use a feature interpreter to see which feature is contributing lot to prediction\n",
    "9. Use extrapolation to see if we can remove feature which add bias of training & validation set\n",
    "10. Use partial dependence plot to see outliers/missed features\n",
    "11. Submit to kaggle the RF model and see the score\n",
    "11. Use stratified kfold to train the RF model and submit to kaggle\n",
    "12. Repeat again with LGBM/XGBoost/Adaboost. Stack the model and submit to kaggle\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load imports and dfs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from fastai.io import *\n",
    "from fastai.structured import *\n",
    "from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier\n",
    "from pandas_summary import DataFrameSummary\n",
    "from IPython.display import display\n",
    "from sklearn import metrics\n",
    "import feather\n",
    "import lightgbm as lgb\n",
    "from sklearn.model_selection import StratifiedKFold\n",
    "from sklearn.metrics import mean_squared_error\n",
    "import warnings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_df2 = feather.read_dataframe('train_df')\n",
    "test_df2 = feather.read_dataframe('test_df')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "for df in [train_df2, test_df2]:\n",
    "    for f in ['purchase_date_max','purchase_date_min','purchase_date_max_old',\\\n",
    "                     'purchase_date_min_old']:\n",
    "        df[f] = df[f].astype(np.int64) * 1e-9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "del_cols = ['first_active_monthIs_month_start', 'authorized_flag_1_mean', 'first_active_monthIs_year_start',\n",
    "       'first_active_monthIs_year_end', 'first_active_monthIs_quarter_end', 'avg_trans_per_merchant',\n",
    "       'first_active_monthIs_month_end', 'first_active_monthDay', 'card_id_size',\n",
    "       'authorized_flag_1_amount_mean_mean', 'authorized_flag_1_amount_sum_sum','card_id', 'first_active_month','target','outliers']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def one_hot_encode_fe(df):\n",
    "    return pd.get_dummies(df, columns=['feature_1', 'feature_2', 'feature_3'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "# [train_df2, test_df2] = [one_hot_encode_fe(d) for d in [train_df2, test_df2]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train_columns = [c for c in train_df2.columns if c not in ['card_id', 'first_active_month','target','outliers']]\n",
    "target = train_df2['target']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((201917, 126), (123623, 124))"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df2.shape, test_df2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(201917,)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "del train_df2['target']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "122"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_train_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%|██████████| 122/122 [00:02<00:00, 37.65it/s]\n"
     ]
    }
   ],
   "source": [
    "from scipy.stats import ks_2samp\n",
    "list_p_value =[]\n",
    "\n",
    "for i in tqdm(df_train_columns):\n",
    "    list_p_value.append(ks_2samp(test_df2[i] , train_df2[i])[1])\n",
    "\n",
    "Se = pd.Series(list_p_value, index = df_train_columns).sort_values() \n",
    "list_discarded = list(Se[Se < .1].index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['avg_spend_per_transaction',\n",
       " 'category_2_sum_sum',\n",
       " 'purchase_amount_mean',\n",
       " 'avg_spend_per_merchant',\n",
       " 'purchase_amount_max_old',\n",
       " 'month_diff_std',\n",
       " 'month_diff_var',\n",
       " 'category_3_mean_mean_old',\n",
       " 'category_3_sum_sum_old',\n",
       " 'purchase_amount_sum']"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list_discarded"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train_columns = [c for c in df_train_columns if c not in list_discarded]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "112"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_train_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fold 0\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "[100]\ttraining's rmse: 3.66423\tvalid_1's rmse: 3.72048\n",
      "[200]\ttraining's rmse: 3.58717\tvalid_1's rmse: 3.68736\n",
      "[300]\ttraining's rmse: 3.53952\tvalid_1's rmse: 3.67382\n",
      "[400]\ttraining's rmse: 3.50226\tvalid_1's rmse: 3.66634\n",
      "[500]\ttraining's rmse: 3.472\tvalid_1's rmse: 3.6612\n",
      "[600]\ttraining's rmse: 3.44776\tvalid_1's rmse: 3.65833\n",
      "[700]\ttraining's rmse: 3.42537\tvalid_1's rmse: 3.65649\n",
      "[800]\ttraining's rmse: 3.40543\tvalid_1's rmse: 3.65536\n",
      "[900]\ttraining's rmse: 3.38654\tvalid_1's rmse: 3.65461\n",
      "[1000]\ttraining's rmse: 3.36899\tvalid_1's rmse: 3.65422\n",
      "Early stopping, best iteration is:\n",
      "[951]\ttraining's rmse: 3.37751\tvalid_1's rmse: 3.65411\n",
      "fold 1\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "[100]\ttraining's rmse: 3.66594\tvalid_1's rmse: 3.71269\n",
      "[200]\ttraining's rmse: 3.58776\tvalid_1's rmse: 3.68042\n",
      "[300]\ttraining's rmse: 3.53798\tvalid_1's rmse: 3.66872\n",
      "[400]\ttraining's rmse: 3.49971\tvalid_1's rmse: 3.66279\n",
      "[500]\ttraining's rmse: 3.46988\tvalid_1's rmse: 3.6589\n",
      "[600]\ttraining's rmse: 3.44493\tvalid_1's rmse: 3.65603\n",
      "[700]\ttraining's rmse: 3.42216\tvalid_1's rmse: 3.65418\n",
      "[800]\ttraining's rmse: 3.40127\tvalid_1's rmse: 3.65357\n",
      "[900]\ttraining's rmse: 3.38261\tvalid_1's rmse: 3.65284\n",
      "[1000]\ttraining's rmse: 3.36408\tvalid_1's rmse: 3.65189\n",
      "[1100]\ttraining's rmse: 3.34696\tvalid_1's rmse: 3.651\n",
      "[1200]\ttraining's rmse: 3.33027\tvalid_1's rmse: 3.65044\n",
      "[1300]\ttraining's rmse: 3.31497\tvalid_1's rmse: 3.64999\n",
      "[1400]\ttraining's rmse: 3.29919\tvalid_1's rmse: 3.65006\n",
      "Early stopping, best iteration is:\n",
      "[1348]\ttraining's rmse: 3.30746\tvalid_1's rmse: 3.64976\n",
      "fold 2\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "[100]\ttraining's rmse: 3.66371\tvalid_1's rmse: 3.7203\n",
      "[200]\ttraining's rmse: 3.58407\tvalid_1's rmse: 3.69034\n",
      "[300]\ttraining's rmse: 3.53612\tvalid_1's rmse: 3.67783\n",
      "[400]\ttraining's rmse: 3.49999\tvalid_1's rmse: 3.66934\n",
      "[500]\ttraining's rmse: 3.47037\tvalid_1's rmse: 3.66407\n",
      "[600]\ttraining's rmse: 3.44442\tvalid_1's rmse: 3.66087\n",
      "[700]\ttraining's rmse: 3.42195\tvalid_1's rmse: 3.65887\n",
      "[800]\ttraining's rmse: 3.40163\tvalid_1's rmse: 3.6578\n",
      "[900]\ttraining's rmse: 3.38261\tvalid_1's rmse: 3.65733\n",
      "[1000]\ttraining's rmse: 3.36483\tvalid_1's rmse: 3.65628\n",
      "[1100]\ttraining's rmse: 3.34822\tvalid_1's rmse: 3.65607\n",
      "[1200]\ttraining's rmse: 3.33194\tvalid_1's rmse: 3.65571\n",
      "Early stopping, best iteration is:\n",
      "[1199]\ttraining's rmse: 3.33215\tvalid_1's rmse: 3.65568\n",
      "fold 3\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "[100]\ttraining's rmse: 3.66246\tvalid_1's rmse: 3.72287\n",
      "[200]\ttraining's rmse: 3.58219\tvalid_1's rmse: 3.69361\n",
      "[300]\ttraining's rmse: 3.53251\tvalid_1's rmse: 3.68202\n",
      "[400]\ttraining's rmse: 3.49714\tvalid_1's rmse: 3.67416\n",
      "[500]\ttraining's rmse: 3.46709\tvalid_1's rmse: 3.66948\n",
      "[600]\ttraining's rmse: 3.44197\tvalid_1's rmse: 3.66652\n",
      "[700]\ttraining's rmse: 3.42007\tvalid_1's rmse: 3.66455\n",
      "[800]\ttraining's rmse: 3.40039\tvalid_1's rmse: 3.66285\n",
      "[900]\ttraining's rmse: 3.38132\tvalid_1's rmse: 3.66209\n",
      "[1000]\ttraining's rmse: 3.36323\tvalid_1's rmse: 3.66102\n",
      "[1100]\ttraining's rmse: 3.34572\tvalid_1's rmse: 3.66104\n",
      "[1200]\ttraining's rmse: 3.32946\tvalid_1's rmse: 3.66035\n",
      "[1300]\ttraining's rmse: 3.31395\tvalid_1's rmse: 3.66028\n",
      "Early stopping, best iteration is:\n",
      "[1278]\ttraining's rmse: 3.31757\tvalid_1's rmse: 3.66012\n",
      "fold 4\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "[100]\ttraining's rmse: 3.66456\tvalid_1's rmse: 3.70727\n",
      "[200]\ttraining's rmse: 3.58458\tvalid_1's rmse: 3.67883\n",
      "[300]\ttraining's rmse: 3.53511\tvalid_1's rmse: 3.66655\n",
      "[400]\ttraining's rmse: 3.49685\tvalid_1's rmse: 3.66118\n",
      "[500]\ttraining's rmse: 3.46676\tvalid_1's rmse: 3.65783\n",
      "[600]\ttraining's rmse: 3.44137\tvalid_1's rmse: 3.65622\n",
      "[700]\ttraining's rmse: 3.41882\tvalid_1's rmse: 3.65497\n",
      "[800]\ttraining's rmse: 3.39726\tvalid_1's rmse: 3.6548\n",
      "[900]\ttraining's rmse: 3.37829\tvalid_1's rmse: 3.65448\n",
      "[1000]\ttraining's rmse: 3.3611\tvalid_1's rmse: 3.6541\n",
      "[1100]\ttraining's rmse: 3.34354\tvalid_1's rmse: 3.65358\n",
      "[1200]\ttraining's rmse: 3.32698\tvalid_1's rmse: 3.65398\n",
      "Early stopping, best iteration is:\n",
      "[1153]\ttraining's rmse: 3.33454\tvalid_1's rmse: 3.65345\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "3.6546249070742816"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "param = {'num_leaves': 31,\n",
    "         'min_data_in_leaf': 30, \n",
    "         'objective':'regression',\n",
    "         'max_depth': -1,\n",
    "         'learning_rate': 0.01,\n",
    "         \"min_child_samples\": 20,\n",
    "         \"boosting\": \"gbdt\",\n",
    "         \"feature_fraction\": 0.9,\n",
    "         \"bagging_freq\": 1,\n",
    "         \"bagging_fraction\": 0.9 ,\n",
    "         \"bagging_seed\": 11,\n",
    "         \"metric\": 'rmse',\n",
    "         \"lambda_l1\": 0.1,\n",
    "         \"verbosity\": -1,\n",
    "         \"nthread\": 4,\n",
    "         \"random_state\": 4590}\n",
    "folds = StratifiedKFold(n_splits=5, shuffle=True, random_state=4590)\n",
    "oof = np.zeros(len(train_df2))\n",
    "predictions = np.zeros(len(test_df2))\n",
    "feature_importance_df = pd.DataFrame()\n",
    "\n",
    "for fold_, (trn_idx, val_idx) in enumerate(folds.split(train_df2,train_df2['outliers'].values)):\n",
    "    print(\"fold {}\".format(fold_))\n",
    "    trn_data = lgb.Dataset(train_df2.iloc[trn_idx][df_train_columns], label=target.iloc[trn_idx])#, categorical_feature=categorical_feats)\n",
    "    val_data = lgb.Dataset(train_df2.iloc[val_idx][df_train_columns], label=target.iloc[val_idx])#, categorical_feature=categorical_feats)\n",
    "\n",
    "    num_round = 10000\n",
    "    clf = lgb.train(param, trn_data, num_round, valid_sets = [trn_data, val_data], verbose_eval=100, early_stopping_rounds = 100)\n",
    "    oof[val_idx] = clf.predict(train_df2.iloc[val_idx][df_train_columns], num_iteration=clf.best_iteration)\n",
    "    \n",
    "    fold_importance_df = pd.DataFrame()\n",
    "    fold_importance_df[\"Feature\"] = df_train_columns\n",
    "    fold_importance_df[\"importance\"] = clf.feature_importance()\n",
    "    fold_importance_df[\"fold\"] = fold_ + 1\n",
    "    feature_importance_df = pd.concat([feature_importance_df, fold_importance_df], axis=0)\n",
    "    \n",
    "    predictions += clf.predict(test_df2[df_train_columns], num_iteration=clf.best_iteration) / folds.n_splits\n",
    "\n",
    "np.sqrt(mean_squared_error(oof, target))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Score for submission-2019-01-11 10:18:09.909061.csv - 3.6597596743401666, LB - 3.707 (included cat_1)\n",
    "2. Score for submission-2019-01-12 13:53:27.215115.csv - 3.656726211308068, LB - 3.696 (jst refactored)\n",
    "3. No changes what so ever - 3.6627995460091523\n",
    "4. Replaced with kernels code - 3.6623128394907103\n",
    "5. Replaced with kernels code along with cat_2 mean - 3.6609564684554594\n",
    "6. Added extra feature - 3.6559302073797637, LB - 3.696 (No grouping by auth flag and all)\n",
    "7. Added aggs on cat_1, auth - 3.6554801486969906, LB- 3.696\n",
    "8. Removed unnecessary cols - 3.6556548946965446, LB - 3.696\n",
    "9. Removed aggs on cat_1 - 3.654208034404632, LB - 3.697\n",
    "10. Removed unnecessary del_cols - 3.65493381575084, LB - 3.697\n",
    "11. One hot encoded features - 3.6558286566186897\n",
    "12. Added monthly aggregates - 3.653533666238162, LB - 3.716\n",
    "13. Removed some monthly aggregates - 3.654769374794982, LB - 3.707\n",
    "14. reverting to earlier checkpoing - 3.65377489489624\n",
    "15. Benchmarks - LGBM - 3.654910478618945, DL - 3.6971527526968155\n",
    "16. Just ran the whole FE page - 3.6546249070742816"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chandrasekhar/anaconda3/envs/fastai/lib/python3.6/site-packages/scipy/stats/stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cols = (feature_importance_df[[\"Feature\", \"importance\"]]\n",
    "        .groupby(\"Feature\")\n",
    "        .mean()\n",
    "        .sort_values(by=\"importance\", ascending=False)[:1000].index)\n",
    "\n",
    "best_features = feature_importance_df.loc[feature_importance_df.Feature.isin(cols)]\n",
    "\n",
    "plt.figure(figsize=(14,25))\n",
    "sns.barplot(x=\"importance\",\n",
    "            y=\"Feature\",\n",
    "            data=best_features.sort_values(by=\"importance\",\n",
    "                                           ascending=False))\n",
    "plt.title('LightGBM Features (avg over folds)')\n",
    "plt.tight_layout()\n",
    "plt.savefig('lgbm_importances.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['first_active_monthIs_month_start', 'first_active_monthDay', 'first_active_monthIs_year_start',\n",
       "       'authorized_flag_mean', 'first_active_monthIs_year_end', 'first_active_monthIs_month_end',\n",
       "       'first_active_monthIs_quarter_end', 'avg_trans_per_merchant', 'card_id_size',\n",
       "       'purchase_Year_nunique_old', 'authorized_flag_sum', 'repurchase_merchant_rate'], dtype=object)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "best_features.sort_values(by='importance', ascending=True)[:50]['Feature'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "sub_df = pd.DataFrame({\"card_id\":test_df2[\"card_id\"].values})\n",
    "sub_df[\"target\"] = predictions\n",
    "sub_df.to_csv(f'submission-{pd.to_datetime(\"today\")}.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'Elo - ML model - cat aggregates.ipynb'\r\n",
      "'Elo - ML model clean.ipynb'\r\n",
      "'Elo - ML model proc_df.ipynb'\r\n",
      "'Elo - ML model-RF copy.ipynb'\r\n",
      "'Elo - ML model-backup.ipynb'\r\n",
      "'Elo - ML model-new.ipynb'\r\n",
      "'Elo - ML model.ipynb'\r\n",
      "'Elo RF- New.ipynb'\r\n",
      "'Elo RF.ipynb'\r\n",
      "'Elo end 2 end.ipynb'\r\n",
      "'Elo feature engineering using agg.ipynb'\r\n",
      "'Elo feature engineering-backup.ipynb'\r\n",
      "'Elo feature engineering-proc_df - new-Copy1.ipynb'\r\n",
      "'Elo feature engineering-proc_df - new.ipynb'\r\n",
      "'Elo feature engineering-proc_df-OLD.ipynb'\r\n",
      "'Elo feature engineering.ipynb'\r\n",
      "'Elo merchant category reco - using RF.ipynb'\r\n",
      " README.md\r\n",
      "'Scrap pad.ipynb'\r\n",
      "'Scrap pad.py'\r\n",
      "'TS Fresh.ipynb'\r\n",
      "'TS Fresh.py'\r\n",
      "'Train & test clean.ipynb'\r\n",
      "'Using DL.ipynb'\r\n",
      "'Using Feature tools.ipynb'\r\n",
      " adf\r\n",
      " authorised_trans_proc_agg\r\n",
      " cols_keep.npy\r\n",
      " data\r\n",
      " df_auth\r\n",
      " df_hot_dropped_all\r\n",
      " df_hot_ext\r\n",
      " df_hot_test\r\n",
      " df_hot_test_ext\r\n",
      " df_new\r\n",
      " df_non_auth\r\n",
      " df_proc_dfed\r\n",
      " df_test_n_o\r\n",
      " df_xo\r\n",
      " fastai\r\n",
      " fm_new_hist\r\n",
      " hist_trans\r\n",
      " hist_trans_agg\r\n",
      " hist_trans_agg_n\r\n",
      " hist_trans_agg_proc\r\n",
      " lgbm_importances.png\r\n",
      " new_hist_prc\r\n",
      " new_hist_trans\r\n",
      " new_hist_trans_agg\r\n",
      " new_hist_trans_agg_n\r\n",
      " new_trans_agg_proc\r\n",
      " new_trans_proc_agg\r\n",
      " non_authorised_trans_proc\r\n",
      " non_authorised_trans_proc_agg\r\n",
      "'scrap pad 2.ipynb'\r\n",
      "'submission-2019-01-11 09:49:53.716164.csv'\r\n",
      "'submission-2019-01-11 10:18:09.909061.csv'\r\n",
      "'submission-2019-01-12 13:53:27.215115.csv'\r\n",
      "'submission-2019-01-12 16:27:31.239044.csv'\r\n",
      "'submission-2019-01-12 17:25:56.678553.csv'\r\n",
      "'submission-2019-01-12 17:33:29.475835.csv'\r\n",
      "'submission-2019-01-12 17:42:01.350278.csv'\r\n",
      "'submission-2019-01-12 22:12:59.947458.csv'\r\n",
      "'submission-2019-01-13 15:59:45.792347.csv'\r\n",
      "'submission-2019-01-13 18:24:51.237991.csv'\r\n",
      "'submission-2019-01-14 19:04:33.028609.csv'\r\n",
      "'submission-2019-01-14 19:56:09.906235.csv'\r\n",
      "'submission-2019-01-15 22:18:34.294443.csv'\r\n",
      "'submission-2019-01-15 22:24:38.071972.csv'\r\n",
      "'submission-2019-01-15 22:29:20.144417.csv'\r\n",
      "'submission-2019-01-16 00:35:46.490517.csv'\r\n",
      "'submission-2019-01-16 00:36:26.004443.csv'\r\n",
      "'submission-2019-01-16 12:20:00.957329.csv'\r\n",
      "'submission-2019-01-16 21:37:16.421927.csv'\r\n",
      "'submission-2019-01-17 10:20:06.724992.csv'\r\n",
      "'submission-2019-01-17 11:09:17.495216.csv'\r\n",
      "'submission-2019-01-17 23:23:57.743505.csv'\r\n",
      "'submission-2019-01-18 01:18:08.182115.csv'\r\n",
      "'submission-2019-01-18 01:42:20.587834.csv'\r\n",
      "'submission-2019-01-18 01:47:04.024727.csv'\r\n",
      "'submission-2019-01-18 16:16:45.475456.csv'\r\n",
      "'submission-2019-01-18 16:27:58.560480.csv'\r\n",
      "'submission-2019-01-18 17:22:46.188675.csv'\r\n",
      "'submission-2019-01-20 00:30:10.643280.csv'\r\n",
      "'submission-2019-01-20 01:28:12.077657.csv'\r\n",
      "'submission-2019-01-20 01:46:39.187580.csv'\r\n",
      " target_all\r\n",
      " target_outliers_removed\r\n",
      " test_clean.csv\r\n",
      " test_clean.csv.zip\r\n",
      " test_df\r\n",
      " test_df_proc\r\n",
      " test_df_proc_new\r\n",
      " test_df_proc_new_m\r\n",
      " train_clean.csv\r\n",
      " train_clean.csv.zip\r\n",
      " train_clean0\r\n",
      " train_df\r\n",
      " train_df_proc\r\n",
      " train_df_proc_new\r\n",
      " train_df_proc_new_m\r\n"
     ]
    }
   ],
   "source": [
    "!ls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<a href='./submission-2019-01-20 01:46:39.187580.csv' target='_blank'>./submission-2019-01-20 01:46:39.187580.csv</a><br>"
      ],
      "text/plain": [
       "/home/chandrasekhar/private/kaggle/submission-2019-01-20 01:46:39.187580.csv"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FileLink('./submission-2019-01-20 01:46:39.187580.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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