UmojaHack_2022_Zimnat_Claim_Challenge_7th_Place.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c6877ca1-2e41-4dde-9681-52cd2af40925",
   "metadata": {},
   "source": [
    "# Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "36805c8e-c35f-4893-8acd-37a73006e52c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.metrics import mean_absolute_error as mae\n",
    "from sklearn.model_selection import cross_val_score, cross_validate\n",
    "from lightgbm import LGBMRegressor"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7b3d920-b8dd-4ef2-861b-f5ccca0d244c",
   "metadata": {},
   "source": [
    "# Loading Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f2adc296-7f8a-44e5-bfc0-fe1af43884a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>claim_id</th>\n",
       "      <th>policy_number</th>\n",
       "      <th>claim_number</th>\n",
       "      <th>sum_insured</th>\n",
       "      <th>product</th>\n",
       "      <th>agent</th>\n",
       "      <th>class_of_business</th>\n",
       "      <th>risk_type</th>\n",
       "      <th>loss_date</th>\n",
       "      <th>client_type</th>\n",
       "      <th>renewal_frequency</th>\n",
       "      <th>primary_cause</th>\n",
       "      <th>secondary_cause</th>\n",
       "      <th>branch</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ID_JZ7QWRHH57RO</td>\n",
       "      <td>pol000009680</td>\n",
       "      <td>claim0011359</td>\n",
       "      <td>300000.0</td>\n",
       "      <td>prod00027</td>\n",
       "      <td>ag00068</td>\n",
       "      <td>cob00031</td>\n",
       "      <td>rt00006</td>\n",
       "      <td>2021-05-13</td>\n",
       "      <td>ct0003</td>\n",
       "      <td>rf0001</td>\n",
       "      <td>pc0007</td>\n",
       "      <td>sc00022</td>\n",
       "      <td>br00006</td>\n",
       "      <td>82150.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ID_KQ5TJMVLJ4EP</td>\n",
       "      <td>pol000006869</td>\n",
       "      <td>claim0005272</td>\n",
       "      <td>16000.0</td>\n",
       "      <td>prod00005</td>\n",
       "      <td>ag00226</td>\n",
       "      <td>cob00010</td>\n",
       "      <td>rt00032</td>\n",
       "      <td>2018-05-13</td>\n",
       "      <td>ct0003</td>\n",
       "      <td>rf0001</td>\n",
       "      <td>pc0007</td>\n",
       "      <td>sc00023</td>\n",
       "      <td>br00002</td>\n",
       "      <td>3780.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ID_NYHI7WJGGIAE</td>\n",
       "      <td>pol000006135</td>\n",
       "      <td>claim0004147</td>\n",
       "      <td>3000.0</td>\n",
       "      <td>prod00029</td>\n",
       "      <td>ag00037</td>\n",
       "      <td>cob00010</td>\n",
       "      <td>rt00026</td>\n",
       "      <td>2018-08-18</td>\n",
       "      <td>ct0003</td>\n",
       "      <td>rf0001</td>\n",
       "      <td>pc0007</td>\n",
       "      <td>sc00024</td>\n",
       "      <td>br00002</td>\n",
       "      <td>2196.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ID_ROMMDCXYUXN5</td>\n",
       "      <td>pol000008991</td>\n",
       "      <td>claim0009962</td>\n",
       "      <td>6000.0</td>\n",
       "      <td>prod00005</td>\n",
       "      <td>ag00037</td>\n",
       "      <td>cob00009</td>\n",
       "      <td>rt00032</td>\n",
       "      <td>2018-12-20</td>\n",
       "      <td>ct0003</td>\n",
       "      <td>rf0001</td>\n",
       "      <td>pc0007</td>\n",
       "      <td>sc00021</td>\n",
       "      <td>br00001</td>\n",
       "      <td>105.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ID_2OTD9NX8L73D</td>\n",
       "      <td>pol000007768</td>\n",
       "      <td>claim0007346</td>\n",
       "      <td>26850.0</td>\n",
       "      <td>prod00015</td>\n",
       "      <td>ag00226</td>\n",
       "      <td>cob00034</td>\n",
       "      <td>rt00023</td>\n",
       "      <td>2018-11-07</td>\n",
       "      <td>ct0001</td>\n",
       "      <td>rf0001</td>\n",
       "      <td>pc0007</td>\n",
       "      <td>sc00021</td>\n",
       "      <td>br00001</td>\n",
       "      <td>1605.64</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          claim_id policy_number  claim_number  sum_insured    product  \\\n",
       "0  ID_JZ7QWRHH57RO  pol000009680  claim0011359     300000.0  prod00027   \n",
       "1  ID_KQ5TJMVLJ4EP  pol000006869  claim0005272      16000.0  prod00005   \n",
       "2  ID_NYHI7WJGGIAE  pol000006135  claim0004147       3000.0  prod00029   \n",
       "3  ID_ROMMDCXYUXN5  pol000008991  claim0009962       6000.0  prod00005   \n",
       "4  ID_2OTD9NX8L73D  pol000007768  claim0007346      26850.0  prod00015   \n",
       "\n",
       "     agent class_of_business risk_type   loss_date client_type  \\\n",
       "0  ag00068          cob00031   rt00006  2021-05-13      ct0003   \n",
       "1  ag00226          cob00010   rt00032  2018-05-13      ct0003   \n",
       "2  ag00037          cob00010   rt00026  2018-08-18      ct0003   \n",
       "3  ag00037          cob00009   rt00032  2018-12-20      ct0003   \n",
       "4  ag00226          cob00034   rt00023  2018-11-07      ct0001   \n",
       "\n",
       "  renewal_frequency primary_cause secondary_cause   branch    target  \n",
       "0            rf0001        pc0007         sc00022  br00006  82150.00  \n",
       "1            rf0001        pc0007         sc00023  br00002   3780.24  \n",
       "2            rf0001        pc0007         sc00024  br00002   2196.50  \n",
       "3            rf0001        pc0007         sc00021  br00001    105.67  \n",
       "4            rf0001        pc0007         sc00021  br00001   1605.64  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Loading data\n",
    "train = pd.read_csv('data/train.csv')\n",
    "policies = pd.read_csv('data/policies.csv')\n",
    "test = pd.read_csv('data/test.csv')\n",
    "samplesubmission = pd.read_csv('data/SampleSubmission.csv')\n",
    "\n",
    "# Preview train dataset\n",
    "train.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecc49604-7e4d-4ab1-bc74-072ea37b4113",
   "metadata": {},
   "source": [
    "# Feature Engineering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "51384008-6060-4144-81eb-72da66dc4748",
   "metadata": {},
   "outputs": [],
   "source": [
    "# casting\n",
    "def build_features(df):\n",
    "    # Time features\n",
    "    df['loss_date'] = pd.to_datetime(df['loss_date'])\n",
    "    df['loss_date_day'] = df.loss_date.dt.day\n",
    "    df['loss_date_month'] = df.loss_date.dt.month\n",
    "    df['loss_date_year'] = df.loss_date.dt.year\n",
    "    # log of insured sum\n",
    "    df['log_sum'] = np.log1p(df['sum_insured'])\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "34f380bd-aa8f-433e-bf3d-fa1f29e2e441",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_df = build_features(train)\n",
    "test_df = build_features(test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ddf899eb-7aed-47b5-8d8e-e124d8c5ba08",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Apply log(1+y) to avoid large values on target\n",
    "train_df['target'] = np.log1p(train.target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4617195a-3ea7-4f4e-aa61-428fb4862a67",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Convert object to 'category'\n",
    "# Convert categorical variables to categorical objects\n",
    "cat_cols = train_df.columns.difference(['claim_id', 'loss_date','sum_insured','log_sum', 'target']).tolist()\n",
    "for col in cat_cols:\n",
    "    train_df[col] = train_df[col].astype('category')\n",
    "    test_df[col] = test_df[col].astype('category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e5cfc0a8-4a8d-4966-8d04-993536546e8f",
   "metadata": {},
   "outputs": [],
   "source": [
    "cols_to_drop = ['loss_date']\n",
    "train_df = train_df.drop(cols_to_drop,axis=1)\n",
    "test_df = test_df.drop(cols_to_drop,axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "062c360b-ce1f-461d-9dca-db520daf962d",
   "metadata": {},
   "source": [
    "# CV Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e7ced50f-10f4-4c6f-87d5-52ff6242afa1",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import KFold\n",
    "def evaluate(model,args,train,k=5):\n",
    "    y = train.target\n",
    "    y = pd.Series(y)\n",
    "    X = train.drop(['claim_id','target'],axis='columns')\n",
    "    kf = KFold(n_splits=k)\n",
    "    scores = []\n",
    "    for train_index, test_index in kf.split(X):\n",
    "        m = model(**args) \n",
    "        #print(\"TRAIN:\", train_index, \"TEST:\", test_index)\n",
    "        X_train, X_test = X.iloc[train_index,:], X.iloc[test_index,:]\n",
    "        y_train, y_test = y.iloc[train_index], y.iloc[test_index]\n",
    "        m.fit(X_train,y_train)\n",
    "        y_hat = m.predict(X_test)\n",
    "        score = mae(np.expm1(y_test),np.expm1(y_hat))\n",
    "        \n",
    "        print(score)\n",
    "        scores.append(score)\n",
    "    print('MAE Average on ',k,' folds: ', sum(scores)/k)\n",
    "    print('MAE std on ',k,' folds: ', np.std(scores)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "07e971bc-0a8e-47af-a638-6cc910235377",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "37235.440912263184\n",
      "33638.02674775547\n",
      "28496.718093654472\n",
      "46728.2915860278\n",
      "37796.162209915106\n",
      "28251.256265642052\n",
      "31167.673506247418\n",
      "27278.062646977745\n",
      "51231.0249582277\n",
      "28896.38214440405\n",
      "MAE Average on  10  folds:  35071.9039071115\n",
      "MAE std on  10  folds:  7842.355479257708\n"
     ]
    }
   ],
   "source": [
    "\n",
    "params = {\n",
    "    'objective': 'mae',\n",
    "    'n_estimators':200,\n",
    "    'max_depth':7,\n",
    "    'num_leaves':15,\n",
    "    'learning_rate':0.2\n",
    "}\n",
    "evaluate(LGBMRegressor,params,train_df,10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "4d1b2bfc-95f2-4443-a6c5-803e0ec1c62c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import warnings\n",
    "warnings.simplefilter(action='ignore', category=FutureWarning)\n",
    "\n",
    "def plotImp(model, X , num = 20, fig_size = (40, 20)):\n",
    "    feature_imp = pd.DataFrame({'Value':model.feature_importances_,'Feature':X.columns})\n",
    "    plt.figure(figsize=fig_size)\n",
    "    sns.set(font_scale = 5)\n",
    "    sns.barplot(x=\"Value\", y=\"Feature\", data=feature_imp.sort_values(by=\"Value\", \n",
    "                                                        ascending=False)[0:num])\n",
    "    plt.title('LightGBM Features (avg over folds)')\n",
    "    plt.tight_layout()\n",
    "    #plt.savefig('lgbm_importances-01.png')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d5cdb6f3-0605-49f5-8004-8077135ca6d5",
   "metadata": {},
   "source": [
    "# Fitting & Predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "acd90a29-af66-4966-b892-a2e096938504",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "X = train_df.drop(['claim_id','target'],axis=1)\n",
    "y = train_df.target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "02a7c012-8148-4bc0-becc-d1d5b3d2bc83",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'objective': 'mae', 'n_estimators': 300, 'max_depth': 7, 'num_leaves': 15, 'learning_rate': 0.05}\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "LGBMRegressor(learning_rate=0.05, max_depth=7, n_estimators=300, num_leaves=15,\n",
       "              objective='mae')"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(params)\n",
    "model = LGBMRegressor(**params)\n",
    "model.fit(X,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "4c23d0c5-9f4e-475d-8526-5579c4c3eceb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 2880x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotImp(model,X,20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "e4bf489e-bbe2-4da9-b7a4-5353f618d085",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'objective': 'mae',\n",
       " 'n_estimators': 200,\n",
       " 'max_depth': 7,\n",
       " 'num_leaves': 16,\n",
       " 'learning_rate': 0.2}"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "72efa255-6e39-4de7-9e8e-c080978f617b",
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions = model.predict(test_df.drop(['claim_id'],axis=1))\n",
    "# Don't forget to inverse the transformation\n",
    "preds = np.expm1(predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "6f1e2a98-c25b-4844-bf5c-93d259061798",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([134343.72117303,  29708.58836989,   5061.27135423, ...,\n",
       "       100660.35080103,  45003.7676749 ,  70698.02595782])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "7313f71f-d8e5-400f-be1a-029f2a63dbc0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>claim_id</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ID_4RO0KZI9BBW2</td>\n",
       "      <td>131631.447234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ID_GTE9ZUJ9GZ97</td>\n",
       "      <td>33189.069758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ID_RUVIYRKWZ4RG</td>\n",
       "      <td>4092.023008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ID_J81X8SWU6JYN</td>\n",
       "      <td>1771.013336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ID_94NM3JJAWWOQ</td>\n",
       "      <td>9093.823302</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          claim_id         target\n",
       "0  ID_4RO0KZI9BBW2  131631.447234\n",
       "1  ID_GTE9ZUJ9GZ97   33189.069758\n",
       "2  ID_RUVIYRKWZ4RG    4092.023008\n",
       "3  ID_J81X8SWU6JYN    1771.013336\n",
       "4  ID_94NM3JJAWWOQ    9093.823302"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub = samplesubmission.copy()\n",
    "sub.target = preds\n",
    "sub.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "a6fa0115-2a22-4628-81a9-03ae46d21f9a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count      4019.000000\n",
       "mean      14421.348552\n",
       "std       35272.641297\n",
       "min          38.298599\n",
       "25%         852.878499\n",
       "50%        1889.469522\n",
       "75%       10140.805561\n",
       "max      795673.810324\n",
       "Name: target, dtype: float64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub.target.describe()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "1f354d4d-8a24-41a0-b5ca-33076d1166fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    9376.000000\n",
       "mean        7.108465\n",
       "std         3.518393\n",
       "min         0.000000\n",
       "25%         5.666167\n",
       "50%         7.579640\n",
       "75%         9.449486\n",
       "max        15.878390\n",
       "Name: target, dtype: float64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.target.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "a7a729e1-37eb-4474-8f32-d0d51d5f914e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Write to csv file to submit to Zindi\n",
    "sub_fn = 'winning_lgbm_mae_2.csv'\n",
    "sub.to_csv(f\"submissions/{sub_fn}\", index = False)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}