try_RGF.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get data here: https://datahack.analyticsvidhya.com/contest/practice-problem-big-mart-sales-iii/\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from rgf.sklearn import RGFRegressor\n",
    "from sklearn import preprocessing \n",
    "from sklearn.metrics import mean_squared_error, r2_score  # for regression labels\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.model_selection import GridSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train = pd.read_csv(\"Big_Mart_Train.csv\")\n",
    "test = pd.read_csv(\"Big_Mart_Test.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train.Item_Weight = train.Item_Weight.fillna(np.nanmedian(train.Item_Weight))\n",
    "test.Item_Weight = test.Item_Weight.fillna(np.nanmedian(test.Item_Weight))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train.Outlet_Size = train.Outlet_Size.fillna(train.Outlet_Size.mode().iloc[0])\n",
    "test.Outlet_Size = test.Outlet_Size.fillna(train.Outlet_Size.mode().iloc[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train.Item_Fat_Content = train.Item_Fat_Content.replace(['low fat', 'LF'], ['Low Fat', 'Low Fat'])\n",
    "test.Item_Fat_Content = test.Item_Fat_Content.replace(['low fat', 'LF'], ['Low Fat', 'Low Fat'])\n",
    "train.Item_Fat_Content = train.Item_Fat_Content.replace(['reg'], ['Regular'])\n",
    "test.Item_Fat_Content = test.Item_Fat_Content.replace(['reg'], ['Regular'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train.Outlet_Establishment_Year = 2017 - train.Outlet_Establishment_Year\n",
    "test.Outlet_Establishment_Year = 2017 - test.Outlet_Establishment_Year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# label encoding, do this by combining train and test together\n",
    "\n",
    "test['Item_Outlet_Sales'] = 0\n",
    "combi = train.append(test)\n",
    "number = LabelEncoder()\n",
    "\n",
    "for i in combi.columns:\n",
    "    if (combi[i].dtype == 'object'):\n",
    "        combi[i] = number.fit_transform(combi[i].astype('str'))\n",
    "        combi[i] = combi[i].astype('object')\n",
    "        \n",
    "train = combi[:train.shape[0]]\n",
    "test = combi[train.shape[0]:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Item_Identifier</th>\n",
       "      <th>Item_Weight</th>\n",
       "      <th>Item_Fat_Content</th>\n",
       "      <th>Item_Visibility</th>\n",
       "      <th>Item_Type</th>\n",
       "      <th>Item_MRP</th>\n",
       "      <th>Outlet_Identifier</th>\n",
       "      <th>Outlet_Establishment_Year</th>\n",
       "      <th>Outlet_Size</th>\n",
       "      <th>Outlet_Location_Type</th>\n",
       "      <th>Outlet_Type</th>\n",
       "      <th>Item_Outlet_Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1114</td>\n",
       "      <td>20.750</td>\n",
       "      <td>0</td>\n",
       "      <td>0.007565</td>\n",
       "      <td>13</td>\n",
       "      <td>107.8622</td>\n",
       "      <td>9</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1078</td>\n",
       "      <td>8.300</td>\n",
       "      <td>1</td>\n",
       "      <td>0.038428</td>\n",
       "      <td>4</td>\n",
       "      <td>87.3198</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1420</td>\n",
       "      <td>14.600</td>\n",
       "      <td>0</td>\n",
       "      <td>0.099575</td>\n",
       "      <td>11</td>\n",
       "      <td>241.7538</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>817</td>\n",
       "      <td>7.315</td>\n",
       "      <td>0</td>\n",
       "      <td>0.015388</td>\n",
       "      <td>13</td>\n",
       "      <td>155.0340</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1197</td>\n",
       "      <td>12.500</td>\n",
       "      <td>1</td>\n",
       "      <td>0.118599</td>\n",
       "      <td>4</td>\n",
       "      <td>234.2300</td>\n",
       "      <td>5</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Item_Identifier  Item_Weight Item_Fat_Content  Item_Visibility Item_Type  \\\n",
       "0            1114       20.750                0         0.007565        13   \n",
       "1            1078        8.300                1         0.038428         4   \n",
       "2            1420       14.600                0         0.099575        11   \n",
       "3             817        7.315                0         0.015388        13   \n",
       "4            1197       12.500                1         0.118599         4   \n",
       "\n",
       "   Item_MRP Outlet_Identifier  Outlet_Establishment_Year Outlet_Size  \\\n",
       "0  107.8622                 9                         18           1   \n",
       "1   87.3198                 2                         10           1   \n",
       "2  241.7538                 0                         19           1   \n",
       "3  155.0340                 2                         10           1   \n",
       "4  234.2300                 5                         32           1   \n",
       "\n",
       "  Outlet_Location_Type Outlet_Type  Item_Outlet_Sales  \n",
       "0                    0           1                0.0  \n",
       "1                    1           1                0.0  \n",
       "2                    2           0                0.0  \n",
       "3                    1           1                0.0  \n",
       "4                    2           3                0.0  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "train = train.drop('Item_Identifier',axis=1)\n",
    "test = test.drop('Item_Identifier',axis=1)\n",
    "\n",
    "y = train.Item_Outlet_Sales\n",
    "X = train.drop(['Item_Outlet_Sales'], axis=1)\n",
    "\n",
    "X_train, X_validation, y_train, y_validation = train_test_split(X, y, train_size=0.7, test_size=0.3, random_state=410)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Item_Weight</th>\n",
       "      <th>Item_Fat_Content</th>\n",
       "      <th>Item_Visibility</th>\n",
       "      <th>Item_Type</th>\n",
       "      <th>Item_MRP</th>\n",
       "      <th>Outlet_Identifier</th>\n",
       "      <th>Outlet_Establishment_Year</th>\n",
       "      <th>Outlet_Size</th>\n",
       "      <th>Outlet_Location_Type</th>\n",
       "      <th>Outlet_Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2438</th>\n",
       "      <td>8.51</td>\n",
       "      <td>1</td>\n",
       "      <td>0.078339</td>\n",
       "      <td>13</td>\n",
       "      <td>172.9422</td>\n",
       "      <td>1</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5523</th>\n",
       "      <td>12.60</td>\n",
       "      <td>0</td>\n",
       "      <td>0.087437</td>\n",
       "      <td>6</td>\n",
       "      <td>109.9228</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1097</th>\n",
       "      <td>12.60</td>\n",
       "      <td>1</td>\n",
       "      <td>0.040163</td>\n",
       "      <td>13</td>\n",
       "      <td>181.1660</td>\n",
       "      <td>5</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3146</th>\n",
       "      <td>8.52</td>\n",
       "      <td>0</td>\n",
       "      <td>0.045292</td>\n",
       "      <td>14</td>\n",
       "      <td>153.5682</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2582</th>\n",
       "      <td>20.35</td>\n",
       "      <td>0</td>\n",
       "      <td>0.090480</td>\n",
       "      <td>13</td>\n",
       "      <td>119.5466</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Item_Weight Item_Fat_Content  Item_Visibility Item_Type  Item_MRP  \\\n",
       "2438         8.51                1         0.078339        13  172.9422   \n",
       "5523        12.60                0         0.087437         6  109.9228   \n",
       "1097        12.60                1         0.040163        13  181.1660   \n",
       "3146         8.52                0         0.045292        14  153.5682   \n",
       "2582        20.35                0         0.090480        13  119.5466   \n",
       "\n",
       "     Outlet_Identifier  Outlet_Establishment_Year Outlet_Size  \\\n",
       "2438                 1                         30           0   \n",
       "5523                 6                         13           2   \n",
       "1097                 5                         32           1   \n",
       "3146                 0                         19           1   \n",
       "2582                 0                         19           1   \n",
       "\n",
       "     Outlet_Location_Type Outlet_Type  \n",
       "2438                    2           1  \n",
       "5523                    1           1  \n",
       "1097                    2           3  \n",
       "3146                    2           0  \n",
       "2582                    2           0  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "param_set = {'max_leaf':[1000,1200,1300,1400,1500,1600,1700,1800,1900,2000],\n",
    "              'l2':[0.1,0.2,0.3],\n",
    "              'min_samples_leaf':[4,10]}\n",
    "\n",
    "gsearch = GridSearchCV(estimator = RGFRegressor(learning_rate =0.1, loss='Log'), \n",
    " param_grid = param_set,n_jobs=7, cv=10, scoring='neg_mean_squared_error')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "({'mean_fit_time': array([ 0.3684557 ,  0.59250512,  0.45376027,  0.44017498,  0.45626903,\n",
       "          0.44970973,  0.43894658,  0.42482817,  0.49904621,  0.43536808,\n",
       "          0.44014027,  0.44622054,  0.43466704,  0.45483651,  0.43847854,\n",
       "          0.45948772,  0.44655688,  0.45149384,  0.45311253,  0.46100452,\n",
       "          0.44782608,  0.45524945,  0.4535507 ,  0.47965879,  0.47501144,\n",
       "          0.45171614,  0.47223487,  0.46248789,  0.45438995,  0.46145663,\n",
       "          0.46803682,  0.442698  ,  0.44157901,  0.43842547,  0.44351537,\n",
       "          0.44436464,  0.4477586 ,  0.44880841,  0.4553823 ,  0.4346102 ,\n",
       "          0.44632061,  0.44164464,  0.45784819,  0.4479074 ,  0.45300131,\n",
       "          0.44986243,  0.43918016,  0.48512106,  0.471105  ,  0.46990399,\n",
       "          0.45762208,  0.44246798,  0.45598526,  0.4642153 ,  0.44291341,\n",
       "          0.43375523,  0.44405489,  0.44084697,  0.45812194,  0.43781297]),\n",
       "  'mean_score_time': array([ 0.04046104,  0.0551976 ,  0.04598184,  0.04738538,  0.0429038 ,\n",
       "          0.05474763,  0.04634361,  0.04158435,  0.0466908 ,  0.04448042,\n",
       "          0.04823101,  0.04795635,  0.05046024,  0.05352499,  0.05181653,\n",
       "          0.04520338,  0.04408855,  0.05587437,  0.05473716,  0.04534819,\n",
       "          0.04952407,  0.04940584,  0.05083671,  0.04855413,  0.04531181,\n",
       "          0.05385697,  0.04632862,  0.04706519,  0.04987118,  0.04473786,\n",
       "          0.04536426,  0.04845929,  0.05108988,  0.0429173 ,  0.04908371,\n",
       "          0.05201006,  0.04913671,  0.04596291,  0.04940317,  0.04767489,\n",
       "          0.04825537,  0.05056312,  0.05134263,  0.04312971,  0.04951243,\n",
       "          0.05168281,  0.05587878,  0.05950878,  0.0600652 ,  0.05484829,\n",
       "          0.05214508,  0.0527045 ,  0.05935094,  0.0600343 ,  0.05676706,\n",
       "          0.05559394,  0.0552933 ,  0.06353762,  0.05417867,  0.0562829 ]),\n",
       "  'mean_test_score': array([-2857080.48825523, -2857080.48825523, -2857080.48825523,\n",
       "         -2857080.48825523, -2857080.48825523, -2857080.48825523,\n",
       "         -2857080.48825523, -2857080.48825523, -2857080.48825523,\n",
       "         -2857080.48825523, -2857080.48825523, -2857080.48825523,\n",
       "         -2857080.48825523, -2857080.48825523, -2857080.48825523,\n",
       "         -2857080.48825523, -2857080.48825523, -2857080.48825523,\n",
       "         -2857080.48825523, -2857080.48825523, -2857080.48825523,\n",
       "         -2857080.48825523, -2857080.48825523, -2857080.48825523,\n",
       "         -2857080.48825523, -2857080.48825523, -2857080.48825523,\n",
       "         -2857080.48825523, -2857080.48825523, -2857080.48825523,\n",
       "         -2857080.48825523, -2857080.48825523, -2857080.48825523,\n",
       "         -2857080.48825523, -2857080.48825523, -2857080.48825523,\n",
       "         -2857080.48825523, -2857080.48825523, -2857080.48825523,\n",
       "         -2857080.48825523, -2857080.48825523, -2857080.48825523,\n",
       "         -2857080.48825523, -2857080.48825523, -2857080.48825523,\n",
       "         -2857080.48825523, -2857080.48825523, -2857080.48825523,\n",
       "         -2857080.48825523, -2857080.48825523, -2857080.48825523,\n",
       "         -2857080.48825523, -2857080.48825523, -2857080.48825523,\n",
       "         -2857080.48825523, -2857080.48825523, -2857080.48825523,\n",
       "         -2857080.48825523, -2857080.48825523, -2857080.48825523]),\n",
       "  'mean_train_score': array([-2856293.03625434, -2856293.03625434, -2856293.03625434,\n",
       "         -2856293.03625434, -2856293.03625434, -2856293.03625434,\n",
       "         -2856293.03625434, -2856293.03625434, -2856293.03625434,\n",
       "         -2856293.03625434, -2856293.03625434, -2856293.03625434,\n",
       "         -2856293.03625434, -2856293.03625434, -2856293.03625434,\n",
       "         -2856293.03625434, -2856293.03625434, -2856293.03625434,\n",
       "         -2856293.03625434, -2856293.03625434, -2856293.03625434,\n",
       "         -2856293.03625434, -2856293.03625434, -2856293.03625434,\n",
       "         -2856293.03625434, -2856293.03625434, -2856293.03625434,\n",
       "         -2856293.03625434, -2856293.03625434, -2856293.03625434,\n",
       "         -2856293.03625434, -2856293.03625434, -2856293.03625434,\n",
       "         -2856293.03625434, -2856293.03625434, -2856293.03625434,\n",
       "         -2856293.03625434, -2856293.03625434, -2856293.03625434,\n",
       "         -2856293.03625434, -2856293.03625434, -2856293.03625434,\n",
       "         -2856293.03625434, -2856293.03625434, -2856293.03625434,\n",
       "         -2856293.03625434, -2856293.03625434, -2856293.03625434,\n",
       "         -2856293.03625434, -2856293.03625434, -2856293.03625434,\n",
       "         -2856293.03625434, -2856293.03625434, -2856293.03625434,\n",
       "         -2856293.03625434, -2856293.03625434, -2856293.03625434,\n",
       "         -2856293.03625434, -2856293.03625434, -2856293.03625434]),\n",
       "  'param_l2': masked_array(data = [0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1\n",
       "   0.1 0.1 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2\n",
       "   0.2 0.2 0.2 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3\n",
       "   0.3 0.3 0.3 0.3 0.3 0.3],\n",
       "               mask = [False False False False False False False False False False False False\n",
       "   False False False False False False False False False False False False\n",
       "   False False False False False False False False False False False False\n",
       "   False False False False False False False False False False False False\n",
       "   False False False False False False False False False False False False],\n",
       "         fill_value = ?),\n",
       "  'param_max_leaf': masked_array(data = [1000 1000 1200 1200 1300 1300 1400 1400 1500 1500 1600 1600 1700 1700 1800\n",
       "   1800 1900 1900 2000 2000 1000 1000 1200 1200 1300 1300 1400 1400 1500 1500\n",
       "   1600 1600 1700 1700 1800 1800 1900 1900 2000 2000 1000 1000 1200 1200 1300\n",
       "   1300 1400 1400 1500 1500 1600 1600 1700 1700 1800 1800 1900 1900 2000 2000],\n",
       "               mask = [False False False False False False False False False False False False\n",
       "   False False False False False False False False False False False False\n",
       "   False False False False False False False False False False False False\n",
       "   False False False False False False False False False False False False\n",
       "   False False False False False False False False False False False False],\n",
       "         fill_value = ?),\n",
       "  'param_min_samples_leaf': masked_array(data = [4 10 4 10 4 10 4 10 4 10 4 10 4 10 4 10 4 10 4 10 4 10 4 10 4 10 4 10 4 10\n",
       "   4 10 4 10 4 10 4 10 4 10 4 10 4 10 4 10 4 10 4 10 4 10 4 10 4 10 4 10 4 10],\n",
       "               mask = [False False False False False False False False False False False False\n",
       "   False False False False False False False False False False False False\n",
       "   False False False False False False False False False False False False\n",
       "   False False False False False False False False False False False False\n",
       "   False False False False False False False False False False False False],\n",
       "         fill_value = ?),\n",
       "  'params': ({'l2': 0.1, 'max_leaf': 1000, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.1, 'max_leaf': 1000, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.1, 'max_leaf': 1200, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.1, 'max_leaf': 1200, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.1, 'max_leaf': 1300, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.1, 'max_leaf': 1300, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.1, 'max_leaf': 1400, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.1, 'max_leaf': 1400, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.1, 'max_leaf': 1500, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.1, 'max_leaf': 1500, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.1, 'max_leaf': 1600, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.1, 'max_leaf': 1600, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.1, 'max_leaf': 1700, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.1, 'max_leaf': 1700, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.1, 'max_leaf': 1800, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.1, 'max_leaf': 1800, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.1, 'max_leaf': 1900, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.1, 'max_leaf': 1900, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.1, 'max_leaf': 2000, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.1, 'max_leaf': 2000, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.2, 'max_leaf': 1000, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.2, 'max_leaf': 1000, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.2, 'max_leaf': 1200, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.2, 'max_leaf': 1200, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.2, 'max_leaf': 1300, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.2, 'max_leaf': 1300, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.2, 'max_leaf': 1400, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.2, 'max_leaf': 1400, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.2, 'max_leaf': 1500, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.2, 'max_leaf': 1500, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.2, 'max_leaf': 1600, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.2, 'max_leaf': 1600, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.2, 'max_leaf': 1700, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.2, 'max_leaf': 1700, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.2, 'max_leaf': 1800, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.2, 'max_leaf': 1800, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.2, 'max_leaf': 1900, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.2, 'max_leaf': 1900, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.2, 'max_leaf': 2000, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.2, 'max_leaf': 2000, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.3, 'max_leaf': 1000, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.3, 'max_leaf': 1000, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.3, 'max_leaf': 1200, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.3, 'max_leaf': 1200, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.3, 'max_leaf': 1300, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.3, 'max_leaf': 1300, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.3, 'max_leaf': 1400, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.3, 'max_leaf': 1400, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.3, 'max_leaf': 1500, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.3, 'max_leaf': 1500, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.3, 'max_leaf': 1600, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.3, 'max_leaf': 1600, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.3, 'max_leaf': 1700, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.3, 'max_leaf': 1700, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.3, 'max_leaf': 1800, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.3, 'max_leaf': 1800, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.3, 'max_leaf': 1900, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.3, 'max_leaf': 1900, 'min_samples_leaf': 10},\n",
       "   {'l2': 0.3, 'max_leaf': 2000, 'min_samples_leaf': 4},\n",
       "   {'l2': 0.3, 'max_leaf': 2000, 'min_samples_leaf': 10}),\n",
       "  'rank_test_score': array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "         1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "         1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], dtype=int32),\n",
       "  'split0_test_score': array([-2776062.95022249, -2776062.95022249, -2776062.95022249,\n",
       "         -2776062.95022249, -2776062.95022249, -2776062.95022249,\n",
       "         -2776062.95022249, -2776062.95022249, -2776062.95022249,\n",
       "         -2776062.95022249, -2776062.95022249, -2776062.95022249,\n",
       "         -2776062.95022249, -2776062.95022249, -2776062.95022249,\n",
       "         -2776062.95022249, -2776062.95022249, -2776062.95022249,\n",
       "         -2776062.95022249, -2776062.95022249, -2776062.95022249,\n",
       "         -2776062.95022249, -2776062.95022249, -2776062.95022249,\n",
       "         -2776062.95022249, -2776062.95022249, -2776062.95022249,\n",
       "         -2776062.95022249, -2776062.95022249, -2776062.95022249,\n",
       "         -2776062.95022249, -2776062.95022249, -2776062.95022249,\n",
       "         -2776062.95022249, -2776062.95022249, -2776062.95022249,\n",
       "         -2776062.95022249, -2776062.95022249, -2776062.95022249,\n",
       "         -2776062.95022249, -2776062.95022249, -2776062.95022249,\n",
       "         -2776062.95022249, -2776062.95022249, -2776062.95022249,\n",
       "         -2776062.95022249, -2776062.95022249, -2776062.95022249,\n",
       "         -2776062.95022249, -2776062.95022249, -2776062.95022249,\n",
       "         -2776062.95022249, -2776062.95022249, -2776062.95022249,\n",
       "         -2776062.95022249, -2776062.95022249, -2776062.95022249,\n",
       "         -2776062.95022249, -2776062.95022249, -2776062.95022249]),\n",
       "  'split0_train_score': array([-2865372.6532548, -2865372.6532548, -2865372.6532548,\n",
       "         -2865372.6532548, -2865372.6532548, -2865372.6532548,\n",
       "         -2865372.6532548, -2865372.6532548, -2865372.6532548,\n",
       "         -2865372.6532548, -2865372.6532548, -2865372.6532548,\n",
       "         -2865372.6532548, -2865372.6532548, -2865372.6532548,\n",
       "         -2865372.6532548, -2865372.6532548, -2865372.6532548,\n",
       "         -2865372.6532548, -2865372.6532548, -2865372.6532548,\n",
       "         -2865372.6532548, -2865372.6532548, -2865372.6532548,\n",
       "         -2865372.6532548, -2865372.6532548, -2865372.6532548,\n",
       "         -2865372.6532548, -2865372.6532548, -2865372.6532548,\n",
       "         -2865372.6532548, -2865372.6532548, -2865372.6532548,\n",
       "         -2865372.6532548, -2865372.6532548, -2865372.6532548,\n",
       "         -2865372.6532548, -2865372.6532548, -2865372.6532548,\n",
       "         -2865372.6532548, -2865372.6532548, -2865372.6532548,\n",
       "         -2865372.6532548, -2865372.6532548, -2865372.6532548,\n",
       "         -2865372.6532548, -2865372.6532548, -2865372.6532548,\n",
       "         -2865372.6532548, -2865372.6532548, -2865372.6532548,\n",
       "         -2865372.6532548, -2865372.6532548, -2865372.6532548,\n",
       "         -2865372.6532548, -2865372.6532548, -2865372.6532548,\n",
       "         -2865372.6532548, -2865372.6532548, -2865372.6532548]),\n",
       "  'split1_test_score': array([-3004644.62486288, -3004644.62486288, -3004644.62486288,\n",
       "         -3004644.62486288, -3004644.62486288, -3004644.62486288,\n",
       "         -3004644.62486288, -3004644.62486288, -3004644.62486288,\n",
       "         -3004644.62486288, -3004644.62486288, -3004644.62486288,\n",
       "         -3004644.62486288, -3004644.62486288, -3004644.62486288,\n",
       "         -3004644.62486288, -3004644.62486288, -3004644.62486288,\n",
       "         -3004644.62486288, -3004644.62486288, -3004644.62486288,\n",
       "         -3004644.62486288, -3004644.62486288, -3004644.62486288,\n",
       "         -3004644.62486288, -3004644.62486288, -3004644.62486288,\n",
       "         -3004644.62486288, -3004644.62486288, -3004644.62486288,\n",
       "         -3004644.62486288, -3004644.62486288, -3004644.62486288,\n",
       "         -3004644.62486288, -3004644.62486288, -3004644.62486288,\n",
       "         -3004644.62486288, -3004644.62486288, -3004644.62486288,\n",
       "         -3004644.62486288, -3004644.62486288, -3004644.62486288,\n",
       "         -3004644.62486288, -3004644.62486288, -3004644.62486288,\n",
       "         -3004644.62486288, -3004644.62486288, -3004644.62486288,\n",
       "         -3004644.62486288, -3004644.62486288, -3004644.62486288,\n",
       "         -3004644.62486288, -3004644.62486288, -3004644.62486288,\n",
       "         -3004644.62486288, -3004644.62486288, -3004644.62486288,\n",
       "         -3004644.62486288, -3004644.62486288, -3004644.62486288]),\n",
       "  'split1_train_score': array([-2839885.19557603, -2839885.19557603, -2839885.19557603,\n",
       "         -2839885.19557603, -2839885.19557603, -2839885.19557603,\n",
       "         -2839885.19557603, -2839885.19557603, -2839885.19557603,\n",
       "         -2839885.19557603, -2839885.19557603, -2839885.19557603,\n",
       "         -2839885.19557603, -2839885.19557603, -2839885.19557603,\n",
       "         -2839885.19557603, -2839885.19557603, -2839885.19557603,\n",
       "         -2839885.19557603, -2839885.19557603, -2839885.19557603,\n",
       "         -2839885.19557603, -2839885.19557603, -2839885.19557603,\n",
       "         -2839885.19557603, -2839885.19557603, -2839885.19557603,\n",
       "         -2839885.19557603, -2839885.19557603, -2839885.19557603,\n",
       "         -2839885.19557603, -2839885.19557603, -2839885.19557603,\n",
       "         -2839885.19557603, -2839885.19557603, -2839885.19557603,\n",
       "         -2839885.19557603, -2839885.19557603, -2839885.19557603,\n",
       "         -2839885.19557603, -2839885.19557603, -2839885.19557603,\n",
       "         -2839885.19557603, -2839885.19557603, -2839885.19557603,\n",
       "         -2839885.19557603, -2839885.19557603, -2839885.19557603,\n",
       "         -2839885.19557603, -2839885.19557603, -2839885.19557603,\n",
       "         -2839885.19557603, -2839885.19557603, -2839885.19557603,\n",
       "         -2839885.19557603, -2839885.19557603, -2839885.19557603,\n",
       "         -2839885.19557603, -2839885.19557603, -2839885.19557603]),\n",
       "  'split2_test_score': array([-2900220.26168769, -2900220.26168769, -2900220.26168769,\n",
       "         -2900220.26168769, -2900220.26168769, -2900220.26168769,\n",
       "         -2900220.26168769, -2900220.26168769, -2900220.26168769,\n",
       "         -2900220.26168769, -2900220.26168769, -2900220.26168769,\n",
       "         -2900220.26168769, -2900220.26168769, -2900220.26168769,\n",
       "         -2900220.26168769, -2900220.26168769, -2900220.26168769,\n",
       "         -2900220.26168769, -2900220.26168769, -2900220.26168769,\n",
       "         -2900220.26168769, -2900220.26168769, -2900220.26168769,\n",
       "         -2900220.26168769, -2900220.26168769, -2900220.26168769,\n",
       "         -2900220.26168769, -2900220.26168769, -2900220.26168769,\n",
       "         -2900220.26168769, -2900220.26168769, -2900220.26168769,\n",
       "         -2900220.26168769, -2900220.26168769, -2900220.26168769,\n",
       "         -2900220.26168769, -2900220.26168769, -2900220.26168769,\n",
       "         -2900220.26168769, -2900220.26168769, -2900220.26168769,\n",
       "         -2900220.26168769, -2900220.26168769, -2900220.26168769,\n",
       "         -2900220.26168769, -2900220.26168769, -2900220.26168769,\n",
       "         -2900220.26168769, -2900220.26168769, -2900220.26168769,\n",
       "         -2900220.26168769, -2900220.26168769, -2900220.26168769,\n",
       "         -2900220.26168769, -2900220.26168769, -2900220.26168769,\n",
       "         -2900220.26168769, -2900220.26168769, -2900220.26168769]),\n",
       "  'split2_train_score': array([-2851539.54211191, -2851539.54211191, -2851539.54211191,\n",
       "         -2851539.54211191, -2851539.54211191, -2851539.54211191,\n",
       "         -2851539.54211191, -2851539.54211191, -2851539.54211191,\n",
       "         -2851539.54211191, -2851539.54211191, -2851539.54211191,\n",
       "         -2851539.54211191, -2851539.54211191, -2851539.54211191,\n",
       "         -2851539.54211191, -2851539.54211191, -2851539.54211191,\n",
       "         -2851539.54211191, -2851539.54211191, -2851539.54211191,\n",
       "         -2851539.54211191, -2851539.54211191, -2851539.54211191,\n",
       "         -2851539.54211191, -2851539.54211191, -2851539.54211191,\n",
       "         -2851539.54211191, -2851539.54211191, -2851539.54211191,\n",
       "         -2851539.54211191, -2851539.54211191, -2851539.54211191,\n",
       "         -2851539.54211191, -2851539.54211191, -2851539.54211191,\n",
       "         -2851539.54211191, -2851539.54211191, -2851539.54211191,\n",
       "         -2851539.54211191, -2851539.54211191, -2851539.54211191,\n",
       "         -2851539.54211191, -2851539.54211191, -2851539.54211191,\n",
       "         -2851539.54211191, -2851539.54211191, -2851539.54211191,\n",
       "         -2851539.54211191, -2851539.54211191, -2851539.54211191,\n",
       "         -2851539.54211191, -2851539.54211191, -2851539.54211191,\n",
       "         -2851539.54211191, -2851539.54211191, -2851539.54211191,\n",
       "         -2851539.54211191, -2851539.54211191, -2851539.54211191]),\n",
       "  'split3_test_score': array([-3040845.81236447, -3040845.81236447, -3040845.81236447,\n",
       "         -3040845.81236447, -3040845.81236447, -3040845.81236447,\n",
       "         -3040845.81236447, -3040845.81236447, -3040845.81236447,\n",
       "         -3040845.81236447, -3040845.81236447, -3040845.81236447,\n",
       "         -3040845.81236447, -3040845.81236447, -3040845.81236447,\n",
       "         -3040845.81236447, -3040845.81236447, -3040845.81236447,\n",
       "         -3040845.81236447, -3040845.81236447, -3040845.81236447,\n",
       "         -3040845.81236447, -3040845.81236447, -3040845.81236447,\n",
       "         -3040845.81236447, -3040845.81236447, -3040845.81236447,\n",
       "         -3040845.81236447, -3040845.81236447, -3040845.81236447,\n",
       "         -3040845.81236447, -3040845.81236447, -3040845.81236447,\n",
       "         -3040845.81236447, -3040845.81236447, -3040845.81236447,\n",
       "         -3040845.81236447, -3040845.81236447, -3040845.81236447,\n",
       "         -3040845.81236447, -3040845.81236447, -3040845.81236447,\n",
       "         -3040845.81236447, -3040845.81236447, -3040845.81236447,\n",
       "         -3040845.81236447, -3040845.81236447, -3040845.81236447,\n",
       "         -3040845.81236447, -3040845.81236447, -3040845.81236447,\n",
       "         -3040845.81236447, -3040845.81236447, -3040845.81236447,\n",
       "         -3040845.81236447, -3040845.81236447, -3040845.81236447,\n",
       "         -3040845.81236447, -3040845.81236447, -3040845.81236447]),\n",
       "  'split3_train_score': array([-2835817.05052385, -2835817.05052385, -2835817.05052385,\n",
       "         -2835817.05052385, -2835817.05052385, -2835817.05052385,\n",
       "         -2835817.05052385, -2835817.05052385, -2835817.05052385,\n",
       "         -2835817.05052385, -2835817.05052385, -2835817.05052385,\n",
       "         -2835817.05052385, -2835817.05052385, -2835817.05052385,\n",
       "         -2835817.05052385, -2835817.05052385, -2835817.05052385,\n",
       "         -2835817.05052385, -2835817.05052385, -2835817.05052385,\n",
       "         -2835817.05052385, -2835817.05052385, -2835817.05052385,\n",
       "         -2835817.05052385, -2835817.05052385, -2835817.05052385,\n",
       "         -2835817.05052385, -2835817.05052385, -2835817.05052385,\n",
       "         -2835817.05052385, -2835817.05052385, -2835817.05052385,\n",
       "         -2835817.05052385, -2835817.05052385, -2835817.05052385,\n",
       "         -2835817.05052385, -2835817.05052385, -2835817.05052385,\n",
       "         -2835817.05052385, -2835817.05052385, -2835817.05052385,\n",
       "         -2835817.05052385, -2835817.05052385, -2835817.05052385,\n",
       "         -2835817.05052385, -2835817.05052385, -2835817.05052385,\n",
       "         -2835817.05052385, -2835817.05052385, -2835817.05052385,\n",
       "         -2835817.05052385, -2835817.05052385, -2835817.05052385,\n",
       "         -2835817.05052385, -2835817.05052385, -2835817.05052385,\n",
       "         -2835817.05052385, -2835817.05052385, -2835817.05052385]),\n",
       "  'split4_test_score': array([-2597060.23592873, -2597060.23592873, -2597060.23592873,\n",
       "         -2597060.23592873, -2597060.23592873, -2597060.23592873,\n",
       "         -2597060.23592873, -2597060.23592873, -2597060.23592873,\n",
       "         -2597060.23592873, -2597060.23592873, -2597060.23592873,\n",
       "         -2597060.23592873, -2597060.23592873, -2597060.23592873,\n",
       "         -2597060.23592873, -2597060.23592873, -2597060.23592873,\n",
       "         -2597060.23592873, -2597060.23592873, -2597060.23592873,\n",
       "         -2597060.23592873, -2597060.23592873, -2597060.23592873,\n",
       "         -2597060.23592873, -2597060.23592873, -2597060.23592873,\n",
       "         -2597060.23592873, -2597060.23592873, -2597060.23592873,\n",
       "         -2597060.23592873, -2597060.23592873, -2597060.23592873,\n",
       "         -2597060.23592873, -2597060.23592873, -2597060.23592873,\n",
       "         -2597060.23592873, -2597060.23592873, -2597060.23592873,\n",
       "         -2597060.23592873, -2597060.23592873, -2597060.23592873,\n",
       "         -2597060.23592873, -2597060.23592873, -2597060.23592873,\n",
       "         -2597060.23592873, -2597060.23592873, -2597060.23592873,\n",
       "         -2597060.23592873, -2597060.23592873, -2597060.23592873,\n",
       "         -2597060.23592873, -2597060.23592873, -2597060.23592873,\n",
       "         -2597060.23592873, -2597060.23592873, -2597060.23592873,\n",
       "         -2597060.23592873, -2597060.23592873, -2597060.23592873]),\n",
       "  'split4_train_score': array([-2885189.47261286, -2885189.47261286, -2885189.47261286,\n",
       "         -2885189.47261286, -2885189.47261286, -2885189.47261286,\n",
       "         -2885189.47261286, -2885189.47261286, -2885189.47261286,\n",
       "         -2885189.47261286, -2885189.47261286, -2885189.47261286,\n",
       "         -2885189.47261286, -2885189.47261286, -2885189.47261286,\n",
       "         -2885189.47261286, -2885189.47261286, -2885189.47261286,\n",
       "         -2885189.47261286, -2885189.47261286, -2885189.47261286,\n",
       "         -2885189.47261286, -2885189.47261286, -2885189.47261286,\n",
       "         -2885189.47261286, -2885189.47261286, -2885189.47261286,\n",
       "         -2885189.47261286, -2885189.47261286, -2885189.47261286,\n",
       "         -2885189.47261286, -2885189.47261286, -2885189.47261286,\n",
       "         -2885189.47261286, -2885189.47261286, -2885189.47261286,\n",
       "         -2885189.47261286, -2885189.47261286, -2885189.47261286,\n",
       "         -2885189.47261286, -2885189.47261286, -2885189.47261286,\n",
       "         -2885189.47261286, -2885189.47261286, -2885189.47261286,\n",
       "         -2885189.47261286, -2885189.47261286, -2885189.47261286,\n",
       "         -2885189.47261286, -2885189.47261286, -2885189.47261286,\n",
       "         -2885189.47261286, -2885189.47261286, -2885189.47261286,\n",
       "         -2885189.47261286, -2885189.47261286, -2885189.47261286,\n",
       "         -2885189.47261286, -2885189.47261286, -2885189.47261286]),\n",
       "  'split5_test_score': array([-2638127.39274796, -2638127.39274796, -2638127.39274796,\n",
       "         -2638127.39274796, -2638127.39274796, -2638127.39274796,\n",
       "         -2638127.39274796, -2638127.39274796, -2638127.39274796,\n",
       "         -2638127.39274796, -2638127.39274796, -2638127.39274796,\n",
       "         -2638127.39274796, -2638127.39274796, -2638127.39274796,\n",
       "         -2638127.39274796, -2638127.39274796, -2638127.39274796,\n",
       "         -2638127.39274796, -2638127.39274796, -2638127.39274796,\n",
       "         -2638127.39274796, -2638127.39274796, -2638127.39274796,\n",
       "         -2638127.39274796, -2638127.39274796, -2638127.39274796,\n",
       "         -2638127.39274796, -2638127.39274796, -2638127.39274796,\n",
       "         -2638127.39274796, -2638127.39274796, -2638127.39274796,\n",
       "         -2638127.39274796, -2638127.39274796, -2638127.39274796,\n",
       "         -2638127.39274796, -2638127.39274796, -2638127.39274796,\n",
       "         -2638127.39274796, -2638127.39274796, -2638127.39274796,\n",
       "         -2638127.39274796, -2638127.39274796, -2638127.39274796,\n",
       "         -2638127.39274796, -2638127.39274796, -2638127.39274796,\n",
       "         -2638127.39274796, -2638127.39274796, -2638127.39274796,\n",
       "         -2638127.39274796, -2638127.39274796, -2638127.39274796,\n",
       "         -2638127.39274796, -2638127.39274796, -2638127.39274796,\n",
       "         -2638127.39274796, -2638127.39274796, -2638127.39274796]),\n",
       "  'split5_train_score': array([-2880663.85156337, -2880663.85156337, -2880663.85156337,\n",
       "         -2880663.85156337, -2880663.85156337, -2880663.85156337,\n",
       "         -2880663.85156337, -2880663.85156337, -2880663.85156337,\n",
       "         -2880663.85156337, -2880663.85156337, -2880663.85156337,\n",
       "         -2880663.85156337, -2880663.85156337, -2880663.85156337,\n",
       "         -2880663.85156337, -2880663.85156337, -2880663.85156337,\n",
       "         -2880663.85156337, -2880663.85156337, -2880663.85156337,\n",
       "         -2880663.85156337, -2880663.85156337, -2880663.85156337,\n",
       "         -2880663.85156337, -2880663.85156337, -2880663.85156337,\n",
       "         -2880663.85156337, -2880663.85156337, -2880663.85156337,\n",
       "         -2880663.85156337, -2880663.85156337, -2880663.85156337,\n",
       "         -2880663.85156337, -2880663.85156337, -2880663.85156337,\n",
       "         -2880663.85156337, -2880663.85156337, -2880663.85156337,\n",
       "         -2880663.85156337, -2880663.85156337, -2880663.85156337,\n",
       "         -2880663.85156337, -2880663.85156337, -2880663.85156337,\n",
       "         -2880663.85156337, -2880663.85156337, -2880663.85156337,\n",
       "         -2880663.85156337, -2880663.85156337, -2880663.85156337,\n",
       "         -2880663.85156337, -2880663.85156337, -2880663.85156337,\n",
       "         -2880663.85156337, -2880663.85156337, -2880663.85156337,\n",
       "         -2880663.85156337, -2880663.85156337, -2880663.85156337]),\n",
       "  'split6_test_score': array([-3189750.79887701, -3189750.79887701, -3189750.79887701,\n",
       "         -3189750.79887701, -3189750.79887701, -3189750.79887701,\n",
       "         -3189750.79887701, -3189750.79887701, -3189750.79887701,\n",
       "         -3189750.79887701, -3189750.79887701, -3189750.79887701,\n",
       "         -3189750.79887701, -3189750.79887701, -3189750.79887701,\n",
       "         -3189750.79887701, -3189750.79887701, -3189750.79887701,\n",
       "         -3189750.79887701, -3189750.79887701, -3189750.79887701,\n",
       "         -3189750.79887701, -3189750.79887701, -3189750.79887701,\n",
       "         -3189750.79887701, -3189750.79887701, -3189750.79887701,\n",
       "         -3189750.79887701, -3189750.79887701, -3189750.79887701,\n",
       "         -3189750.79887701, -3189750.79887701, -3189750.79887701,\n",
       "         -3189750.79887701, -3189750.79887701, -3189750.79887701,\n",
       "         -3189750.79887701, -3189750.79887701, -3189750.79887701,\n",
       "         -3189750.79887701, -3189750.79887701, -3189750.79887701,\n",
       "         -3189750.79887701, -3189750.79887701, -3189750.79887701,\n",
       "         -3189750.79887701, -3189750.79887701, -3189750.79887701,\n",
       "         -3189750.79887701, -3189750.79887701, -3189750.79887701,\n",
       "         -3189750.79887701, -3189750.79887701, -3189750.79887701,\n",
       "         -3189750.79887701, -3189750.79887701, -3189750.79887701,\n",
       "         -3189750.79887701, -3189750.79887701, -3189750.79887701]),\n",
       "  'split6_train_score': array([-2819349.3472314, -2819349.3472314, -2819349.3472314,\n",
       "         -2819349.3472314, -2819349.3472314, -2819349.3472314,\n",
       "         -2819349.3472314, -2819349.3472314, -2819349.3472314,\n",
       "         -2819349.3472314, -2819349.3472314, -2819349.3472314,\n",
       "         -2819349.3472314, -2819349.3472314, -2819349.3472314,\n",
       "         -2819349.3472314, -2819349.3472314, -2819349.3472314,\n",
       "         -2819349.3472314, -2819349.3472314, -2819349.3472314,\n",
       "         -2819349.3472314, -2819349.3472314, -2819349.3472314,\n",
       "         -2819349.3472314, -2819349.3472314, -2819349.3472314,\n",
       "         -2819349.3472314, -2819349.3472314, -2819349.3472314,\n",
       "         -2819349.3472314, -2819349.3472314, -2819349.3472314,\n",
       "         -2819349.3472314, -2819349.3472314, -2819349.3472314,\n",
       "         -2819349.3472314, -2819349.3472314, -2819349.3472314,\n",
       "         -2819349.3472314, -2819349.3472314, -2819349.3472314,\n",
       "         -2819349.3472314, -2819349.3472314, -2819349.3472314,\n",
       "         -2819349.3472314, -2819349.3472314, -2819349.3472314,\n",
       "         -2819349.3472314, -2819349.3472314, -2819349.3472314,\n",
       "         -2819349.3472314, -2819349.3472314, -2819349.3472314,\n",
       "         -2819349.3472314, -2819349.3472314, -2819349.3472314,\n",
       "         -2819349.3472314, -2819349.3472314, -2819349.3472314]),\n",
       "  'split7_test_score': array([-2960112.49809488, -2960112.49809488, -2960112.49809488,\n",
       "         -2960112.49809488, -2960112.49809488, -2960112.49809488,\n",
       "         -2960112.49809488, -2960112.49809488, -2960112.49809488,\n",
       "         -2960112.49809488, -2960112.49809488, -2960112.49809488,\n",
       "         -2960112.49809488, -2960112.49809488, -2960112.49809488,\n",
       "         -2960112.49809488, -2960112.49809488, -2960112.49809488,\n",
       "         -2960112.49809488, -2960112.49809488, -2960112.49809488,\n",
       "         -2960112.49809488, -2960112.49809488, -2960112.49809488,\n",
       "         -2960112.49809488, -2960112.49809488, -2960112.49809488,\n",
       "         -2960112.49809488, -2960112.49809488, -2960112.49809488,\n",
       "         -2960112.49809488, -2960112.49809488, -2960112.49809488,\n",
       "         -2960112.49809488, -2960112.49809488, -2960112.49809488,\n",
       "         -2960112.49809488, -2960112.49809488, -2960112.49809488,\n",
       "         -2960112.49809488, -2960112.49809488, -2960112.49809488,\n",
       "         -2960112.49809488, -2960112.49809488, -2960112.49809488,\n",
       "         -2960112.49809488, -2960112.49809488, -2960112.49809488,\n",
       "         -2960112.49809488, -2960112.49809488, -2960112.49809488,\n",
       "         -2960112.49809488, -2960112.49809488, -2960112.49809488,\n",
       "         -2960112.49809488, -2960112.49809488, -2960112.49809488,\n",
       "         -2960112.49809488, -2960112.49809488, -2960112.49809488]),\n",
       "  'split7_train_score': array([-2844814.40457342, -2844814.40457342, -2844814.40457342,\n",
       "         -2844814.40457342, -2844814.40457342, -2844814.40457342,\n",
       "         -2844814.40457342, -2844814.40457342, -2844814.40457342,\n",
       "         -2844814.40457342, -2844814.40457342, -2844814.40457342,\n",
       "         -2844814.40457342, -2844814.40457342, -2844814.40457342,\n",
       "         -2844814.40457342, -2844814.40457342, -2844814.40457342,\n",
       "         -2844814.40457342, -2844814.40457342, -2844814.40457342,\n",
       "         -2844814.40457342, -2844814.40457342, -2844814.40457342,\n",
       "         -2844814.40457342, -2844814.40457342, -2844814.40457342,\n",
       "         -2844814.40457342, -2844814.40457342, -2844814.40457342,\n",
       "         -2844814.40457342, -2844814.40457342, -2844814.40457342,\n",
       "         -2844814.40457342, -2844814.40457342, -2844814.40457342,\n",
       "         -2844814.40457342, -2844814.40457342, -2844814.40457342,\n",
       "         -2844814.40457342, -2844814.40457342, -2844814.40457342,\n",
       "         -2844814.40457342, -2844814.40457342, -2844814.40457342,\n",
       "         -2844814.40457342, -2844814.40457342, -2844814.40457342,\n",
       "         -2844814.40457342, -2844814.40457342, -2844814.40457342,\n",
       "         -2844814.40457342, -2844814.40457342, -2844814.40457342,\n",
       "         -2844814.40457342, -2844814.40457342, -2844814.40457342,\n",
       "         -2844814.40457342, -2844814.40457342, -2844814.40457342]),\n",
       "  'split8_test_score': array([-2641999.82177895, -2641999.82177895, -2641999.82177895,\n",
       "         -2641999.82177895, -2641999.82177895, -2641999.82177895,\n",
       "         -2641999.82177895, -2641999.82177895, -2641999.82177895,\n",
       "         -2641999.82177895, -2641999.82177895, -2641999.82177895,\n",
       "         -2641999.82177895, -2641999.82177895, -2641999.82177895,\n",
       "         -2641999.82177895, -2641999.82177895, -2641999.82177895,\n",
       "         -2641999.82177895, -2641999.82177895, -2641999.82177895,\n",
       "         -2641999.82177895, -2641999.82177895, -2641999.82177895,\n",
       "         -2641999.82177895, -2641999.82177895, -2641999.82177895,\n",
       "         -2641999.82177895, -2641999.82177895, -2641999.82177895,\n",
       "         -2641999.82177895, -2641999.82177895, -2641999.82177895,\n",
       "         -2641999.82177895, -2641999.82177895, -2641999.82177895,\n",
       "         -2641999.82177895, -2641999.82177895, -2641999.82177895,\n",
       "         -2641999.82177895, -2641999.82177895, -2641999.82177895,\n",
       "         -2641999.82177895, -2641999.82177895, -2641999.82177895,\n",
       "         -2641999.82177895, -2641999.82177895, -2641999.82177895,\n",
       "         -2641999.82177895, -2641999.82177895, -2641999.82177895,\n",
       "         -2641999.82177895, -2641999.82177895, -2641999.82177895,\n",
       "         -2641999.82177895, -2641999.82177895, -2641999.82177895,\n",
       "         -2641999.82177895, -2641999.82177895, -2641999.82177895]),\n",
       "  'split8_train_score': array([-2880121.03767345, -2880121.03767345, -2880121.03767345,\n",
       "         -2880121.03767345, -2880121.03767345, -2880121.03767345,\n",
       "         -2880121.03767345, -2880121.03767345, -2880121.03767345,\n",
       "         -2880121.03767345, -2880121.03767345, -2880121.03767345,\n",
       "         -2880121.03767345, -2880121.03767345, -2880121.03767345,\n",
       "         -2880121.03767345, -2880121.03767345, -2880121.03767345,\n",
       "         -2880121.03767345, -2880121.03767345, -2880121.03767345,\n",
       "         -2880121.03767345, -2880121.03767345, -2880121.03767345,\n",
       "         -2880121.03767345, -2880121.03767345, -2880121.03767345,\n",
       "         -2880121.03767345, -2880121.03767345, -2880121.03767345,\n",
       "         -2880121.03767345, -2880121.03767345, -2880121.03767345,\n",
       "         -2880121.03767345, -2880121.03767345, -2880121.03767345,\n",
       "         -2880121.03767345, -2880121.03767345, -2880121.03767345,\n",
       "         -2880121.03767345, -2880121.03767345, -2880121.03767345,\n",
       "         -2880121.03767345, -2880121.03767345, -2880121.03767345,\n",
       "         -2880121.03767345, -2880121.03767345, -2880121.03767345,\n",
       "         -2880121.03767345, -2880121.03767345, -2880121.03767345,\n",
       "         -2880121.03767345, -2880121.03767345, -2880121.03767345,\n",
       "         -2880121.03767345, -2880121.03767345, -2880121.03767345,\n",
       "         -2880121.03767345, -2880121.03767345, -2880121.03767345]),\n",
       "  'split9_test_score': array([-2822291.76392641, -2822291.76392641, -2822291.76392641,\n",
       "         -2822291.76392641, -2822291.76392641, -2822291.76392641,\n",
       "         -2822291.76392641, -2822291.76392641, -2822291.76392641,\n",
       "         -2822291.76392641, -2822291.76392641, -2822291.76392641,\n",
       "         -2822291.76392641, -2822291.76392641, -2822291.76392641,\n",
       "         -2822291.76392641, -2822291.76392641, -2822291.76392641,\n",
       "         -2822291.76392641, -2822291.76392641, -2822291.76392641,\n",
       "         -2822291.76392641, -2822291.76392641, -2822291.76392641,\n",
       "         -2822291.76392641, -2822291.76392641, -2822291.76392641,\n",
       "         -2822291.76392641, -2822291.76392641, -2822291.76392641,\n",
       "         -2822291.76392641, -2822291.76392641, -2822291.76392641,\n",
       "         -2822291.76392641, -2822291.76392641, -2822291.76392641,\n",
       "         -2822291.76392641, -2822291.76392641, -2822291.76392641,\n",
       "         -2822291.76392641, -2822291.76392641, -2822291.76392641,\n",
       "         -2822291.76392641, -2822291.76392641, -2822291.76392641,\n",
       "         -2822291.76392641, -2822291.76392641, -2822291.76392641,\n",
       "         -2822291.76392641, -2822291.76392641, -2822291.76392641,\n",
       "         -2822291.76392641, -2822291.76392641, -2822291.76392641,\n",
       "         -2822291.76392641, -2822291.76392641, -2822291.76392641,\n",
       "         -2822291.76392641, -2822291.76392641, -2822291.76392641]),\n",
       "  'split9_train_score': array([-2860177.80742235, -2860177.80742235, -2860177.80742235,\n",
       "         -2860177.80742235, -2860177.80742235, -2860177.80742235,\n",
       "         -2860177.80742235, -2860177.80742235, -2860177.80742235,\n",
       "         -2860177.80742235, -2860177.80742235, -2860177.80742235,\n",
       "         -2860177.80742235, -2860177.80742235, -2860177.80742235,\n",
       "         -2860177.80742235, -2860177.80742235, -2860177.80742235,\n",
       "         -2860177.80742235, -2860177.80742235, -2860177.80742235,\n",
       "         -2860177.80742235, -2860177.80742235, -2860177.80742235,\n",
       "         -2860177.80742235, -2860177.80742235, -2860177.80742235,\n",
       "         -2860177.80742235, -2860177.80742235, -2860177.80742235,\n",
       "         -2860177.80742235, -2860177.80742235, -2860177.80742235,\n",
       "         -2860177.80742235, -2860177.80742235, -2860177.80742235,\n",
       "         -2860177.80742235, -2860177.80742235, -2860177.80742235,\n",
       "         -2860177.80742235, -2860177.80742235, -2860177.80742235,\n",
       "         -2860177.80742235, -2860177.80742235, -2860177.80742235,\n",
       "         -2860177.80742235, -2860177.80742235, -2860177.80742235,\n",
       "         -2860177.80742235, -2860177.80742235, -2860177.80742235,\n",
       "         -2860177.80742235, -2860177.80742235, -2860177.80742235,\n",
       "         -2860177.80742235, -2860177.80742235, -2860177.80742235,\n",
       "         -2860177.80742235, -2860177.80742235, -2860177.80742235]),\n",
       "  'std_fit_time': array([ 0.07003647,  0.10939787,  0.05440079,  0.02323791,  0.03195635,\n",
       "          0.03409246,  0.0282477 ,  0.02728663,  0.05661752,  0.02864217,\n",
       "          0.02856771,  0.03186752,  0.01999223,  0.02947235,  0.01818718,\n",
       "          0.02841084,  0.01647963,  0.01827562,  0.02302459,  0.0146498 ,\n",
       "          0.01572038,  0.02434109,  0.01782538,  0.03329793,  0.01579261,\n",
       "          0.01928341,  0.04728298,  0.01589499,  0.02538911,  0.02026158,\n",
       "          0.01974127,  0.01091489,  0.01429731,  0.01568751,  0.01371622,\n",
       "          0.0151309 ,  0.02100357,  0.01738316,  0.0182147 ,  0.01243647,\n",
       "          0.01681152,  0.02418367,  0.01373587,  0.00942205,  0.02741182,\n",
       "          0.02317303,  0.01889606,  0.02620571,  0.04094543,  0.01726726,\n",
       "          0.01348773,  0.01830132,  0.02333939,  0.02221836,  0.01965785,\n",
       "          0.02402031,  0.01452782,  0.0159529 ,  0.02381651,  0.06272376]),\n",
       "  'std_score_time': array([ 0.00600049,  0.01381409,  0.00844949,  0.01087642,  0.00841234,\n",
       "          0.01482654,  0.00793956,  0.00849723,  0.00944325,  0.00894834,\n",
       "          0.00945621,  0.00970096,  0.01876238,  0.01416629,  0.01260631,\n",
       "          0.01033665,  0.01104499,  0.01708854,  0.01543645,  0.0088805 ,\n",
       "          0.01224368,  0.01137507,  0.01308997,  0.00976282,  0.00824619,\n",
       "          0.01415281,  0.00685542,  0.00783131,  0.01489142,  0.00810487,\n",
       "          0.01141579,  0.00778709,  0.01556294,  0.01054666,  0.00895094,\n",
       "          0.01722476,  0.01157164,  0.00981526,  0.00873521,  0.0088544 ,\n",
       "          0.00882836,  0.00870744,  0.01191126,  0.00928156,  0.01427147,\n",
       "          0.01047817,  0.01234109,  0.01317315,  0.01317103,  0.01201124,\n",
       "          0.01020182,  0.01235683,  0.01542119,  0.01235834,  0.01237864,\n",
       "          0.00981357,  0.0155668 ,  0.00774542,  0.00869656,  0.02070143]),\n",
       "  'std_test_score': array([ 186608.27010713,  186608.27010713,  186608.27010713,\n",
       "          186608.27010713,  186608.27010713,  186608.27010713,\n",
       "          186608.27010713,  186608.27010713,  186608.27010713,\n",
       "          186608.27010713,  186608.27010713,  186608.27010713,\n",
       "          186608.27010713,  186608.27010713,  186608.27010713,\n",
       "          186608.27010713,  186608.27010713,  186608.27010713,\n",
       "          186608.27010713,  186608.27010713,  186608.27010713,\n",
       "          186608.27010713,  186608.27010713,  186608.27010713,\n",
       "          186608.27010713,  186608.27010713,  186608.27010713,\n",
       "          186608.27010713,  186608.27010713,  186608.27010713,\n",
       "          186608.27010713,  186608.27010713,  186608.27010713,\n",
       "          186608.27010713,  186608.27010713,  186608.27010713,\n",
       "          186608.27010713,  186608.27010713,  186608.27010713,\n",
       "          186608.27010713,  186608.27010713,  186608.27010713,\n",
       "          186608.27010713,  186608.27010713,  186608.27010713,\n",
       "          186608.27010713,  186608.27010713,  186608.27010713,\n",
       "          186608.27010713,  186608.27010713,  186608.27010713,\n",
       "          186608.27010713,  186608.27010713,  186608.27010713,\n",
       "          186608.27010713,  186608.27010713,  186608.27010713,\n",
       "          186608.27010713,  186608.27010713,  186608.27010713]),\n",
       "  'std_train_score': array([ 20741.06866676,  20741.06866676,  20741.06866676,  20741.06866676,\n",
       "          20741.06866676,  20741.06866676,  20741.06866676,  20741.06866676,\n",
       "          20741.06866676,  20741.06866676,  20741.06866676,  20741.06866676,\n",
       "          20741.06866676,  20741.06866676,  20741.06866676,  20741.06866676,\n",
       "          20741.06866676,  20741.06866676,  20741.06866676,  20741.06866676,\n",
       "          20741.06866676,  20741.06866676,  20741.06866676,  20741.06866676,\n",
       "          20741.06866676,  20741.06866676,  20741.06866676,  20741.06866676,\n",
       "          20741.06866676,  20741.06866676,  20741.06866676,  20741.06866676,\n",
       "          20741.06866676,  20741.06866676,  20741.06866676,  20741.06866676,\n",
       "          20741.06866676,  20741.06866676,  20741.06866676,  20741.06866676,\n",
       "          20741.06866676,  20741.06866676,  20741.06866676,  20741.06866676,\n",
       "          20741.06866676,  20741.06866676,  20741.06866676,  20741.06866676,\n",
       "          20741.06866676,  20741.06866676,  20741.06866676,  20741.06866676,\n",
       "          20741.06866676,  20741.06866676,  20741.06866676,  20741.06866676,\n",
       "          20741.06866676,  20741.06866676,  20741.06866676,  20741.06866676])},\n",
       " {'l2': 0.1, 'max_leaf': 1000, 'min_samples_leaf': 4},\n",
       " -2857080.4882552344)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rgf_model = gsearch.fit(X_train, y_train)\n",
    "rgf_model.cv_results_, rgf_model.best_params_, rgf_model.best_score_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 2173.45  2173.45  2173.45 ...,  2173.45  2173.45  2173.45]\n"
     ]
    }
   ],
   "source": [
    "y_pred = rgf_model.predict(X_validation)\n",
    "print(y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean squared error: 3041420.35\n",
      "Variance score: -0.00\n"
     ]
    }
   ],
   "source": [
    "# The mean squared error\n",
    "print(\"Mean squared error: %.2f\"\n",
    "      % mean_squared_error(y_validation, y_pred))\n",
    "# Explained variance score: 1 is perfect prediction\n",
    "print('Variance score: %.2f' % r2_score(y_validation, y_pred))"
   ]
  }
 ],
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