Clean HPCC Data.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# First read the 'sklearn-benchmark-data.tsv.gz' file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "benchmark_data = pd.read_csv('sklearn-benchmark-data.tsv.gz', sep='\\t')\n",
    "benchmark_data.head()\n",
    "benchmark_data.rename(columns={'heart-c':'Dataset_Name',\n",
    "                               'GradientBoostingClassifier':'Method_Name',\n",
    "                               'loss=exponential,learning_rate=10.0,n_estimators=100,max_depth=3,max_features=sqrt,warm_start=True':\n",
    "                               'Parameters',\n",
    "                               '0.723684210526':'Test_Score'},inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get all the method names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "methodNames_list = benchmark_data['Method_Name'].unique().tolist()\n",
    "#methodNames_list"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Store the data method wise separately"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "methodWiseData = {}\n",
    "for name in methodNames_list:\n",
    "    methodWiseData[name] = benchmark_data[(benchmark_data.Method_Name == name)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Save the data method wise to a folder in tsv.gz format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#for i in names_list:\n",
    "#    print(d[i])\n",
    "import os\n",
    "if not os.path.isdir('newBenchmark_results'):\n",
    "    os.mkdir('newBenchmark_results')\n",
    "\n",
    "gb = methodWiseData['GradientBoostingClassifier']\n",
    "gb.to_pickle('newBenchmark_results/GradientBoostingClassifier_results.tsv.gz')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Dataset_Name</th>\n",
       "      <th>Method_Name</th>\n",
       "      <th>Parameters</th>\n",
       "      <th>Test_Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.736842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.815789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.802632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.815789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.684211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.763158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.710526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.776316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.723684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.736842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.789474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.789474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.736842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.736842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.776316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.763158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.802632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.815789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.828947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.736842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.736842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.789474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.815789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.697368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.842105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=exponential,learning_rate=10.0,n_estimato...</td>\n",
       "      <td>0.776316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=50.0,n_estimators=...</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2162999</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163000</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163001</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163002</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163003</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163004</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163005</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163006</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163007</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163008</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163009</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163010</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163011</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163012</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163013</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163014</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163015</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163016</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163017</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163018</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163019</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163020</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163021</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163022</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163023</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163024</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163025</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163026</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163027</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2163028</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>loss=deviance,learning_rate=0.5,n_estimators=1...</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1527509 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Dataset_Name                 Method_Name  \\\n",
       "0                        heart-c  GradientBoostingClassifier   \n",
       "1                        heart-c  GradientBoostingClassifier   \n",
       "2                        heart-c  GradientBoostingClassifier   \n",
       "3                        heart-c  GradientBoostingClassifier   \n",
       "4                        heart-c  GradientBoostingClassifier   \n",
       "5                        heart-c  GradientBoostingClassifier   \n",
       "6                        heart-c  GradientBoostingClassifier   \n",
       "7                        heart-c  GradientBoostingClassifier   \n",
       "8                        heart-c  GradientBoostingClassifier   \n",
       "9                        heart-c  GradientBoostingClassifier   \n",
       "10                       heart-c  GradientBoostingClassifier   \n",
       "11                       heart-c  GradientBoostingClassifier   \n",
       "12                       heart-c  GradientBoostingClassifier   \n",
       "13                       heart-c  GradientBoostingClassifier   \n",
       "14                       heart-c  GradientBoostingClassifier   \n",
       "15                       heart-c  GradientBoostingClassifier   \n",
       "16                       heart-c  GradientBoostingClassifier   \n",
       "17                       heart-c  GradientBoostingClassifier   \n",
       "18                       heart-c  GradientBoostingClassifier   \n",
       "19                       heart-c  GradientBoostingClassifier   \n",
       "20                       heart-c  GradientBoostingClassifier   \n",
       "21                       heart-c  GradientBoostingClassifier   \n",
       "22                       heart-c  GradientBoostingClassifier   \n",
       "23                       heart-c  GradientBoostingClassifier   \n",
       "24                       heart-c  GradientBoostingClassifier   \n",
       "25                       heart-c  GradientBoostingClassifier   \n",
       "26                       heart-c  GradientBoostingClassifier   \n",
       "27                       heart-c  GradientBoostingClassifier   \n",
       "28                       heart-c  GradientBoostingClassifier   \n",
       "29       shuttle-landing-control  GradientBoostingClassifier   \n",
       "...                          ...                         ...   \n",
       "2162999  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163000  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163001  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163002  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163003  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163004  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163005  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163006  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163007  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163008  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163009  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163010  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163011  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163012  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163013  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163014  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163015  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163016  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163017  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163018  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163019  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163020  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163021  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163022  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163023  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163024  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163025  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163026  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163027  shuttle-landing-control  GradientBoostingClassifier   \n",
       "2163028  shuttle-landing-control  GradientBoostingClassifier   \n",
       "\n",
       "                                                Parameters  Test_Score  \n",
       "0        loss=exponential,learning_rate=10.0,n_estimato...    0.736842  \n",
       "1        loss=exponential,learning_rate=10.0,n_estimato...    0.815789  \n",
       "2        loss=exponential,learning_rate=10.0,n_estimato...    0.802632  \n",
       "3        loss=exponential,learning_rate=10.0,n_estimato...    0.750000  \n",
       "4        loss=exponential,learning_rate=10.0,n_estimato...    0.815789  \n",
       "5        loss=exponential,learning_rate=10.0,n_estimato...    0.684211  \n",
       "6        loss=exponential,learning_rate=10.0,n_estimato...    0.763158  \n",
       "7        loss=exponential,learning_rate=10.0,n_estimato...    0.750000  \n",
       "8        loss=exponential,learning_rate=10.0,n_estimato...    0.710526  \n",
       "9        loss=exponential,learning_rate=10.0,n_estimato...    0.776316  \n",
       "10       loss=exponential,learning_rate=10.0,n_estimato...    0.723684  \n",
       "11       loss=exponential,learning_rate=10.0,n_estimato...    0.736842  \n",
       "12       loss=exponential,learning_rate=10.0,n_estimato...    0.789474  \n",
       "13       loss=exponential,learning_rate=10.0,n_estimato...    0.789474  \n",
       "14       loss=exponential,learning_rate=10.0,n_estimato...    0.736842  \n",
       "15       loss=exponential,learning_rate=10.0,n_estimato...    0.736842  \n",
       "16       loss=exponential,learning_rate=10.0,n_estimato...    0.776316  \n",
       "17       loss=exponential,learning_rate=10.0,n_estimato...    0.763158  \n",
       "18       loss=exponential,learning_rate=10.0,n_estimato...    0.802632  \n",
       "19       loss=exponential,learning_rate=10.0,n_estimato...    0.815789  \n",
       "20       loss=exponential,learning_rate=10.0,n_estimato...    0.828947  \n",
       "21       loss=exponential,learning_rate=10.0,n_estimato...    0.736842  \n",
       "22       loss=exponential,learning_rate=10.0,n_estimato...    0.736842  \n",
       "23       loss=exponential,learning_rate=10.0,n_estimato...    0.750000  \n",
       "24       loss=exponential,learning_rate=10.0,n_estimato...    0.789474  \n",
       "25       loss=exponential,learning_rate=10.0,n_estimato...    0.815789  \n",
       "26       loss=exponential,learning_rate=10.0,n_estimato...    0.697368  \n",
       "27       loss=exponential,learning_rate=10.0,n_estimato...    0.842105  \n",
       "28       loss=exponential,learning_rate=10.0,n_estimato...    0.776316  \n",
       "29       loss=deviance,learning_rate=50.0,n_estimators=...    0.750000  \n",
       "...                                                    ...         ...  \n",
       "2162999  loss=deviance,learning_rate=0.5,n_estimators=1...    0.500000  \n",
       "2163000  loss=deviance,learning_rate=0.5,n_estimators=1...    0.750000  \n",
       "2163001  loss=deviance,learning_rate=0.5,n_estimators=1...    0.750000  \n",
       "2163002  loss=deviance,learning_rate=0.5,n_estimators=1...    0.500000  \n",
       "2163003  loss=deviance,learning_rate=0.5,n_estimators=1...    0.750000  \n",
       "2163004  loss=deviance,learning_rate=0.5,n_estimators=1...    0.750000  \n",
       "2163005  loss=deviance,learning_rate=0.5,n_estimators=1...    0.750000  \n",
       "2163006  loss=deviance,learning_rate=0.5,n_estimators=1...    0.250000  \n",
       "2163007  loss=deviance,learning_rate=0.5,n_estimators=1...    0.750000  \n",
       "2163008  loss=deviance,learning_rate=0.5,n_estimators=1...    0.750000  \n",
       "2163009  loss=deviance,learning_rate=0.5,n_estimators=1...    1.000000  \n",
       "2163010  loss=deviance,learning_rate=0.5,n_estimators=1...    0.500000  \n",
       "2163011  loss=deviance,learning_rate=0.5,n_estimators=1...    1.000000  \n",
       "2163012  loss=deviance,learning_rate=0.5,n_estimators=1...    0.750000  \n",
       "2163013  loss=deviance,learning_rate=0.5,n_estimators=1...    0.750000  \n",
       "2163014  loss=deviance,learning_rate=0.5,n_estimators=1...    0.750000  \n",
       "2163015  loss=deviance,learning_rate=0.5,n_estimators=1...    0.750000  \n",
       "2163016  loss=deviance,learning_rate=0.5,n_estimators=1...    0.750000  \n",
       "2163017  loss=deviance,learning_rate=0.5,n_estimators=1...    0.500000  \n",
       "2163018  loss=deviance,learning_rate=0.5,n_estimators=1...    0.500000  \n",
       "2163019  loss=deviance,learning_rate=0.5,n_estimators=1...    0.500000  \n",
       "2163020  loss=deviance,learning_rate=0.5,n_estimators=1...    0.500000  \n",
       "2163021  loss=deviance,learning_rate=0.5,n_estimators=1...    0.750000  \n",
       "2163022  loss=deviance,learning_rate=0.5,n_estimators=1...    0.750000  \n",
       "2163023  loss=deviance,learning_rate=0.5,n_estimators=1...    1.000000  \n",
       "2163024  loss=deviance,learning_rate=0.5,n_estimators=1...    0.500000  \n",
       "2163025  loss=deviance,learning_rate=0.5,n_estimators=1...    0.500000  \n",
       "2163026  loss=deviance,learning_rate=0.5,n_estimators=1...    0.500000  \n",
       "2163027  loss=deviance,learning_rate=0.5,n_estimators=1...    0.250000  \n",
       "2163028  loss=deviance,learning_rate=0.5,n_estimators=1...    0.500000  \n",
       "\n",
       "[1527509 rows x 4 columns]"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "method_data = pd.read_pickle('newBenchmark_results/GradientBoostingClassifier-benchmark_results.tsv.gz')\n",
    "method_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Split the parameters into dfifferent columns;\n",
    "# make sure to set the no of coumns according to different methods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Param1</th>\n",
       "      <th>Param2</th>\n",
       "      <th>Param3</th>\n",
       "      <th>Param4</th>\n",
       "      <th>Param5</th>\n",
       "      <th>Param6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=50.0</td>\n",
       "      <td>n_estimators=10</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=log2</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527479</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527480</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527481</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527482</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527483</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527484</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527485</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527486</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527487</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527488</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527489</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527490</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527491</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527492</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527493</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527494</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527495</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527496</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527497</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527498</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527499</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527500</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527501</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527502</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527503</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527504</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527505</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527506</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527507</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527508</th>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1527509 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Param1              Param2             Param3       Param4  \\\n",
       "0        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "1        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "2        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "3        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "4        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "5        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "6        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "7        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "8        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "9        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "10       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "11       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "12       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "13       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "14       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "15       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "16       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "17       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "18       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "19       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "20       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "21       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "22       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "23       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "24       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "25       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "26       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "27       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "28       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "29          loss=deviance  learning_rate=50.0    n_estimators=10  max_depth=2   \n",
       "...                   ...                 ...                ...          ...   \n",
       "1527479     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527480     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527481     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527482     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527483     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527484     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527485     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527486     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527487     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527488     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527489     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527490     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527491     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527492     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527493     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527494     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527495     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527496     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527497     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527498     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527499     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527500     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527501     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527502     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527503     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527504     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527505     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527506     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527507     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527508     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "\n",
       "                    Param5           Param6  \n",
       "0        max_features=sqrt  warm_start=True  \n",
       "1        max_features=sqrt  warm_start=True  \n",
       "2        max_features=sqrt  warm_start=True  \n",
       "3        max_features=sqrt  warm_start=True  \n",
       "4        max_features=sqrt  warm_start=True  \n",
       "5        max_features=sqrt  warm_start=True  \n",
       "6        max_features=sqrt  warm_start=True  \n",
       "7        max_features=sqrt  warm_start=True  \n",
       "8        max_features=sqrt  warm_start=True  \n",
       "9        max_features=sqrt  warm_start=True  \n",
       "10       max_features=sqrt  warm_start=True  \n",
       "11       max_features=sqrt  warm_start=True  \n",
       "12       max_features=sqrt  warm_start=True  \n",
       "13       max_features=sqrt  warm_start=True  \n",
       "14       max_features=sqrt  warm_start=True  \n",
       "15       max_features=sqrt  warm_start=True  \n",
       "16       max_features=sqrt  warm_start=True  \n",
       "17       max_features=sqrt  warm_start=True  \n",
       "18       max_features=sqrt  warm_start=True  \n",
       "19       max_features=sqrt  warm_start=True  \n",
       "20       max_features=sqrt  warm_start=True  \n",
       "21       max_features=sqrt  warm_start=True  \n",
       "22       max_features=sqrt  warm_start=True  \n",
       "23       max_features=sqrt  warm_start=True  \n",
       "24       max_features=sqrt  warm_start=True  \n",
       "25       max_features=sqrt  warm_start=True  \n",
       "26       max_features=sqrt  warm_start=True  \n",
       "27       max_features=sqrt  warm_start=True  \n",
       "28       max_features=sqrt  warm_start=True  \n",
       "29       max_features=log2  warm_start=True  \n",
       "...                    ...              ...  \n",
       "1527479  max_features=0.75  warm_start=True  \n",
       "1527480  max_features=0.75  warm_start=True  \n",
       "1527481  max_features=0.75  warm_start=True  \n",
       "1527482  max_features=0.75  warm_start=True  \n",
       "1527483  max_features=0.75  warm_start=True  \n",
       "1527484  max_features=0.75  warm_start=True  \n",
       "1527485  max_features=0.75  warm_start=True  \n",
       "1527486  max_features=0.75  warm_start=True  \n",
       "1527487  max_features=0.75  warm_start=True  \n",
       "1527488  max_features=0.75  warm_start=True  \n",
       "1527489  max_features=0.75  warm_start=True  \n",
       "1527490  max_features=0.75  warm_start=True  \n",
       "1527491  max_features=0.75  warm_start=True  \n",
       "1527492  max_features=0.75  warm_start=True  \n",
       "1527493  max_features=0.75  warm_start=True  \n",
       "1527494  max_features=0.75  warm_start=True  \n",
       "1527495  max_features=0.75  warm_start=True  \n",
       "1527496  max_features=0.75  warm_start=True  \n",
       "1527497  max_features=0.75  warm_start=True  \n",
       "1527498  max_features=0.75  warm_start=True  \n",
       "1527499  max_features=0.75  warm_start=True  \n",
       "1527500  max_features=0.75  warm_start=True  \n",
       "1527501  max_features=0.75  warm_start=True  \n",
       "1527502  max_features=0.75  warm_start=True  \n",
       "1527503  max_features=0.75  warm_start=True  \n",
       "1527504  max_features=0.75  warm_start=True  \n",
       "1527505  max_features=0.75  warm_start=True  \n",
       "1527506  max_features=0.75  warm_start=True  \n",
       "1527507  max_features=0.75  warm_start=True  \n",
       "1527508  max_features=0.75  warm_start=True  \n",
       "\n",
       "[1527509 rows x 6 columns]"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "method_param = pd.DataFrame(method_data.Parameters.str.split(',').tolist(),\n",
    "                                   columns = ['Param1','Param2','Param3'])\n",
    "method_param"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "method_data1 = method_data.drop('Parameters', 1)   #delete the Paameters column from the original dataframe\n",
    "idx = method_param.index.get_values()              #get the index of the parameter dataframe  \n",
    "#idx\n",
    "method_data2 = method_data1.set_index(idx)         #set the index of method dataframe same as parameter dataframe\n",
    "#kneighbor_data2\n",
    "result = pd.concat([method_data2, method_param], axis = 1)    #finally add the parameter columns to get the result (desired format)\n",
    "#result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Save this result in the HPCC_benchmark_results folder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import os\n",
    "if not os.path.isdir('HPCC_benchmark_results'):\n",
    "    os.mkdir('HPCC_benchmark_results')\n",
    "result.to_pickle('HPCC_benchmark_results/GradientBoostingClassifier-hpcc_results.tsv.gz')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Dataset_Name</th>\n",
       "      <th>Method_Name</th>\n",
       "      <th>Test_Score</th>\n",
       "      <th>Param1</th>\n",
       "      <th>Param2</th>\n",
       "      <th>Param3</th>\n",
       "      <th>Param4</th>\n",
       "      <th>Param5</th>\n",
       "      <th>Param6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.736842</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.815789</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.802632</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.815789</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.684211</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.763158</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.710526</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.776316</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.723684</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.736842</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.789474</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.789474</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.736842</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.736842</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.776316</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.763158</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.802632</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.815789</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.828947</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.736842</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.736842</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.789474</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.815789</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.697368</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.842105</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>heart-c</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.776316</td>\n",
       "      <td>loss=exponential</td>\n",
       "      <td>learning_rate=10.0</td>\n",
       "      <td>n_estimators=100</td>\n",
       "      <td>max_depth=3</td>\n",
       "      <td>max_features=sqrt</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=50.0</td>\n",
       "      <td>n_estimators=10</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=log2</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527479</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527480</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527481</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527482</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527483</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527484</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527485</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527486</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527487</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527488</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527489</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527490</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527491</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527492</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527493</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527494</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527495</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527496</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527497</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527498</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527499</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527500</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527501</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527502</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527503</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527504</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527505</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527506</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527507</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527508</th>\n",
       "      <td>shuttle-landing-control</td>\n",
       "      <td>GradientBoostingClassifier</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>loss=deviance</td>\n",
       "      <td>learning_rate=0.5</td>\n",
       "      <td>n_estimators=1000</td>\n",
       "      <td>max_depth=2</td>\n",
       "      <td>max_features=0.75</td>\n",
       "      <td>warm_start=True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1527509 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Dataset_Name                 Method_Name  Test_Score  \\\n",
       "0                        heart-c  GradientBoostingClassifier    0.736842   \n",
       "1                        heart-c  GradientBoostingClassifier    0.815789   \n",
       "2                        heart-c  GradientBoostingClassifier    0.802632   \n",
       "3                        heart-c  GradientBoostingClassifier    0.750000   \n",
       "4                        heart-c  GradientBoostingClassifier    0.815789   \n",
       "5                        heart-c  GradientBoostingClassifier    0.684211   \n",
       "6                        heart-c  GradientBoostingClassifier    0.763158   \n",
       "7                        heart-c  GradientBoostingClassifier    0.750000   \n",
       "8                        heart-c  GradientBoostingClassifier    0.710526   \n",
       "9                        heart-c  GradientBoostingClassifier    0.776316   \n",
       "10                       heart-c  GradientBoostingClassifier    0.723684   \n",
       "11                       heart-c  GradientBoostingClassifier    0.736842   \n",
       "12                       heart-c  GradientBoostingClassifier    0.789474   \n",
       "13                       heart-c  GradientBoostingClassifier    0.789474   \n",
       "14                       heart-c  GradientBoostingClassifier    0.736842   \n",
       "15                       heart-c  GradientBoostingClassifier    0.736842   \n",
       "16                       heart-c  GradientBoostingClassifier    0.776316   \n",
       "17                       heart-c  GradientBoostingClassifier    0.763158   \n",
       "18                       heart-c  GradientBoostingClassifier    0.802632   \n",
       "19                       heart-c  GradientBoostingClassifier    0.815789   \n",
       "20                       heart-c  GradientBoostingClassifier    0.828947   \n",
       "21                       heart-c  GradientBoostingClassifier    0.736842   \n",
       "22                       heart-c  GradientBoostingClassifier    0.736842   \n",
       "23                       heart-c  GradientBoostingClassifier    0.750000   \n",
       "24                       heart-c  GradientBoostingClassifier    0.789474   \n",
       "25                       heart-c  GradientBoostingClassifier    0.815789   \n",
       "26                       heart-c  GradientBoostingClassifier    0.697368   \n",
       "27                       heart-c  GradientBoostingClassifier    0.842105   \n",
       "28                       heart-c  GradientBoostingClassifier    0.776316   \n",
       "29       shuttle-landing-control  GradientBoostingClassifier    0.750000   \n",
       "...                          ...                         ...         ...   \n",
       "1527479  shuttle-landing-control  GradientBoostingClassifier    0.500000   \n",
       "1527480  shuttle-landing-control  GradientBoostingClassifier    0.750000   \n",
       "1527481  shuttle-landing-control  GradientBoostingClassifier    0.750000   \n",
       "1527482  shuttle-landing-control  GradientBoostingClassifier    0.500000   \n",
       "1527483  shuttle-landing-control  GradientBoostingClassifier    0.750000   \n",
       "1527484  shuttle-landing-control  GradientBoostingClassifier    0.750000   \n",
       "1527485  shuttle-landing-control  GradientBoostingClassifier    0.750000   \n",
       "1527486  shuttle-landing-control  GradientBoostingClassifier    0.250000   \n",
       "1527487  shuttle-landing-control  GradientBoostingClassifier    0.750000   \n",
       "1527488  shuttle-landing-control  GradientBoostingClassifier    0.750000   \n",
       "1527489  shuttle-landing-control  GradientBoostingClassifier    1.000000   \n",
       "1527490  shuttle-landing-control  GradientBoostingClassifier    0.500000   \n",
       "1527491  shuttle-landing-control  GradientBoostingClassifier    1.000000   \n",
       "1527492  shuttle-landing-control  GradientBoostingClassifier    0.750000   \n",
       "1527493  shuttle-landing-control  GradientBoostingClassifier    0.750000   \n",
       "1527494  shuttle-landing-control  GradientBoostingClassifier    0.750000   \n",
       "1527495  shuttle-landing-control  GradientBoostingClassifier    0.750000   \n",
       "1527496  shuttle-landing-control  GradientBoostingClassifier    0.750000   \n",
       "1527497  shuttle-landing-control  GradientBoostingClassifier    0.500000   \n",
       "1527498  shuttle-landing-control  GradientBoostingClassifier    0.500000   \n",
       "1527499  shuttle-landing-control  GradientBoostingClassifier    0.500000   \n",
       "1527500  shuttle-landing-control  GradientBoostingClassifier    0.500000   \n",
       "1527501  shuttle-landing-control  GradientBoostingClassifier    0.750000   \n",
       "1527502  shuttle-landing-control  GradientBoostingClassifier    0.750000   \n",
       "1527503  shuttle-landing-control  GradientBoostingClassifier    1.000000   \n",
       "1527504  shuttle-landing-control  GradientBoostingClassifier    0.500000   \n",
       "1527505  shuttle-landing-control  GradientBoostingClassifier    0.500000   \n",
       "1527506  shuttle-landing-control  GradientBoostingClassifier    0.500000   \n",
       "1527507  shuttle-landing-control  GradientBoostingClassifier    0.250000   \n",
       "1527508  shuttle-landing-control  GradientBoostingClassifier    0.500000   \n",
       "\n",
       "                   Param1              Param2             Param3       Param4  \\\n",
       "0        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "1        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "2        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "3        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "4        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "5        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "6        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "7        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "8        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "9        loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "10       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "11       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "12       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "13       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "14       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "15       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "16       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "17       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "18       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "19       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "20       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "21       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "22       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "23       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "24       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "25       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "26       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "27       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "28       loss=exponential  learning_rate=10.0   n_estimators=100  max_depth=3   \n",
       "29          loss=deviance  learning_rate=50.0    n_estimators=10  max_depth=2   \n",
       "...                   ...                 ...                ...          ...   \n",
       "1527479     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527480     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527481     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527482     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527483     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527484     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527485     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527486     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527487     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527488     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527489     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527490     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527491     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527492     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527493     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527494     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527495     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527496     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527497     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527498     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527499     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527500     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527501     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527502     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527503     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527504     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527505     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527506     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527507     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "1527508     loss=deviance   learning_rate=0.5  n_estimators=1000  max_depth=2   \n",
       "\n",
       "                    Param5           Param6  \n",
       "0        max_features=sqrt  warm_start=True  \n",
       "1        max_features=sqrt  warm_start=True  \n",
       "2        max_features=sqrt  warm_start=True  \n",
       "3        max_features=sqrt  warm_start=True  \n",
       "4        max_features=sqrt  warm_start=True  \n",
       "5        max_features=sqrt  warm_start=True  \n",
       "6        max_features=sqrt  warm_start=True  \n",
       "7        max_features=sqrt  warm_start=True  \n",
       "8        max_features=sqrt  warm_start=True  \n",
       "9        max_features=sqrt  warm_start=True  \n",
       "10       max_features=sqrt  warm_start=True  \n",
       "11       max_features=sqrt  warm_start=True  \n",
       "12       max_features=sqrt  warm_start=True  \n",
       "13       max_features=sqrt  warm_start=True  \n",
       "14       max_features=sqrt  warm_start=True  \n",
       "15       max_features=sqrt  warm_start=True  \n",
       "16       max_features=sqrt  warm_start=True  \n",
       "17       max_features=sqrt  warm_start=True  \n",
       "18       max_features=sqrt  warm_start=True  \n",
       "19       max_features=sqrt  warm_start=True  \n",
       "20       max_features=sqrt  warm_start=True  \n",
       "21       max_features=sqrt  warm_start=True  \n",
       "22       max_features=sqrt  warm_start=True  \n",
       "23       max_features=sqrt  warm_start=True  \n",
       "24       max_features=sqrt  warm_start=True  \n",
       "25       max_features=sqrt  warm_start=True  \n",
       "26       max_features=sqrt  warm_start=True  \n",
       "27       max_features=sqrt  warm_start=True  \n",
       "28       max_features=sqrt  warm_start=True  \n",
       "29       max_features=log2  warm_start=True  \n",
       "...                    ...              ...  \n",
       "1527479  max_features=0.75  warm_start=True  \n",
       "1527480  max_features=0.75  warm_start=True  \n",
       "1527481  max_features=0.75  warm_start=True  \n",
       "1527482  max_features=0.75  warm_start=True  \n",
       "1527483  max_features=0.75  warm_start=True  \n",
       "1527484  max_features=0.75  warm_start=True  \n",
       "1527485  max_features=0.75  warm_start=True  \n",
       "1527486  max_features=0.75  warm_start=True  \n",
       "1527487  max_features=0.75  warm_start=True  \n",
       "1527488  max_features=0.75  warm_start=True  \n",
       "1527489  max_features=0.75  warm_start=True  \n",
       "1527490  max_features=0.75  warm_start=True  \n",
       "1527491  max_features=0.75  warm_start=True  \n",
       "1527492  max_features=0.75  warm_start=True  \n",
       "1527493  max_features=0.75  warm_start=True  \n",
       "1527494  max_features=0.75  warm_start=True  \n",
       "1527495  max_features=0.75  warm_start=True  \n",
       "1527496  max_features=0.75  warm_start=True  \n",
       "1527497  max_features=0.75  warm_start=True  \n",
       "1527498  max_features=0.75  warm_start=True  \n",
       "1527499  max_features=0.75  warm_start=True  \n",
       "1527500  max_features=0.75  warm_start=True  \n",
       "1527501  max_features=0.75  warm_start=True  \n",
       "1527502  max_features=0.75  warm_start=True  \n",
       "1527503  max_features=0.75  warm_start=True  \n",
       "1527504  max_features=0.75  warm_start=True  \n",
       "1527505  max_features=0.75  warm_start=True  \n",
       "1527506  max_features=0.75  warm_start=True  \n",
       "1527507  max_features=0.75  warm_start=True  \n",
       "1527508  max_features=0.75  warm_start=True  \n",
       "\n",
       "[1527509 rows x 9 columns]"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_pickle('HPCC_benchmark_results/GradientBoostingClassifier-hpcc_results.tsv.gz')\n",
    "data"
   ]
  }
 ],
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