numer_minmax.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "\n",
    "os.chdir(\"/Users/PraveenGupta/Downloads/Kaggle/numerai_datasets/\")\n",
    "\n",
    "train=pd.read_csv(\"numerai_training_data.csv\")\n",
    "test=pd.read_csv(\"numerai_tournament_data.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.preprocessing import Normalizer, PolynomialFeatures\n",
    "from sklearn.preprocessing import MaxAbsScaler, MinMaxScaler, StandardScaler, RobustScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "feature_names = train.columns.values\n",
    "train_id_target = train[['t_id','target']]\n",
    "train = train.drop( 'target', axis = 1 )\n",
    "train = train.drop( 't_id', axis = 1 )\n",
    "test_target=test[['t_id']]\n",
    "test = test.drop( 't_id', axis = 1 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['feature1' 'feature2' 'feature3' 'feature4' 'feature5' 'feature6'\n",
      " 'feature7' 'feature8' 'feature9' 'feature10' 'feature11' 'feature12'\n",
      " 'feature13' 'feature14' 'feature15' 'feature16' 'feature17' 'feature18'\n",
      " 'feature19' 'feature20' 'feature21']\n"
     ]
    }
   ],
   "source": [
    "print train.columns.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "transformers = [MaxAbsScaler(), MinMaxScaler(), RobustScaler(), StandardScaler(),Normalizer( norm = 'l1' ), Normalizer( norm = 'l2' ), Normalizer( norm = 'max' )] \n",
    "transformationNames=['MaxAbsScaler','MinMaxScaler','RobustScaler','StandardScaler','Normalizer_L1','Normalizer_L2','Normalizer_max']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def transform_train_and_evaluate(transformer):\n",
    "    train_new = transformer.fit_transform(train)#,train_id_target['target'].values)        #do we need to pass the target here??\n",
    "    test_new = transformer.transform(test)\n",
    "    train_new = pd.DataFrame(train_new,columns=train.columns.values)\n",
    "    train_new = pd.concat([train_new,train_id_target],axis=1)\n",
    "    test_new = pd.DataFrame(test_new,columns=test.columns.values)\n",
    "    test_new = pd.concat([test_new,test_target],axis=1)\n",
    "    return train_new,test_new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "created new table : MaxAbsScaler(copy=True) \n",
      "created new table : MinMaxScaler(copy=True, feature_range=(0, 1)) \n",
      "created new table : RobustScaler(copy=True, with_centering=True, with_scaling=True) \n",
      "created new table : StandardScaler(copy=True, with_mean=True, with_std=True) \n",
      "created new table : Normalizer(copy=True, norm='l1') \n",
      "created new table : Normalizer(copy=True, norm='l2') \n",
      "created new table : Normalizer(copy=True, norm='max') \n"
     ]
    }
   ],
   "source": [
    "i=0\n",
    "for transformer in transformers:\n",
    "    train_transformed,test_transformed = transform_train_and_evaluate(transformer)\n",
    "    train_transformed.to_csv(transformationNames[i]+\"_train.csv\",index=False)\n",
    "    test_transformed.to_csv(transformationNames[i]+\"_test.csv\",index=False)\n",
    "    print \"created new table : %s \"%((str(transformer)))\n",
    "    i=i+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RobustScaler\n"
     ]
    }
   ],
   "source": [
    "print str(transformer)[:(str(transformer)).index('(')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>feature1</th>\n",
       "      <th>feature2</th>\n",
       "      <th>feature3</th>\n",
       "      <th>feature4</th>\n",
       "      <th>feature5</th>\n",
       "      <th>feature6</th>\n",
       "      <th>feature7</th>\n",
       "      <th>feature8</th>\n",
       "      <th>feature9</th>\n",
       "      <th>feature10</th>\n",
       "      <th>...</th>\n",
       "      <th>feature12</th>\n",
       "      <th>feature13</th>\n",
       "      <th>feature14</th>\n",
       "      <th>feature15</th>\n",
       "      <th>feature16</th>\n",
       "      <th>feature17</th>\n",
       "      <th>feature18</th>\n",
       "      <th>feature19</th>\n",
       "      <th>feature20</th>\n",
       "      <th>feature21</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>-0.313588</td>\n",
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       "      <td>-0.009009</td>\n",
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       "      <td>0.124437</td>\n",
       "      <td>0.713260</td>\n",
       "      <td>-0.538150</td>\n",
       "      <td>0.345616</td>\n",
       "      <td>0.273537</td>\n",
       "      <td>-0.314769</td>\n",
       "      <td>-0.023340</td>\n",
       "      <td>-0.153320</td>\n",
       "      <td>-0.468282</td>\n",
       "      <td>0.587186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.707763</td>\n",
       "      <td>-0.123937</td>\n",
       "      <td>-0.145961</td>\n",
       "      <td>-0.658291</td>\n",
       "      <td>0.028878</td>\n",
       "      <td>-0.426332</td>\n",
       "      <td>-0.833165</td>\n",
       "      <td>0.792465</td>\n",
       "      <td>-0.578033</td>\n",
       "      <td>0.323109</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.961097</td>\n",
       "      <td>0.129457</td>\n",
       "      <td>-0.507930</td>\n",
       "      <td>0.134582</td>\n",
       "      <td>0.411894</td>\n",
       "      <td>0.190980</td>\n",
       "      <td>-0.108574</td>\n",
       "      <td>0.924086</td>\n",
       "      <td>0.454979</td>\n",
       "      <td>0.057260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.790490</td>\n",
       "      <td>0.185716</td>\n",
       "      <td>0.402282</td>\n",
       "      <td>0.763339</td>\n",
       "      <td>0.095122</td>\n",
       "      <td>0.455018</td>\n",
       "      <td>1.011367</td>\n",
       "      <td>-0.987597</td>\n",
       "      <td>0.844772</td>\n",
       "      <td>0.793506</td>\n",
       "      <td>...</td>\n",
       "      <td>0.648685</td>\n",
       "      <td>0.669430</td>\n",
       "      <td>0.784298</td>\n",
       "      <td>0.555093</td>\n",
       "      <td>0.320575</td>\n",
       "      <td>-0.574788</td>\n",
       "      <td>0.678669</td>\n",
       "      <td>-0.894796</td>\n",
       "      <td>-0.612232</td>\n",
       "      <td>0.268919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.643927</td>\n",
       "      <td>-0.433827</td>\n",
       "      <td>-0.540434</td>\n",
       "      <td>0.517380</td>\n",
       "      <td>-0.703354</td>\n",
       "      <td>0.587514</td>\n",
       "      <td>-0.642726</td>\n",
       "      <td>0.683993</td>\n",
       "      <td>-0.561626</td>\n",
       "      <td>-0.984398</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.523931</td>\n",
       "      <td>-0.799125</td>\n",
       "      <td>0.634258</td>\n",
       "      <td>-0.376950</td>\n",
       "      <td>-0.683689</td>\n",
       "      <td>-0.950395</td>\n",
       "      <td>-0.620420</td>\n",
       "      <td>0.695255</td>\n",
       "      <td>-0.981099</td>\n",
       "      <td>-0.942930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.889952</td>\n",
       "      <td>-0.909470</td>\n",
       "      <td>-0.141117</td>\n",
       "      <td>-0.637855</td>\n",
       "      <td>-0.759768</td>\n",
       "      <td>-0.829930</td>\n",
       "      <td>-0.818578</td>\n",
       "      <td>-0.313376</td>\n",
       "      <td>-0.223361</td>\n",
       "      <td>-0.664655</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.943311</td>\n",
       "      <td>-0.838855</td>\n",
       "      <td>-0.881833</td>\n",
       "      <td>0.665032</td>\n",
       "      <td>0.460546</td>\n",
       "      <td>0.706635</td>\n",
       "      <td>-0.771568</td>\n",
       "      <td>-0.982725</td>\n",
       "      <td>0.582607</td>\n",
       "      <td>-0.730411</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   feature1  feature2  feature3  feature4  feature5  feature6  feature7  \\\n",
       "0 -0.437448  0.424928  0.431940 -0.559140 -0.313588 -0.416496 -0.039559   \n",
       "1  0.707763 -0.123937 -0.145961 -0.658291  0.028878 -0.426332 -0.833165   \n",
       "2 -0.790490  0.185716  0.402282  0.763339  0.095122  0.455018  1.011367   \n",
       "3  0.643927 -0.433827 -0.540434  0.517380 -0.703354  0.587514 -0.642726   \n",
       "4 -0.889952 -0.909470 -0.141117 -0.637855 -0.759768 -0.829930 -0.818578   \n",
       "\n",
       "   feature8  feature9  feature10    ...      feature12  feature13  feature14  \\\n",
       "0 -0.131025  0.094763  -0.009009    ...       0.124437   0.713260  -0.538150   \n",
       "1  0.792465 -0.578033   0.323109    ...      -0.961097   0.129457  -0.507930   \n",
       "2 -0.987597  0.844772   0.793506    ...       0.648685   0.669430   0.784298   \n",
       "3  0.683993 -0.561626  -0.984398    ...      -0.523931  -0.799125   0.634258   \n",
       "4 -0.313376 -0.223361  -0.664655    ...      -0.943311  -0.838855  -0.881833   \n",
       "\n",
       "   feature15  feature16  feature17  feature18  feature19  feature20  feature21  \n",
       "0   0.345616   0.273537  -0.314769  -0.023340  -0.153320  -0.468282   0.587186  \n",
       "1   0.134582   0.411894   0.190980  -0.108574   0.924086   0.454979   0.057260  \n",
       "2   0.555093   0.320575  -0.574788   0.678669  -0.894796  -0.612232   0.268919  \n",
       "3  -0.376950  -0.683689  -0.950395  -0.620420   0.695255  -0.981099  -0.942930  \n",
       "4   0.665032   0.460546   0.706635  -0.771568  -0.982725   0.582607  -0.730411  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_transformed.head() #just transform not fit_transform"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "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>feature1</th>\n",
       "      <th>feature2</th>\n",
       "      <th>feature3</th>\n",
       "      <th>feature4</th>\n",
       "      <th>feature5</th>\n",
       "      <th>feature6</th>\n",
       "      <th>feature7</th>\n",
       "      <th>feature8</th>\n",
       "      <th>feature9</th>\n",
       "      <th>feature10</th>\n",
       "      <th>...</th>\n",
       "      <th>feature12</th>\n",
       "      <th>feature13</th>\n",
       "      <th>feature14</th>\n",
       "      <th>feature15</th>\n",
       "      <th>feature16</th>\n",
       "      <th>feature17</th>\n",
       "      <th>feature18</th>\n",
       "      <th>feature19</th>\n",
       "      <th>feature20</th>\n",
       "      <th>feature21</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.437448</td>\n",
       "      <td>0.424928</td>\n",
       "      <td>0.431940</td>\n",
       "      <td>-0.559140</td>\n",
       "      <td>-0.313588</td>\n",
       "      <td>-0.416496</td>\n",
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       "      <td>-0.131025</td>\n",
       "      <td>0.094763</td>\n",
       "      <td>-0.009009</td>\n",
       "      <td>...</td>\n",
       "      <td>0.124437</td>\n",
       "      <td>0.713260</td>\n",
       "      <td>-0.538150</td>\n",
       "      <td>0.345616</td>\n",
       "      <td>0.273537</td>\n",
       "      <td>-0.314769</td>\n",
       "      <td>-0.023340</td>\n",
       "      <td>-0.153320</td>\n",
       "      <td>-0.468282</td>\n",
       "      <td>0.587186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.707763</td>\n",
       "      <td>-0.123937</td>\n",
       "      <td>-0.145961</td>\n",
       "      <td>-0.658291</td>\n",
       "      <td>0.028878</td>\n",
       "      <td>-0.426332</td>\n",
       "      <td>-0.833165</td>\n",
       "      <td>0.792465</td>\n",
       "      <td>-0.578033</td>\n",
       "      <td>0.323109</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.961097</td>\n",
       "      <td>0.129457</td>\n",
       "      <td>-0.507930</td>\n",
       "      <td>0.134582</td>\n",
       "      <td>0.411894</td>\n",
       "      <td>0.190980</td>\n",
       "      <td>-0.108574</td>\n",
       "      <td>0.924086</td>\n",
       "      <td>0.454979</td>\n",
       "      <td>0.057260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.790490</td>\n",
       "      <td>0.185716</td>\n",
       "      <td>0.402282</td>\n",
       "      <td>0.763339</td>\n",
       "      <td>0.095122</td>\n",
       "      <td>0.455018</td>\n",
       "      <td>1.011367</td>\n",
       "      <td>-0.987597</td>\n",
       "      <td>0.844772</td>\n",
       "      <td>0.793506</td>\n",
       "      <td>...</td>\n",
       "      <td>0.648685</td>\n",
       "      <td>0.669430</td>\n",
       "      <td>0.784298</td>\n",
       "      <td>0.555093</td>\n",
       "      <td>0.320575</td>\n",
       "      <td>-0.574788</td>\n",
       "      <td>0.678669</td>\n",
       "      <td>-0.894796</td>\n",
       "      <td>-0.612232</td>\n",
       "      <td>0.268919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.643927</td>\n",
       "      <td>-0.433827</td>\n",
       "      <td>-0.540434</td>\n",
       "      <td>0.517380</td>\n",
       "      <td>-0.703354</td>\n",
       "      <td>0.587514</td>\n",
       "      <td>-0.642726</td>\n",
       "      <td>0.683993</td>\n",
       "      <td>-0.561626</td>\n",
       "      <td>-0.984398</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.523931</td>\n",
       "      <td>-0.799125</td>\n",
       "      <td>0.634258</td>\n",
       "      <td>-0.376950</td>\n",
       "      <td>-0.683689</td>\n",
       "      <td>-0.950395</td>\n",
       "      <td>-0.620420</td>\n",
       "      <td>0.695255</td>\n",
       "      <td>-0.981099</td>\n",
       "      <td>-0.942930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.889952</td>\n",
       "      <td>-0.909470</td>\n",
       "      <td>-0.141117</td>\n",
       "      <td>-0.637855</td>\n",
       "      <td>-0.759768</td>\n",
       "      <td>-0.829930</td>\n",
       "      <td>-0.818578</td>\n",
       "      <td>-0.313376</td>\n",
       "      <td>-0.223361</td>\n",
       "      <td>-0.664655</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.943311</td>\n",
       "      <td>-0.838855</td>\n",
       "      <td>-0.881833</td>\n",
       "      <td>0.665032</td>\n",
       "      <td>0.460546</td>\n",
       "      <td>0.706635</td>\n",
       "      <td>-0.771568</td>\n",
       "      <td>-0.982725</td>\n",
       "      <td>0.582607</td>\n",
       "      <td>-0.730411</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   feature1  feature2  feature3  feature4  feature5  feature6  feature7  \\\n",
       "0 -0.437448  0.424928  0.431940 -0.559140 -0.313588 -0.416496 -0.039559   \n",
       "1  0.707763 -0.123937 -0.145961 -0.658291  0.028878 -0.426332 -0.833165   \n",
       "2 -0.790490  0.185716  0.402282  0.763339  0.095122  0.455018  1.011367   \n",
       "3  0.643927 -0.433827 -0.540434  0.517380 -0.703354  0.587514 -0.642726   \n",
       "4 -0.889952 -0.909470 -0.141117 -0.637855 -0.759768 -0.829930 -0.818578   \n",
       "\n",
       "   feature8  feature9  feature10    ...      feature12  feature13  feature14  \\\n",
       "0 -0.131025  0.094763  -0.009009    ...       0.124437   0.713260  -0.538150   \n",
       "1  0.792465 -0.578033   0.323109    ...      -0.961097   0.129457  -0.507930   \n",
       "2 -0.987597  0.844772   0.793506    ...       0.648685   0.669430   0.784298   \n",
       "3  0.683993 -0.561626  -0.984398    ...      -0.523931  -0.799125   0.634258   \n",
       "4 -0.313376 -0.223361  -0.664655    ...      -0.943311  -0.838855  -0.881833   \n",
       "\n",
       "   feature15  feature16  feature17  feature18  feature19  feature20  feature21  \n",
       "0   0.345616   0.273537  -0.314769  -0.023340  -0.153320  -0.468282   0.587186  \n",
       "1   0.134582   0.411894   0.190980  -0.108574   0.924086   0.454979   0.057260  \n",
       "2   0.555093   0.320575  -0.574788   0.678669  -0.894796  -0.612232   0.268919  \n",
       "3  -0.376950  -0.683689  -0.950395  -0.620420   0.695255  -0.981099  -0.942930  \n",
       "4   0.665032   0.460546   0.706635  -0.771568  -0.982725   0.582607  -0.730411  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_transformed.head() #target not passed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
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       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>feature1</th>\n",
       "      <th>feature2</th>\n",
       "      <th>feature3</th>\n",
       "      <th>feature4</th>\n",
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       "      <th>feature21</th>\n",
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       "      <td>-0.023340</td>\n",
       "      <td>-0.153320</td>\n",
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       "      <td>0.028878</td>\n",
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       "      <td>0.792465</td>\n",
       "      <td>-0.578033</td>\n",
       "      <td>0.323109</td>\n",
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       "      <td>-0.961097</td>\n",
       "      <td>0.129457</td>\n",
       "      <td>-0.507930</td>\n",
       "      <td>0.134582</td>\n",
       "      <td>0.411894</td>\n",
       "      <td>0.190980</td>\n",
       "      <td>-0.108574</td>\n",
       "      <td>0.924086</td>\n",
       "      <td>0.454979</td>\n",
       "      <td>0.057260</td>\n",
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       "      <td>0.185716</td>\n",
       "      <td>0.402282</td>\n",
       "      <td>0.763339</td>\n",
       "      <td>0.095122</td>\n",
       "      <td>0.455018</td>\n",
       "      <td>1.011367</td>\n",
       "      <td>-0.987597</td>\n",
       "      <td>0.844772</td>\n",
       "      <td>0.793506</td>\n",
       "      <td>...</td>\n",
       "      <td>0.648685</td>\n",
       "      <td>0.669430</td>\n",
       "      <td>0.784298</td>\n",
       "      <td>0.555093</td>\n",
       "      <td>0.320575</td>\n",
       "      <td>-0.574788</td>\n",
       "      <td>0.678669</td>\n",
       "      <td>-0.894796</td>\n",
       "      <td>-0.612232</td>\n",
       "      <td>0.268919</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.643927</td>\n",
       "      <td>-0.433827</td>\n",
       "      <td>-0.540434</td>\n",
       "      <td>0.517380</td>\n",
       "      <td>-0.703354</td>\n",
       "      <td>0.587514</td>\n",
       "      <td>-0.642726</td>\n",
       "      <td>0.683993</td>\n",
       "      <td>-0.561626</td>\n",
       "      <td>-0.984398</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.523931</td>\n",
       "      <td>-0.799125</td>\n",
       "      <td>0.634258</td>\n",
       "      <td>-0.376950</td>\n",
       "      <td>-0.683689</td>\n",
       "      <td>-0.950395</td>\n",
       "      <td>-0.620420</td>\n",
       "      <td>0.695255</td>\n",
       "      <td>-0.981099</td>\n",
       "      <td>-0.942930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.889952</td>\n",
       "      <td>-0.909470</td>\n",
       "      <td>-0.141117</td>\n",
       "      <td>-0.637855</td>\n",
       "      <td>-0.759768</td>\n",
       "      <td>-0.829930</td>\n",
       "      <td>-0.818578</td>\n",
       "      <td>-0.313376</td>\n",
       "      <td>-0.223361</td>\n",
       "      <td>-0.664655</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.943311</td>\n",
       "      <td>-0.838855</td>\n",
       "      <td>-0.881833</td>\n",
       "      <td>0.665032</td>\n",
       "      <td>0.460546</td>\n",
       "      <td>0.706635</td>\n",
       "      <td>-0.771568</td>\n",
       "      <td>-0.982725</td>\n",
       "      <td>0.582607</td>\n",
       "      <td>-0.730411</td>\n",
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       "   feature1  feature2  feature3  feature4  feature5  feature6  feature7  \\\n",
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       "1  0.707763 -0.123937 -0.145961 -0.658291  0.028878 -0.426332 -0.833165   \n",
       "2 -0.790490  0.185716  0.402282  0.763339  0.095122  0.455018  1.011367   \n",
       "3  0.643927 -0.433827 -0.540434  0.517380 -0.703354  0.587514 -0.642726   \n",
       "4 -0.889952 -0.909470 -0.141117 -0.637855 -0.759768 -0.829930 -0.818578   \n",
       "\n",
       "   feature8  feature9  feature10    ...      feature12  feature13  feature14  \\\n",
       "0 -0.131025  0.094763  -0.009009    ...       0.124437   0.713260  -0.538150   \n",
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       "2 -0.987597  0.844772   0.793506    ...       0.648685   0.669430   0.784298   \n",
       "3  0.683993 -0.561626  -0.984398    ...      -0.523931  -0.799125   0.634258   \n",
       "4 -0.313376 -0.223361  -0.664655    ...      -0.943311  -0.838855  -0.881833   \n",
       "\n",
       "   feature15  feature16  feature17  feature18  feature19  feature20  feature21  \n",
       "0   0.345616   0.273537  -0.314769  -0.023340  -0.153320  -0.468282   0.587186  \n",
       "1   0.134582   0.411894   0.190980  -0.108574   0.924086   0.454979   0.057260  \n",
       "2   0.555093   0.320575  -0.574788   0.678669  -0.894796  -0.612232   0.268919  \n",
       "3  -0.376950  -0.683689  -0.950395  -0.620420   0.695255  -0.981099  -0.942930  \n",
       "4   0.665032   0.460546   0.706635  -0.771568  -0.982725   0.582607  -0.730411  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_transformed.head()  #target passed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
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       "      <td>0.558338</td>\n",
       "      <td>-0.930034</td>\n",
       "      <td>1.065204</td>\n",
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       "      <td>-0.092229</td>\n",
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       "      <td>-0.334029</td>\n",
       "      <td>-0.863134</td>\n",
       "      <td>-0.164593</td>\n",
       "      <td>-0.183371</td>\n",
       "      <td>-0.753266</td>\n",
       "      <td>0.776527</td>\n",
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       "      <td>-0.826133</td>\n",
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       "      <td>-0.658266</td>\n",
       "      <td>0.213008</td>\n",
       "      <td>0.745555</td>\n",
       "      <td>-0.555402</td>\n",
       "      <td>-0.653610</td>\n",
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       "      <td>0.380201</td>\n",
       "      <td>0.862863</td>\n",
       "      <td>-0.457820</td>\n",
       "      <td>0.484740</td>\n",
       "      <td>0.415902</td>\n",
       "      <td>-0.033177</td>\n",
       "      <td>-0.205611</td>\n",
       "      <td>0.920227</td>\n",
       "      <td>-0.242081</td>\n",
       "      <td>-0.517036</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>0.859962</td>\n",
       "      <td>0.084500</td>\n",
       "      <td>0.008265</td>\n",
       "      <td>-0.702632</td>\n",
       "      <td>0.726231</td>\n",
       "      <td>1.017840</td>\n",
       "      <td>-0.191737</td>\n",
       "      <td>0.617950</td>\n",
       "      <td>0.155431</td>\n",
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       "      <td>0.747996</td>\n",
       "      <td>-0.240813</td>\n",
       "      <td>-0.106466</td>\n",
       "      <td>0.343986</td>\n",
       "      <td>0.463507</td>\n",
       "      <td>-0.400993</td>\n",
       "      <td>0.954065</td>\n",
       "      <td>-0.375376</td>\n",
       "      <td>-0.509994</td>\n",
       "      <td>0.808041</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.735365</td>\n",
       "      <td>-0.787809</td>\n",
       "      <td>-0.956968</td>\n",
       "      <td>-0.525693</td>\n",
       "      <td>0.808868</td>\n",
       "      <td>-0.861279</td>\n",
       "      <td>-0.960535</td>\n",
       "      <td>-0.732010</td>\n",
       "      <td>-0.728140</td>\n",
       "      <td>-0.750012</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.746713</td>\n",
       "      <td>0.897352</td>\n",
       "      <td>-0.780987</td>\n",
       "      <td>0.497260</td>\n",
       "      <td>0.560954</td>\n",
       "      <td>0.953875</td>\n",
       "      <td>-0.908331</td>\n",
       "      <td>-0.943664</td>\n",
       "      <td>0.966438</td>\n",
       "      <td>-0.390171</td>\n",
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       "   feature1  feature2  feature3  feature4  feature5  feature6  feature7  \\\n",
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       "1  0.987852  0.453582  0.099631  0.822369 -0.692876  0.869254  0.460108   \n",
       "2  0.671580 -0.211836 -0.483510 -0.826133 -0.020293 -0.658266  0.213008   \n",
       "3 -0.480311  0.859962  0.084500  0.008265 -0.702632  0.726231  1.017840   \n",
       "4 -0.735365 -0.787809 -0.956968 -0.525693  0.808868 -0.861279 -0.960535   \n",
       "\n",
       "   feature8  feature9  feature10    ...      feature12  feature13  feature14  \\\n",
       "0  0.864497 -0.177956  -0.129382    ...       0.783131   0.798268   0.312633   \n",
       "1  0.558338 -0.930034   1.065204    ...       0.517756  -0.092229   0.646790   \n",
       "2  0.745555 -0.555402  -0.653610    ...       0.380201   0.862863  -0.457820   \n",
       "3 -0.191737  0.617950   0.155431    ...       0.747996  -0.240813  -0.106466   \n",
       "4 -0.732010 -0.728140  -0.750012    ...      -0.746713   0.897352  -0.780987   \n",
       "\n",
       "   feature15  feature16  feature17  feature18  feature19  feature20  feature21  \n",
       "0   0.910168   0.777358   0.794960  -0.324877  -0.770816   0.883357  -0.958388  \n",
       "1  -0.620009  -0.334029  -0.863134  -0.164593  -0.183371  -0.753266   0.776527  \n",
       "2   0.484740   0.415902  -0.033177  -0.205611   0.920227  -0.242081  -0.517036  \n",
       "3   0.343986   0.463507  -0.400993   0.954065  -0.375376  -0.509994   0.808041  \n",
       "4   0.497260   0.560954   0.953875  -0.908331  -0.943664   0.966438  -0.390171  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_transformed.head() #target not passed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>feature1</th>\n",
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       "      <td>-0.313388</td>\n",
       "      <td>0.229522</td>\n",
       "      <td>0.804742</td>\n",
       "      <td>0.726514</td>\n",
       "      <td>-0.049781</td>\n",
       "      <td>0.864497</td>\n",
       "      <td>-0.177956</td>\n",
       "      <td>-0.129382</td>\n",
       "      <td>...</td>\n",
       "      <td>0.783131</td>\n",
       "      <td>0.798268</td>\n",
       "      <td>0.312633</td>\n",
       "      <td>0.910168</td>\n",
       "      <td>0.777358</td>\n",
       "      <td>0.794960</td>\n",
       "      <td>-0.324877</td>\n",
       "      <td>-0.770816</td>\n",
       "      <td>0.883357</td>\n",
       "      <td>-0.958388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.987852</td>\n",
       "      <td>0.453582</td>\n",
       "      <td>0.099631</td>\n",
       "      <td>0.822369</td>\n",
       "      <td>-0.692876</td>\n",
       "      <td>0.869254</td>\n",
       "      <td>0.460108</td>\n",
       "      <td>0.558338</td>\n",
       "      <td>-0.930034</td>\n",
       "      <td>1.065204</td>\n",
       "      <td>...</td>\n",
       "      <td>0.517756</td>\n",
       "      <td>-0.092229</td>\n",
       "      <td>0.646790</td>\n",
       "      <td>-0.620009</td>\n",
       "      <td>-0.334029</td>\n",
       "      <td>-0.863134</td>\n",
       "      <td>-0.164593</td>\n",
       "      <td>-0.183371</td>\n",
       "      <td>-0.753266</td>\n",
       "      <td>0.776527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.671580</td>\n",
       "      <td>-0.211836</td>\n",
       "      <td>-0.483510</td>\n",
       "      <td>-0.826133</td>\n",
       "      <td>-0.020293</td>\n",
       "      <td>-0.658266</td>\n",
       "      <td>0.213008</td>\n",
       "      <td>0.745555</td>\n",
       "      <td>-0.555402</td>\n",
       "      <td>-0.653610</td>\n",
       "      <td>...</td>\n",
       "      <td>0.380201</td>\n",
       "      <td>0.862863</td>\n",
       "      <td>-0.457820</td>\n",
       "      <td>0.484740</td>\n",
       "      <td>0.415902</td>\n",
       "      <td>-0.033177</td>\n",
       "      <td>-0.205611</td>\n",
       "      <td>0.920227</td>\n",
       "      <td>-0.242081</td>\n",
       "      <td>-0.517036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.480311</td>\n",
       "      <td>0.859962</td>\n",
       "      <td>0.084500</td>\n",
       "      <td>0.008265</td>\n",
       "      <td>-0.702632</td>\n",
       "      <td>0.726231</td>\n",
       "      <td>1.017840</td>\n",
       "      <td>-0.191737</td>\n",
       "      <td>0.617950</td>\n",
       "      <td>0.155431</td>\n",
       "      <td>...</td>\n",
       "      <td>0.747996</td>\n",
       "      <td>-0.240813</td>\n",
       "      <td>-0.106466</td>\n",
       "      <td>0.343986</td>\n",
       "      <td>0.463507</td>\n",
       "      <td>-0.400993</td>\n",
       "      <td>0.954065</td>\n",
       "      <td>-0.375376</td>\n",
       "      <td>-0.509994</td>\n",
       "      <td>0.808041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.735365</td>\n",
       "      <td>-0.787809</td>\n",
       "      <td>-0.956968</td>\n",
       "      <td>-0.525693</td>\n",
       "      <td>0.808868</td>\n",
       "      <td>-0.861279</td>\n",
       "      <td>-0.960535</td>\n",
       "      <td>-0.732010</td>\n",
       "      <td>-0.728140</td>\n",
       "      <td>-0.750012</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.746713</td>\n",
       "      <td>0.897352</td>\n",
       "      <td>-0.780987</td>\n",
       "      <td>0.497260</td>\n",
       "      <td>0.560954</td>\n",
       "      <td>0.953875</td>\n",
       "      <td>-0.908331</td>\n",
       "      <td>-0.943664</td>\n",
       "      <td>0.966438</td>\n",
       "      <td>-0.390171</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   feature1  feature2  feature3  feature4  feature5  feature6  feature7  \\\n",
       "0  0.758500  0.980365 -0.313388  0.229522  0.804742  0.726514 -0.049781   \n",
       "1  0.987852  0.453582  0.099631  0.822369 -0.692876  0.869254  0.460108   \n",
       "2  0.671580 -0.211836 -0.483510 -0.826133 -0.020293 -0.658266  0.213008   \n",
       "3 -0.480311  0.859962  0.084500  0.008265 -0.702632  0.726231  1.017840   \n",
       "4 -0.735365 -0.787809 -0.956968 -0.525693  0.808868 -0.861279 -0.960535   \n",
       "\n",
       "   feature8  feature9  feature10    ...      feature12  feature13  feature14  \\\n",
       "0  0.864497 -0.177956  -0.129382    ...       0.783131   0.798268   0.312633   \n",
       "1  0.558338 -0.930034   1.065204    ...       0.517756  -0.092229   0.646790   \n",
       "2  0.745555 -0.555402  -0.653610    ...       0.380201   0.862863  -0.457820   \n",
       "3 -0.191737  0.617950   0.155431    ...       0.747996  -0.240813  -0.106466   \n",
       "4 -0.732010 -0.728140  -0.750012    ...      -0.746713   0.897352  -0.780987   \n",
       "\n",
       "   feature15  feature16  feature17  feature18  feature19  feature20  feature21  \n",
       "0   0.910168   0.777358   0.794960  -0.324877  -0.770816   0.883357  -0.958388  \n",
       "1  -0.620009  -0.334029  -0.863134  -0.164593  -0.183371  -0.753266   0.776527  \n",
       "2   0.484740   0.415902  -0.033177  -0.205611   0.920227  -0.242081  -0.517036  \n",
       "3   0.343986   0.463507  -0.400993   0.954065  -0.375376  -0.509994   0.808041  \n",
       "4   0.497260   0.560954   0.953875  -0.908331  -0.943664   0.966438  -0.390171  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_transformed.head() #target passed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "train_MinMax=Normalizer(norm='l1').fit_transform(train)\n",
    "train_MinMax=pd.DataFrame(train_MinMax)"
   ]
  }
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