dataset_preparation_with_FeaturesAll_Regressed_bagOfWordsCombined.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy\n",
    "\n",
    "from sklearn.feature_extraction.text import CountVectorizer, TfidfTransformer\n",
    "from sklearn import tree\n",
    "from sklearn import neighbors\n",
    "from sklearn import naive_bayes\n",
    "from sklearn import svm\n",
    "from sklearn import linear_model\n",
    "from sklearn import ensemble\n",
    "from sklearn import neural_network\n",
    "from sklearn import feature_selection\n",
    "from dataset_preperation_modules import RawFeatureToBucketize, BucketFeatureExtractor\n",
    "\n",
    "# Preaparing Test Data for further processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.naive_bayes import MultinomialNB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.feature_selection import SelectFromModel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "test_vectorizer = CountVectorizer()\n",
    "\n",
    "test_file_name = 'test_tweets_preprocessed.txt'\n",
    "\n",
    "test_sentence_list = list()\n",
    "test_score_list = list()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "with open(test_file_name, 'r', encoding='utf8') as test_file:\n",
    "    for line in test_file:\n",
    "        splitted_line = line.split(' ')\n",
    "        splitted_line.pop()\n",
    "        score = float(splitted_line[-1])\n",
    "        test_score_list.append(score)\n",
    "        splitted_line.pop()\n",
    "        sentence = ' '.join(splitted_line)\n",
    "        test_sentence_list.append(sentence)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    " #Preparing Training Data for further processing\n",
    "\n",
    "vectorizer = CountVectorizer()\n",
    "\n",
    "file_name = 'train_tweets_preprocessed.txt'\n",
    "\n",
    "sentence_list = list()\n",
    "score_list = list()\n",
    "\n",
    "with open(file_name, 'r', encoding='utf8') as file:\n",
    "    for line in file:\n",
    "        splitted_line = line.split(' ')\n",
    "        splitted_line.pop()\n",
    "        score = float(splitted_line[-1])\n",
    "        score_list.append(score)\n",
    "        splitted_line.pop()\n",
    "        sentence = ' '.join(splitted_line)\n",
    "        sentence_list.append(sentence)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "score_array = numpy.array(score_list)\n",
    "test_score_array = numpy.array(test_score_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "feature_array = vectorizer.fit_transform(sentence_list)\n",
    "test_feature_array = vectorizer.transform(test_sentence_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(757, 1361)\n",
      "(200, 1361)\n"
     ]
    }
   ],
   "source": [
    "print(feature_array.shape)\n",
    "print(test_feature_array.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tfidf_transformer = TfidfTransformer()\n",
    "\n",
    "feature_array = tfidf_transformer.fit_transform(feature_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "test_feature_array = tfidf_transformer.transform(test_feature_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(757, 1361)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_array.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(200, 1361)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_feature_array.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Bucketing features into 7 distinct buckets from negative to positive 1-7\n",
    "\n",
    "features_to_bucketize = dict()\n",
    "\n",
    "for feature_name in vectorizer.get_feature_names():\n",
    "    features_to_bucketize[feature_name] = RawFeatureToBucketize(feature_name)\n",
    "\n",
    "\n",
    "for sentence, score in zip(sentence_list, score_list):\n",
    "    sentence = sentence.split(' ')\n",
    "\n",
    "    for word in sentence:\n",
    "        if word in features_to_bucketize:\n",
    "            features_to_bucketize[word].add_score(score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Bucketing operation\n",
    "\n",
    "word_sentiment_dictionary = dict()\n",
    "\n",
    "for feature_name in features_to_bucketize:\n",
    "    if 1.0 >= features_to_bucketize[feature_name].get_average_score() >= 0.5:\n",
    "        word_sentiment_dictionary[feature_name] = 'VeryPositive'\n",
    "    elif 0.5 > features_to_bucketize[feature_name].get_average_score() >= 0.0:\n",
    "        word_sentiment_dictionary[feature_name] = 'Positive'\n",
    "    elif 0.0 > features_to_bucketize[feature_name].get_average_score() >= -0.25:\n",
    "        word_sentiment_dictionary[feature_name] = 'Neutral'\n",
    "    elif -0.25 > features_to_bucketize[feature_name].get_average_score() >= -0.5:\n",
    "        word_sentiment_dictionary[feature_name] = 'MinorNegative'\n",
    "    elif -0.5 > features_to_bucketize[feature_name].get_average_score() >= -0.75:\n",
    "        word_sentiment_dictionary[feature_name] = 'Negative'\n",
    "    elif -0.75 > features_to_bucketize[feature_name].get_average_score() >= -0.90:\n",
    "        word_sentiment_dictionary[feature_name] = 'VeryNegative'\n",
    "    elif -0.90 > features_to_bucketize[feature_name].get_average_score() >= -1:\n",
    "        word_sentiment_dictionary[feature_name] = 'ExtremelyNegative'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-0.3011889035667103\n"
     ]
    }
   ],
   "source": [
    "# Average score of the Training Set\n",
    "\n",
    "score_total = 0\n",
    "number_of_scores = 0\n",
    "\n",
    "for score in score_list:\n",
    "    number_of_scores += 1\n",
    "    score_total += score\n",
    "\n",
    "print(score_total / number_of_scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'00': 'Neutral', '000': 'Positive', '01': 'Positive', '015': 'Positive', '018471': 'Positive', '02': 'Positive', '0212': 'Negative', '028': 'Negative', '03': 'Positive', '05': 'Positive', '050583': 'MinorNegative', '050630': 'Positive', '053277': 'Positive', '0535': 'Negative', '053841': 'Positive', '053888': 'Positive', '053979': 'Positive', '0545': 'Positive', '054561': 'Positive', '08': 'ExtremelyNegative', '09': 'ExtremelyNegative', '10': 'Neutral', '100': 'Positive', '100112': 'MinorNegative', '11': 'MinorNegative', '115': 'ExtremelyNegative', '12': 'MinorNegative', '120': 'Negative', '13': 'MinorNegative', '1309': 'VeryPositive', '14': 'Positive', '1415': 'Positive', '15': 'MinorNegative', '16': 'MinorNegative', '17': 'MinorNegative', '175': 'ExtremelyNegative', '18': 'Positive', '19': 'Neutral', '20': 'Negative', '2000': 'MinorNegative', '2004': 'Negative', '2009': 'VeryNegative', '2013': 'ExtremelyNegative', '2014': 'Positive', '212318': 'ExtremelyNegative', '212596': 'Positive', '23': 'Positive', '24': 'ExtremelyNegative', '25': 'ExtremelyNegative', '2986': 'MinorNegative', '30': 'MinorNegative', '300': 'ExtremelyNegative', '333': 'Negative', '334': 'Positive', '34': 'MinorNegative', '36': 'Positive', '386312': 'MinorNegative', '41': 'Negative', '410': 'MinorNegative', '43': 'Positive', '444': 'Negative', '444033': 'Negative', '45': 'ExtremelyNegative', '46': 'Negative', '50': 'MinorNegative', '5000': 'ExtremelyNegative', '507': 'MinorNegative', '5127': 'Positive', '532': 'Positive', '535637': 'Positive', '55': 'ExtremelyNegative', '576': 'Positive', '58': 'MinorNegative', '60': 'ExtremelyNegative', '610305': 'Neutral', '619': 'Positive', '630': 'VeryNegative', '640': 'Positive', '65': 'Positive', '656': 'MinorNegative', '68': 'MinorNegative', '686883': 'ExtremelyNegative', '69': 'MinorNegative', '694': 'Positive', '70': 'ExtremelyNegative', '71': 'Positive', '73': 'Positive', '77': 'Positive', '787': 'Positive', '94': 'MinorNegative', 'ab': 'Positive', 'abdull': 'ExtremelyNegative', 'abi': 'VeryNegative', 'about': 'ExtremelyNegative', 'acil': 'Neutral', 'acilen': 'ExtremelyNegative', 'aciz': 'ExtremelyNegative', 'acımak': 'ExtremelyNegative', 'ad': 'VeryNegative', 'ada': 'ExtremelyNegative', 'adet': 'Positive', 'adres': 'Negative', 'adına': 'ExtremelyNegative', 'afeder': 'Positive', 'aidat': 'Negative', 'ak': 'ExtremelyNegative', 'akbank': 'MinorNegative', 'akbaş': 'Neutral', 'akra': 'MinorNegative', 'akrep': 'ExtremelyNegative', 'aksi': 'ExtremelyNegative', 'aksu': 'Positive', 'aktarm': 'ExtremelyNegative', 'aktif': 'Neutral', 'aktive': 'Positive', 'akıllı': 'ExtremelyNegative', 'akşam': 'Neutral', 'al': 'Neutral', 'ala': 'Negative', 'alaka': 'Positive', 'alaçam': 'Positive', 'ali': 'ExtremelyNegative', 'alkışl': 'ExtremelyNegative', 'allah': 'VeryNegative', 'almak': 'MinorNegative', 'alo': 'Negative', 'alper': 'MinorNegative', 'alt': 'VeryNegative', 'altern': 'Neutral', 'altyap': 'ExtremelyNegative', 'alçak': 'ExtremelyNegative', 'alınma': 'Negative', 'alışka': 'ExtremelyNegative', 'alışve': 'MinorNegative', 'amaç': 'VeryNegative', 'ankara': 'Neutral', 'anlam': 'Negative', 'anlama': 'Neutral', 'anlatm': 'Neutral', 'anlayı': 'Negative', 'anlaşm': 'Positive', 'anne': 'Positive', 'anında': 'Positive', 'applic': 'ExtremelyNegative', 'ar': 'ExtremelyNegative', 'ara': 'Neutral', 'aracı': 'ExtremelyNegative', 'aracıl': 'Positive', 'aramak': 'Neutral', 'arami': 'ExtremelyNegative', 'aranma': 'Negative', 'araştı': 'VeryNegative', 'arefe': 'Neutral', 'arkada': 'MinorNegative', 'artik': 'ExtremelyNegative', 'artmak': 'VeryNegative', 'arttır': 'ExtremelyNegative', 'artçı': 'ExtremelyNegative', 'artı': 'ExtremelyNegative', 'artık': 'Negative', 'artırı': 'Positive', 'arz': 'MinorNegative', 'arzu': 'MinorNegative', 'arıza': 'Neutral', 'aslî': 'Positive', 'asıl': 'Positive', 'at': 'ExtremelyNegative', 'atamak': 'MinorNegative', 'atatür': 'ExtremelyNegative', 'ataşeh': 'ExtremelyNegative', 'atm': 'Neutral', 'atmak': 'MinorNegative', 'atme': 'MinorNegative', 'atmış': 'ExtremelyNegative', 'ato': 'MinorNegative', 'atrium': 'Negative', 'avans': 'MinorNegative', 'avanta': 'Neutral', 'avm': 'ExtremelyNegative', 'axess': 'Neutral', 'ay': 'VeryNegative', 'aylama': 'MinorNegative', 'aylık': 'Negative', 'aymak': 'Negative', 'aynen': 'Neutral', 'aynı': 'VeryNegative', 'ayrıca': 'Neutral', 'ayrılm': 'ExtremelyNegative', 'ayıp': 'VeryNegative', 'ayırma': 'ExtremelyNegative', 'az': 'MinorNegative', 'aç': 'Negative', 'açmak': 'Negative', 'açı': 'Positive', 'açık': 'MinorNegative', 'açıkla': 'Negative', 'açıkça': 'Neutral', 'ağaç': 'ExtremelyNegative', 'ağır': 'Negative', 'aşama': 'MinorNegative', 'aşk': 'MinorNegative', 'ba': 'Negative', 'baba': 'ExtremelyNegative', 'bahane': 'ExtremelyNegative', 'bahis': 'MinorNegative', 'bahset': 'Positive', 'bakan': 'ExtremelyNegative', 'baki': 'Positive', 'bakiye': 'Negative', 'bakmak': 'MinorNegative', 'balçov': 'Positive', 'bamya': 'Positive', 'bank': 'ExtremelyNegative', 'banka': 'Negative', 'bankam': 'VeryNegative', 'bara': 'Neutral', 'barbar': 'Positive', 'bari': 'VeryNegative', 'bas': 'Positive', 'basit': 'Negative', 'batmak': 'ExtremelyNegative', 'bayan': 'MinorNegative', 'bayram': 'Neutral', 'bağ': 'ExtremelyNegative', 'bağlam': 'MinorNegative', 'bağım': 'Positive', 'baş': 'ExtremelyNegative', 'başarm': 'ExtremelyNegative', 'başarı': 'VeryPositive', 'başbak': 'ExtremelyNegative', 'başka': 'Neutral', 'başlam': 'MinorNegative', 'başlık': 'ExtremelyNegative', 'başta': 'ExtremelyNegative', 'başvur': 'MinorNegative', 'be': 'Negative', 'bebek': 'Positive', 'beceri': 'ExtremelyNegative', 'becerm': 'MinorNegative', 'bedel': 'Negative', 'bek': 'VeryPositive', 'beklem': 'MinorNegative', 'bekçi': 'ExtremelyNegative', 'belirt': 'MinorNegative', 'belli': 'Neutral', 'ben': 'ExtremelyNegative', 'bence': 'MinorNegative', 'benzer': 'VeryPositive', 'berabe': 'ExtremelyNegative', 'berbat': 'ExtremelyNegative', 'beri': 'Negative', 'bey': 'VeryPositive', 'beyan': 'Neutral', 'bihabe': 'ExtremelyNegative', 'bildik': 'ExtremelyNegative', 'bildir': 'MinorNegative', 'bile': 'Negative', 'bileme': 'MinorNegative', 'bilet': 'Neutral', 'bilgi': 'Neutral', 'bilgil': 'Neutral', 'bili': 'ExtremelyNegative', 'bilinç': 'ExtremelyNegative', 'bilmek': 'MinorNegative', 'bin': 'Negative', 'bina': 'ExtremelyNegative', 'bindir': 'VeryPositive', 'bir': 'Negative', 'biraz': 'Neutral', 'birbir': 'Positive', 'birden': 'Neutral', 'birey': 'Positive', 'bireys': 'ExtremelyNegative', 'biri': 'Positive', 'birikm': 'Neutral', 'birlik': 'MinorNegative', 'birşey': 'VeryNegative', 'bitene': 'Positive', 'bitirm': 'Negative', 'bitmek': 'Negative', 'biçim': 'VeryNegative', 'blokla': 'ExtremelyNegative', 'bm': 'MinorNegative', 'bonus': 'Neutral', 'borç': 'Negative', 'boy': 'MinorNegative', 'boyunc': 'Neutral', 'bozdur': 'ExtremelyNegative', 'bozmak': 'VeryNegative', 'bozuk': 'MinorNegative', 'bozulm': 'ExtremelyNegative', 'boş': 'ExtremelyNegative', 'boşuna': 'ExtremelyNegative', 'br': 'VeryPositive', 'brave': 'Positive', 'bravo': 'ExtremelyNegative', 'brunch': 'ExtremelyNegative', 'bu': 'ExtremelyNegative', 'bugün': 'MinorNegative', 'buket': 'Positive', 'bul': 'ExtremelyNegative', 'bulama': 'Negative', 'bulmak': 'Positive', 'bulunm': 'MinorNegative', 'bur': 'ExtremelyNegative', 'bura': 'Neutral', 'burada': 'Neutral', 'burmak': 'ExtremelyNegative', 'burs': 'ExtremelyNegative', 'buçuk': 'ExtremelyNegative', 'bölüm': 'MinorNegative', 'bölünm': 'MinorNegative', 'böyles': 'ExtremelyNegative', 'bürokr': 'Negative', 'büyük': 'MinorNegative', 'büyütm': 'Neutral', 'bıkmak': 'ExtremelyNegative', 'bırakm': 'VeryNegative', 'cadde': 'Positive', 'campai': 'ExtremelyNegative', 'can': 'Negative', 'cari': 'MinorNegative', 'cart': 'VeryPositive', 'cc': 'VeryPositive', 'ce': 'Positive', 'center': 'Negative', 'cep': 'Negative', 'cevap': 'Negative', 'cevapl': 'VeryPositive', 'ceza': 'Negative', 'chp': 'MinorNegative', 'chuck': 'Neutral', 'cihaz': 'Negative', 'cinnet': 'VeryNegative', 'cu': 'MinorNegative', 'cuma': 'MinorNegative', 'cumhur': 'ExtremelyNegative', 'cüzdan': 'MinorNegative', 'da': 'Positive', 'dahası': 'ExtremelyNegative', 'dair': 'MinorNegative', 'dakika': 'MinorNegative', 'dalga': 'ExtremelyNegative', 'dan': 'Neutral', 'danışm': 'Neutral', 'davran': 'Positive', 'ddk': 'ExtremelyNegative', 'de': 'MinorNegative', 'dediği': 'Negative', 'deezer': 'Neutral', 'defa': 'Negative', 'defolm': 'VeryNegative', 'dek': 'Neutral', 'deli': 'ExtremelyNegative', 'deme': 'Negative', 'demek': 'Negative', 'denizb': 'Neutral', 'denmek': 'Negative', 'derin': 'Positive', 'dermek': 'MinorNegative', 'dert': 'ExtremelyNegative', 'destek': 'MinorNegative', 'detay': 'ExtremelyNegative', 'devam': 'Negative', 'devlet': 'ExtremelyNegative', 'değer': 'MinorNegative', 'değil': 'Negative', 'değilm': 'Neutral', 'değişi': 'Neutral', 'değişm': 'MinorNegative', 'dide': 'Neutral', 'digitü': 'Neutral', 'dikkat': 'Neutral', 'dil': 'ExtremelyNegative', 'dilek': 'Negative', 'dileme': 'VeryPositive', 'dilmek': 'MinorNegative', 'dink': 'ExtremelyNegative', 'dinlem': 'ExtremelyNegative', 'direk': 'Neutral', 'direkt': 'Negative', 'diye': 'ExtremelyNegative', 'diğer': 'ExtremelyNegative', 'dk': 'Negative', 'dokuma': 'MinorNegative', 'dokunm': 'ExtremelyNegative', 'dokuz': 'ExtremelyNegative', 'doland': 'VeryNegative', 'doldur': 'Neutral', 'dolmak': 'VeryPositive', 'dost': 'ExtremelyNegative', 'dosya': 'Neutral', 'doğanc': 'VeryNegative', 'doğru': 'Negative', 'doğrus': 'Neutral', 'dua': 'MinorNegative', 'dur': 'ExtremelyNegative', 'durmak': 'Negative', 'durum': 'ExtremelyNegative', 'duyarl': 'Positive', 'duygu': 'ExtremelyNegative', 'duymak': 'Neutral', 'duyurm': 'Negative', 'duyuru': 'Positive', 'dâhi': 'Positive', 'dâhil': 'Neutral', 'dönem': 'Negative', 'dönmek': 'Negative', 'dönüşm': 'Positive', 'döviz': 'ExtremelyNegative', 'dük': 'ExtremelyNegative', 'dümen': 'ExtremelyNegative', 'dün': 'Neutral', 'dünya': 'VeryNegative', 'düzelm': 'Negative', 'düzelt': 'Neutral', 'düş': 'Positive', 'düşman': 'MinorNegative', 'düşmek': 'Neutral', 'düşük': 'MinorNegative', 'düşünm': 'Negative', 'düşürm': 'Negative', 'dış': 'MinorNegative', 'ebe': 'ExtremelyNegative', 'edi': 'ExtremelyNegative', 'edil': 'ExtremelyNegative', 'edinme': 'VeryPositive', 'efe': 'Positive', 'efendi': 'Negative', 'ek': 'Neutral', 'ekip': 'Positive', 'ekleme': 'ExtremelyNegative', 'ekran': 'Neutral', 'eksi': 'Negative', 'ekstre': 'Negative', 'el': 'Negative', 'elektr': 'MinorNegative', 'elma': 'Positive', 'emekli': 'Positive', 'emin': 'Positive', 'en': 'ExtremelyNegative', 'enayi': 'ExtremelyNegative', 'enfes': 'Positive', 'engel': 'Positive', 'enkaz': 'Neutral', 'entere': 'Negative', 'esen': 'VeryPositive', 'eski': 'Neutral', 'eskort': 'ExtremelyNegative', 'esra': 'VeryPositive', 'et': 'Negative', 'etkile': 'Neutral', 'etmek': 'MinorNegative', 'etmen': 'Positive', 'euro': 'ExtremelyNegative', 'ev': 'VeryPositive', 'evet': 'MinorNegative', 'evvel': 'ExtremelyNegative', 'exclamationmark': 'VeryNegative', 'ezgi': 'Positive', 'eğer': 'MinorNegative', 'fahiş': 'ExtremelyNegative', 'fail': 'Neutral', 'faiz': 'MinorNegative', 'faks': 'Positive', 'fark': 'Neutral', 'farket': 'Neutral', 'fatura': 'MinorNegative', 'fazla': 'Negative', 'fazlas': 'Negative', 'fed': 'Negative', 'ferit': 'ExtremelyNegative', 'fikir': 'VeryPositive', 'firma': 'Neutral', 'fiyat': 'ExtremelyNegative', 'flex': 'VeryPositive', 'follow': 'ExtremelyNegative', 'fon': 'Negative', 'fırsat': 'VeryNegative', 'fırça': 'VeryNegative', 'galata': 'Neutral', 'garant': 'Negative', 'gayet': 'Positive', 'gaz': 'ExtremelyNegative', 'gazete': 'ExtremelyNegative', 'gece': 'Negative', 'gecikm': 'MinorNegative', 'gedi': 'ExtremelyNegative', 'gedik': 'MinorNegative', 'gele': 'ExtremelyNegative', 'gelece': 'MinorNegative', 'gelen': 'Negative', 'gelişm': 'ExtremelyNegative', 'gelmek': 'MinorNegative', 'gelmiç': 'VeryNegative', 'genel': 'VeryNegative', 'genç': 'Neutral', 'gerek': 'Neutral', 'gerekl': 'MinorNegative', 'gerekm': 'MinorNegative', 'geri': 'Neutral', 'gerize': 'ExtremelyNegative', 'gerçek': 'MinorNegative', 'geç': 'Negative', 'geçen': 'Neutral', 'geçici': 'Neutral', 'geçilm': 'ExtremelyNegative', 'geçinm': 'ExtremelyNegative', 'geçirm': 'VeryNegative', 'geçişt': 'Negative', 'geçmek': 'Negative', 'gibi': 'Neutral', 'gibisi': 'MinorNegative', 'giderm': 'Negative', 'gine': 'ExtremelyNegative', 'girmek': 'MinorNegative', 'gitmek': 'MinorNegative', 'gizli': 'ExtremelyNegative', 'gişe': 'ExtremelyNegative', 'grip': 'Positive', 'gönder': 'MinorNegative', 'gönül': 'VeryPositive', 'göre': 'Neutral', 'görev': 'VeryNegative', 'görmek': 'Negative', 'görünm': 'Negative', 'görünt': 'ExtremelyNegative', 'görüş': 'Positive', 'görüşm': 'Positive', 'göster': 'MinorNegative', 'götürm': 'ExtremelyNegative', 'göz': 'VeryNegative', 'göztep': 'ExtremelyNegative', 'gözükm': 'MinorNegative', 'gü': 'Neutral', 'gün': 'MinorNegative', 'güncel': 'MinorNegative', 'günde': 'Negative', 'gündem': 'ExtremelyNegative', 'gündüz': 'Positive', 'günlem': 'ExtremelyNegative', 'güve': 'ExtremelyNegative', 'güvenl': 'VeryNegative', 'güvenm': 'ExtremelyNegative', 'güzel': 'Negative', 'güç': 'ExtremelyNegative', 'ha': 'MinorNegative', 'haber': 'Negative', 'hacı': 'MinorNegative', 'had': 'ExtremelyNegative', 'hadi': 'MinorNegative', 'haf': 'MinorNegative', 'hafta': 'MinorNegative', 'haftas': 'Negative', 'hak': 'MinorNegative', 'hakem': 'Negative', 'hakkın': 'MinorNegative', 'hal': 'Negative', 'hallet': 'Positive', 'hamil': 'VeryNegative', 'han': 'Positive', 'hangis': 'VeryPositive', 'hanım': 'Positive', 'haraç': 'MinorNegative', 'harcam': 'MinorNegative', 'hareke': 'MinorNegative', 'hariç': 'ExtremelyNegative', 'has': 'ExtremelyNegative', 'hassas': 'VeryPositive', 'hasta': 'Negative', 'hasır': 'ExtremelyNegative', 'hat': 'Negative', 'hata': 'Neutral', 'hatice': 'VeryPositive', 'hatırl': 'MinorNegative', 'hava': 'Neutral', 'havale': 'Negative', 'havali': 'ExtremelyNegative', 'hayal': 'ExtremelyNegative', 'hayat': 'ExtremelyNegative', 'hayhay': 'ExtremelyNegative', 'hayran': 'Positive', 'hayır': 'MinorNegative', 'hazır': 'MinorNegative', 'hele': 'Positive', 'hemen': 'Positive', 'hep': 'Neutral', 'hergün': 'ExtremelyNegative', 'herhan': 'Neutral', 'herhâl': 'MinorNegative', 'heryer': 'ExtremelyNegative', 'herşey': 'MinorNegative', 'hesap': 'Negative', 'hesapl': 'MinorNegative', 'heyet': 'Negative', 'hizmet': 'Negative', 'hiç': 'ExtremelyNegative', 'hiçbir': 'ExtremelyNegative', 'hiçbiş': 'ExtremelyNegative', 'hoş': 'VeryPositive', 'huzur': 'ExtremelyNegative', 'hâlen': 'MinorNegative', 'hâlâ': 'Negative', 'hız': 'Neutral', 'hızlan': 'VeryPositive', 'hızlı': 'VeryPositive', 'iade': 'MinorNegative', 'ibare': 'Neutral', 'ibaret': 'ExtremelyNegative', 'iflâs': 'ExtremelyNegative', 'ihbar': 'VeryPositive', 'ihtar': 'ExtremelyNegative', 'ihtima': 'ExtremelyNegative', 'ihtiya': 'MinorNegative', 'ikinci': 'ExtremelyNegative', 'il': 'MinorNegative', 'ileti': 'Negative', 'iletiş': 'MinorNegative', 'iletme': 'MinorNegative', 'ilgi': 'Positive', 'ilgile': 'MinorNegative', 'ilişki': 'VeryNegative', 'ilk': 'ExtremelyNegative', 'illet': 'MinorNegative', 'illâ': 'VeryNegative', 'ilçe': 'ExtremelyNegative', 'imek': 'Neutral', 'inadın': 'ExtremelyNegative', 'ince': 'MinorNegative', 'indirm': 'ExtremelyNegative', 'inmek': 'Positive', 'insaf': 'Negative', 'insan': 'Negative', 'inşall': 'MinorNegative', 'iptal': 'Negative', 'irtiba': 'Negative', 'is': 'MinorNegative', 'isim': 'MinorNegative', 'ispat': 'ExtremelyNegative', 'istek': 'Negative', 'isteme': 'MinorNegative', 'ister': 'MinorNegative', 'istirh': 'ExtremelyNegative', 'itibar': 'Neutral', 'itiraz': 'Neutral', 'iyi': 'Neutral', 'iz': 'Negative', 'izah': 'ExtremelyNegative', 'izin': 'VeryNegative', 'iç': 'Negative', 'içeri': 'Neutral', 'için': 'VeryPositive', 'içmek': 'ExtremelyNegative', 'içtenl': 'VeryPositive', 'iş': 'Negative', 'işlem': 'Neutral', 'işleti': 'Negative', 'kabul': 'Positive', 'kadar': 'Neutral', 'kaf': 'ExtremelyNegative', 'kafa': 'ExtremelyNegative', 'kahram': 'Positive', 'kaldır': 'Positive', 'kalite': 'VeryNegative', 'kalkma': 'ExtremelyNegative', 'kalmak': 'MinorNegative', 'kalın': 'VeryNegative', 'kampan': 'Negative', 'kan': 'ExtremelyNegative', 'kana': 'ExtremelyNegative', 'kanal': 'Neutral', 'kapalı': 'MinorNegative', 'kapanm': 'MinorNegative', 'kapatm': 'Negative', 'kapı': 'VeryNegative', 'kara': 'Neutral', 'karar': 'Negative', 'kardeş': 'MinorNegative', 'kargo': 'VeryPositive', 'karmak': 'Negative', 'kart': 'MinorNegative', 'karşı': 'MinorNegative', 'karşıl': 'ExtremelyNegative', 'kas': 'Neutral', 'kasım': 'ExtremelyNegative', 'kasıt': 'Negative', 'kat': 'MinorNegative', 'katı': 'Negative', 'katılm': 'ExtremelyNegative', 'kavram': 'VeryNegative', 'kaybet': 'Negative', 'kaybol': 'Neutral', 'kaymak': 'MinorNegative', 'kayıt': 'ExtremelyNegative', 'kazanç': 'ExtremelyNegative', 'kaçta': 'ExtremelyNegative', 'kedi': 'ExtremelyNegative', 'keklic': 'ExtremelyNegative', 'kemerk': 'Positive', 'kendi': 'Neutral', 'ker': 'Negative', 'kesin': 'VeryPositive', 'kesinl': 'ExtremelyNegative', 'kesmek': 'Negative', 'kez': 'Negative', 'kezban': 'MinorNegative', 'keşke': 'ExtremelyNegative', 'ki': 'Negative', 'kilit': 'Neutral', 'kilitl': 'ExtremelyNegative', 'kim': 'MinorNegative', 'kimse': 'Negative', 'king': 'Neutral', 'kings': 'Neutral', 'kiş': 'Negative', 'kişi': 'ExtremelyNegative', 'kk': 'Neutral', 'kktc': 'Neutral', 'ko': 'MinorNegative', 'kocama': 'ExtremelyNegative', 'kod': 'MinorNegative', 'kol': 'ExtremelyNegative', 'kolay': 'MinorNegative', 'kolayl': 'Neutral', 'komisy': 'ExtremelyNegative', 'komple': 'ExtremelyNegative', 'kontro': 'Neutral', 'kontör': 'MinorNegative', 'konu': 'Neutral', 'konuşm': 'Negative', 'kopya': 'Neutral', 'koruma': 'ExtremelyNegative', 'kot': 'Positive', 'kovmak': 'VeryNegative', 'koymak': 'Negative', 'kredi': 'MinorNegative', 'kriz': 'ExtremelyNegative', 'kulak': 'ExtremelyNegative', 'kullan': 'MinorNegative', 'kulüp': 'Positive', 'kumbar': 'VeryPositive', 'kur': 'VeryNegative', 'kurban': 'Neutral', 'kurtar': 'ExtremelyNegative', 'kurtul': 'Negative', 'kuru': 'MinorNegative', 'kuruş': 'MinorNegative', 'kurye': 'MinorNegative', 'kuryen': 'ExtremelyNegative', 'kusur': 'Negative', 'kutlam': 'MinorNegative', 'kuzen': 'MinorNegative', 'köklü': 'ExtremelyNegative', 'köprü': 'Positive', 'kötü': 'ExtremelyNegative', 'küfür': 'ExtremelyNegative', 'küp': 'VeryPositive', 'küçük': 'ExtremelyNegative', 'küçülm': 'Neutral', 'kıpmak': 'MinorNegative', 'kır': 'ExtremelyNegative', 'kırık': 'ExtremelyNegative', 'kısa': 'Neutral', 'kıvanç': 'ExtremelyNegative', 'kıvrak': 'Negative', 'kıymet': 'ExtremelyNegative', 'kız': 'VeryPositive', 'la': 'MinorNegative', 'laf': 'MinorNegative', 'lahana': 'ExtremelyNegative', 'lakin': 'MinorNegative', 'lan': 'ExtremelyNegative', 'lazım': 'Positive', 'limit': 'Negative', 'link': 'MinorNegative', 'lira': 'VeryNegative', 'lise': 'Neutral', 'list': 'ExtremelyNegative', 'liste': 'Negative', 'lokasy': 'VeryPositive', 'los': 'Neutral', 'lumia': 'Positive', 'lütfen': 'Neutral', 'maales': 'Neutral', 'maaş': 'Negative', 'mafya': 'ExtremelyNegative', 'mah': 'Positive', 'mahke': 'MinorNegative', 'mahkem': 'ExtremelyNegative', 'mail': 'MinorNegative', 'mal': 'ExtremelyNegative', 'maltep': 'Positive', 'malum': 'ExtremelyNegative', 'mangır': 'ExtremelyNegative', 'mantık': 'ExtremelyNegative', 'marife': 'MinorNegative', 'market': 'Negative', 'mart': 'ExtremelyNegative', 'maslak': 'VeryPositive', 'masraf': 'MinorNegative', 'mazere': 'ExtremelyNegative', 'mağdur': 'Negative', 'meb': 'MinorNegative', 'mecbur': 'ExtremelyNegative', 'mecidi': 'Positive', 'medya': 'Positive', 'mehmet': 'Positive', 'mekik': 'MinorNegative', 'mektup': 'ExtremelyNegative', 'memnun': 'Positive', 'memur': 'ExtremelyNegative', 'menü': 'ExtremelyNegative', 'merak': 'VeryNegative', 'merhab': 'Neutral', 'merkez': 'Negative', 'mesai': 'Neutral', 'mesaj': 'MinorNegative', 'mesel': 'MinorNegative', 'mesele': 'Negative', 'meselâ': 'Positive', 'mesut': 'VeryPositive', 'mevcut': 'ExtremelyNegative', 'mevdua': 'ExtremelyNegative', 'meyve': 'Neutral', 'meşgul': 'Negative', 'mi': 'MinorNegative', 'miktar': 'Positive', 'mil': 'MinorNegative', 'miles': 'Positive', 'millet': 'ExtremelyNegative', 'milâs': 'Positive', 'mis': 'Neutral', 'mobil': 'Neutral', 'mod': 'ExtremelyNegative', 'moment': 'Negative', 'mother': 'Neutral', 'ms': 'MinorNegative', 'mu': 'ExtremelyNegative', 'muamel': 'ExtremelyNegative', 'muhata': 'ExtremelyNegative', 'mukabi': 'ExtremelyNegative', 'murat': 'Positive', 'mus': 'MinorNegative', 'mutsuz': 'Negative', 'muş': 'MinorNegative', 'müdür': 'VeryNegative', 'mümkün': 'Neutral', 'müsait': 'Neutral', 'müzik': 'ExtremelyNegative', 'müşter': 'Negative', 'mı': 'Neutral', 'nakit': 'Neutral', 'nasıl': 'Neutral', 'nasıls': 'ExtremelyNegative', 'ne': 'Negative', 'neden': 'Positive', 'nedens': 'ExtremelyNegative', 'nefes': 'ExtremelyNegative', 'negativesmiley': 'Negative', 'nekada': 'VeryPositive', 'nerede': 'VeryNegative', 'net': 'Positive', 'ney': 'ExtremelyNegative', 'nokta': 'Positive', 'normal': 'MinorNegative', 'not': 'Neutral', 'now': 'ExtremelyNegative', 'nsa': 'Positive', 'nter': 'Positive', 'ntern': 'Positive', 'numara': 'MinorNegative', 'nüfus': 'Negative', 'odak': 'VeryPositive', 'ofer': 'Neutral', 'ofis': 'ExtremelyNegative', 'okumak': 'VeryNegative', 'olabil': 'Neutral', 'olacak': 'MinorNegative', 'olasıl': 'MinorNegative', 'olay': 'Neutral', 'oldu': 'Negative', 'oldukç': 'VeryPositive', 'olmadı': 'MinorNegative', 'olmak': 'MinorNegative', 'olmaz': 'MinorNegative', 'olumlu': 'MinorNegative', 'olumsu': 'MinorNegative', 'olur': 'Neutral', 'oluşma': 'Neutral', 'oluşum': 'Neutral', 'on': 'ExtremelyNegative', 'onay': 'Negative', 'onayla': 'Negative', 'onca': 'MinorNegative', 'online': 'Neutral', 'ons': 'VeryPositive', 'onu': 'ExtremelyNegative', 'operat': 'Neutral', 'or': 'MinorNegative', 'ora': 'Negative', 'oradan': 'Neutral', 'oral': 'ExtremelyNegative', 'oran': 'ExtremelyNegative', 'orman': 'Negative', 'orta': 'VeryPositive', 'ortak': 'ExtremelyNegative', 'ortala': 'ExtremelyNegative', 'osurma': 'Negative', 'otomat': 'MinorNegative', 'oturma': 'Negative', 'oy': 'ExtremelyNegative', 'oyun': 'Positive', 'pa': 'ExtremelyNegative', 'paket': 'ExtremelyNegative', 'par': 'Negative', 'para': 'Negative', 'paraca': 'MinorNegative', 'parama': 'Negative', 'pardo': 'ExtremelyNegative', 'parmak': 'ExtremelyNegative', 'parola': 'Positive', 'parti': 'Negative', 'parça': 'ExtremelyNegative', 'parçal': 'MinorNegative', 'patron': 'ExtremelyNegative', 'paylaş': 'MinorNegative', 'pazar': 'Positive', 'pazart': 'Neutral', 'peki': 'VeryPositive', 'perhiz': 'ExtremelyNegative', 'person': 'MinorNegative', 'perşem': 'Positive', 'peş': 'VeryNegative', 'peşin': 'MinorNegative', 'pir': 'Positive', 'platfo': 'Neutral', 'platin': 'ExtremelyNegative', 'positivesmiley': 'Positive', 'premiu': 'Neutral', 'proble': 'Neutral', 'profil': 'VeryNegative', 'progra': 'ExtremelyNegative', 'promos': 'Neutral', 'protes': 'ExtremelyNegative', 'psikol': 'ExtremelyNegative', 'puan': 'Neutral', 'pürüz': 'VeryPositive', 'questionmark': 'MinorNegative', 'rahat': 'Negative', 'rakam': 'Neutral', 'rapor': 'Neutral', 'reddol': 'ExtremelyNegative', 'reflü': 'MinorNegative', 'reklâm': 'Negative', 'renk': 'ExtremelyNegative', 'resmen': 'MinorNegative', 'resmî': 'MinorNegative', 'ret': 'MinorNegative', 'reva': 'ExtremelyNegative', 'rezale': 'Negative', 'rezil': 'VeryNegative', 'rica': 'Neutral', 'robot': 'ExtremelyNegative', 'ruhsat': 'Positive', 'saat': 'Neutral', 'saatle': 'Negative', 'sabah': 'MinorNegative', 'sabaht': 'ExtremelyNegative', 'sabri': 'ExtremelyNegative', 'sabırl': 'VeryPositive', 'sadece': 'Negative', 'saha': 'ExtremelyNegative', 'sahip': 'MinorNegative', 'sallam': 'ExtremelyNegative', 'sanal': 'MinorNegative', 'sanki': 'ExtremelyNegative', 'sanmak': 'Negative', 'sarıye': 'ExtremelyNegative', 'satmak': 'Negative', 'satış': 'Positive', 'savcı': 'Positive', 'savsak': 'Negative', 'sayama': 'ExtremelyNegative', 'saye': 'ExtremelyNegative', 'sayfa': 'MinorNegative', 'saygı': 'VeryNegative', 'saymak': 'ExtremelyNegative', 'sayı': 'ExtremelyNegative', 'sayın': 'Negative', 'saçma': 'Negative', 'sağlam': 'Positive', 'sağlık': 'MinorNegative', 'sağmak': 'MinorNegative', 'sağolm': 'Positive', 'sbs': 'Positive', 'se': 'Negative', 'sebep': 'Negative', 'sefer': 'MinorNegative', 'sel': 'ExtremelyNegative', 'sele': 'ExtremelyNegative', 'self': 'ExtremelyNegative', 'sema': 'Neutral', 'semt': 'VeryPositive', 'sene': 'Neutral', 'serry': 'Neutral', 'ses': 'Positive', 'sesli': 'VeryNegative', 'sevgi': 'Negative', 'sevinm': 'Positive', 'seçmek': 'ExtremelyNegative', 'sigar': 'ExtremelyNegative', 'sigort': 'ExtremelyNegative', 'sikke': 'Neutral', 'silmek': 'ExtremelyNegative', 'sinirl': 'ExtremelyNegative', 'sirkec': 'MinorNegative', 'sistem': 'Negative', 'site': 'Positive', 'sitem': 'ExtremelyNegative', 'siz': 'Negative', 'sizsin': 'Negative', 'slim': 'MinorNegative', 'sol': 'VeryPositive', 'solmak': 'MinorNegative', 'sonlan': 'Negative', 'sonra': 'Negative', 'sonsuz': 'VeryPositive', 'sonund': 'ExtremelyNegative', 'sonuç': 'MinorNegative', 'sonuçl': 'Positive', 'sor': 'Neutral', 'sormak': 'MinorNegative', 'soru': 'Positive', 'soruma': 'Negative', 'soruml': 'ExtremelyNegative', 'sorun': 'MinorNegative', 'sosyal': 'Positive', 'soyad': 'Positive', 'soygun': 'VeryNegative', 'soğuma': 'Positive', 'specia': 'Neutral', 'standa': 'ExtremelyNegative', 'su': 'Positive', 'surat': 'VeryNegative', 'suç': 'Positive', 'swift': 'Neutral', 'sövmek': 'ExtremelyNegative', 'söylem': 'MinorNegative', 'söz': 'MinorNegative', 'süper': 'VeryPositive', 'süre': 'MinorNegative', 'sürekl': 'ExtremelyNegative', 'süreç': 'Neutral', 'sürmek': 'MinorNegative', 'sıfır': 'ExtremelyNegative', 'sıkı': 'ExtremelyNegative', 'sınıf': 'ExtremelyNegative', 'sınır': 'VeryNegative', 'sır': 'Negative', 'sıra': 'ExtremelyNegative', 'sırada': 'ExtremelyNegative', 'sırf': 'ExtremelyNegative', 'sığmak': 'ExtremelyNegative', 't1': 'Positive', 'ta': 'MinorNegative', 'taa': 'Negative', 'tabiî': 'ExtremelyNegative', 'taciz': 'ExtremelyNegative', 'tahakk': 'ExtremelyNegative', 'tahrik': 'ExtremelyNegative', 'tahsil': 'Negative', 'tak': 'ExtremelyNegative', 'takdir': 'Positive', 'takip': 'Neutral', 'taksit': 'MinorNegative', 'taktik': 'MinorNegative', 'talep': 'Negative', 'talima': 'Negative', 'tam': 'Negative', 'tamam': 'Positive', 'tamame': 'ExtremelyNegative', 'tamaml': 'ExtremelyNegative', 'tane': 'ExtremelyNegative', 'tanyer': 'MinorNegative', 'tanıml': 'Neutral', 'taraf': 'Negative', 'tarafı': 'Neutral', 'tarihî': 'Negative', 'tarz': 'VeryNegative', 'tasarl': 'ExtremelyNegative', 'tatbik': 'MinorNegative', 'tatil': 'Neutral', 'tatlı': 'ExtremelyNegative', 'tavsiy': 'Neutral', 'tazmin': 'ExtremelyNegative', 'taşıma': 'ExtremelyNegative', 'te': 'Neutral', 'tebrik': 'Positive', 'tefeci': 'ExtremelyNegative', 'tehdit': 'ExtremelyNegative', 'tehir': 'ExtremelyNegative', 'tehlik': 'ExtremelyNegative', 'teiaş': 'Positive', 'tek': 'Neutral', 'teklif': 'ExtremelyNegative', 'teknik': 'Positive', 'tekrar': 'Positive', 'tel': 'Negative', 'telefo': 'MinorNegative', 'telese': 'Neutral', 'tem': 'ExtremelyNegative', 'tembel': 'Negative', 'tembih': 'VeryNegative', 'temsil': 'MinorNegative', 'tesekk': 'VeryPositive', 'teslim': 'MinorNegative', 'teşekk': 'Positive', 'the': 'ExtremelyNegative', 'this': 'Neutral', 'ti': 'Positive', 'tip': 'ExtremelyNegative', 'tl': 'Negative', 'tobb': 'ExtremelyNegative', 'toplam': 'VeryNegative', 'total': 'ExtremelyNegative', 'trabzo': 'Neutral', 'transf': 'MinorNegative', 'tufan': 'Positive', 'tuhaf': 'MinorNegative', 'tura': 'Positive', 'turkey': 'ExtremelyNegative', 'turşu': 'ExtremelyNegative', 'tutar': 'Neutral', 'tutmak': 'ExtremelyNegative', 'tuğba': 'MinorNegative', 'tuş': 'Neutral', 'tv': 'ExtremelyNegative', 'tweet': 'MinorNegative', 'tweete': 'ExtremelyNegative', 'twitte': 'Positive', 'tüketm': 'Negative', 'türki': 'ExtremelyNegative', 'türlü': 'MinorNegative', 'tıkmak': 'ExtremelyNegative', 'tıp': 'ExtremelyNegative', 'ufacık': 'MinorNegative', 'ula': 'ExtremelyNegative', 'ulamak': 'Negative', 'ulaşma': 'MinorNegative', 'ulaşım': 'Neutral', 'umar': 'Negative', 'ummak': 'Positive', 'umut': 'Negative', 'usb': 'MinorNegative', 'utanma': 'VeryPositive', 'uyarma': 'ExtremelyNegative', 'uyarı': 'Neutral', 'uyduru': 'MinorNegative', 'uygula': 'Negative', 'uygun': 'Positive', 'uymak': 'ExtremelyNegative', 'uzatma': 'MinorNegative', 'uzay': 'ExtremelyNegative', 'uzun': 'VeryNegative', 'uğraş': 'ExtremelyNegative', 'uğraşm': 'VeryPositive', 'vaat': 'VeryNegative', 'vade': 'MinorNegative', 'vakit': 'Negative', 'var': 'MinorNegative', 'varmak': 'VeryPositive', 'vatand': 'ExtremelyNegative', 've': 'ExtremelyNegative', 'vergi': 'MinorNegative', 'vermek': 'MinorNegative', 'vicdan': 'ExtremelyNegative', 'wall': 'Negative', 'we': 'Positive', 'web': 'MinorNegative', 'window': 'Neutral', 'yaa': 'VeryPositive', 'yaaa': 'ExtremelyNegative', 'yabanc': 'ExtremelyNegative', 'yahu': 'ExtremelyNegative', 'yak': 'ExtremelyNegative', 'yaka': 'VeryNegative', 'yaklaş': 'Positive', 'yakın': 'MinorNegative', 'yalan': 'ExtremelyNegative', 'yan': 'Negative', 'yanlış': 'MinorNegative', 'yansım': 'Positive', 'yanılm': 'VeryNegative', 'yanıt': 'VeryNegative', 'yanıtl': 'Negative', 'yapmak': 'MinorNegative', 'yapı': 'Negative', 'yapıla': 'Neutral', 'yapışm': 'Negative', 'yarama': 'ExtremelyNegative', 'yarar': 'ExtremelyNegative', 'yard': 'Neutral', 'yardım': 'MinorNegative', 'yarmak': 'MinorNegative', 'yarım': 'Negative', 'yarın': 'Positive', 'yarışm': 'Positive', 'yasa': 'MinorNegative', 'yasak': 'ExtremelyNegative', 'yasal': 'ExtremelyNegative', 'yatırm': 'Positive', 'yava': 'ExtremelyNegative', 'yavşak': 'ExtremelyNegative', 'yaz': 'ExtremelyNegative', 'yazar': 'Positive', 'yazmak': 'Neutral', 'yazı': 'ExtremelyNegative', 'yazık': 'ExtremelyNegative', 'yağlı': 'ExtremelyNegative', 'yaş': 'Positive', 'yaşama': 'MinorNegative', 'yemek': 'ExtremelyNegative', 'yeni': 'Negative', 'yenide': 'VeryNegative', 'yenike': 'Positive', 'yenile': 'MinorNegative', 'yer': 'Negative', 'yeter': 'Negative', 'yeteri': 'ExtremelyNegative', 'yeterl': 'MinorNegative', 'yetişm': 'Positive', 'yetki': 'Neutral', 'yetmek': 'VeryNegative', 'yeşil': 'ExtremelyNegative', 'ygs': 'Negative', 'yirmi': 'ExtremelyNegative', 'yiyici': 'ExtremelyNegative', 'yok': 'Negative', 'yol': 'Negative', 'yollam': 'Negative', 'yorum': 'MinorNegative', 'you': 'ExtremelyNegative', 'yoğ': 'ExtremelyNegative', 'yoğun': 'MinorNegative', 'yumak': 'ExtremelyNegative', 'yurt': 'Positive', 'yurtdı': 'Neutral', 'yuvarl': 'ExtremelyNegative', 'yâd': 'Neutral', 'yâr': 'ExtremelyNegative', 'yöneti': 'ExtremelyNegative', 'yönetm': 'ExtremelyNegative', 'yönlen': 'Neutral', 'yüklem': 'MinorNegative', 'yüklü': 'Neutral', 'yürüme': 'ExtremelyNegative', 'yürütm': 'ExtremelyNegative', 'yüz': 'Neutral', 'yüzünd': 'Negative', 'yıl': 'MinorNegative', 'yılbaş': 'ExtremelyNegative', 'yılmak': 'ExtremelyNegative', 'yırtma': 'Negative', 'zaman': 'Neutral', 'zan': 'ExtremelyNegative', 'zana': 'Positive', 'zarar': 'ExtremelyNegative', 'zekâ': 'Negative', 'zor': 'Negative', 'zorunl': 'ExtremelyNegative', 'âciz': 'ExtremelyNegative', 'âmâ': 'Negative', 'çabuk': 'VeryPositive', 'çaktır': 'ExtremelyNegative', 'çalmak': 'MinorNegative', 'çalışa': 'Positive', 'çalışm': 'MinorNegative', 'çare': 'ExtremelyNegative', 'çarşam': 'Positive', 'çaycıl': 'ExtremelyNegative', 'çağ': 'Positive', 'çağrı': 'MinorNegative', 'çek': 'ExtremelyNegative', 'çekeme': 'ExtremelyNegative', 'çekilm': 'ExtremelyNegative', 'çekinm': 'MinorNegative', 'çekme': 'Positive', 'çekmek': 'Negative', 'çevirm': 'Positive', 'çeyrek': 'Neutral', 'çifte': 'ExtremelyNegative', 'çorlu': 'MinorNegative', 'çökmek': 'ExtremelyNegative', 'çöz': 'Positive', 'çözmek': 'MinorNegative', 'çözüml': 'Neutral', 'çıkarm': 'MinorNegative', 'çıkmak': 'MinorNegative', 'çıkmaz': 'Positive', 'çıldır': 'ExtremelyNegative', 'ödemek': 'Negative', 'ödenme': 'Negative', 'öldürm': 'ExtremelyNegative', 'ölmek': 'ExtremelyNegative', 'ölüm': 'ExtremelyNegative', 'ömer': 'Positive', 'ömür': 'ExtremelyNegative', 'ön': 'ExtremelyNegative', 'önceli': 'ExtremelyNegative', 'önem': 'Positive', 'öner': 'Positive', 'önerme': 'MinorNegative', 'örnek': 'VeryPositive', 'öte': 'VeryPositive', 'öze': 'MinorNegative', 'özel': 'Negative', 'özelli': 'Neutral', 'özet': 'Positive', 'özkes': 'Positive', 'öğle': 'Neutral', 'öğrenc': 'Negative', 'öğrenm': 'Neutral', 'ücret': 'MinorNegative', 'ülke': 'ExtremelyNegative', 'ün': 'Negative', 'üretme': 'VeryPositive', 'ürün': 'ExtremelyNegative', 'üsküda': 'Positive', 'üslup': 'VeryPositive', 'üst': 'MinorNegative', 'üsteli': 'ExtremelyNegative', 'üstüne': 'Negative', 'üye': 'MinorNegative', 'üzer': 'Neutral', 'üzerin': 'Neutral', 'üzüntü': 'ExtremelyNegative', 'üç': 'ExtremelyNegative', 'ısrar': 'Positive', 'şahenk': 'ExtremelyNegative', 'şahsen': 'Positive', 'şaka': 'MinorNegative', 'şans': 'Positive', 'şaşkın': 'Neutral', 'şaşırm': 'Positive', 'şefik': 'Positive', 'şekil': 'Neutral', 'şeref': 'ExtremelyNegative', 'şiddet': 'ExtremelyNegative', 'şifre': 'Neutral', 'şiir': 'ExtremelyNegative', 'şikâye': 'Negative', 'şimdi': 'MinorNegative', 'şimdid': 'VeryPositive', 'şimdil': 'Negative', 'şirket': 'VeryNegative', 'şişmek': 'ExtremelyNegative', 'şua': 'Positive', 'şube': 'MinorNegative', 'şut': 'Neutral', 'şükür': 'ExtremelyNegative', 'şüphe': 'ExtremelyNegative'}\n"
     ]
    }
   ],
   "source": [
    "# Print Dictionary\n",
    "\n",
    "print(word_sentiment_dictionary)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "00: Neutral\n",
      "000: Positive\n",
      "01: Positive\n",
      "015: Positive\n",
      "018471: Positive\n",
      "02: Positive\n",
      "0212: Negative\n",
      "028: Negative\n",
      "03: Positive\n",
      "05: Positive\n",
      "050583: MinorNegative\n",
      "050630: Positive\n",
      "053277: Positive\n",
      "0535: Negative\n",
      "053841: Positive\n",
      "053888: Positive\n",
      "053979: Positive\n",
      "0545: Positive\n",
      "054561: Positive\n",
      "08: ExtremelyNegative\n",
      "09: ExtremelyNegative\n",
      "10: Neutral\n",
      "100: Positive\n",
      "100112: MinorNegative\n",
      "11: MinorNegative\n",
      "115: ExtremelyNegative\n",
      "12: MinorNegative\n",
      "120: Negative\n",
      "13: MinorNegative\n",
      "1309: VeryPositive\n",
      "14: Positive\n",
      "1415: Positive\n",
      "15: MinorNegative\n",
      "16: MinorNegative\n",
      "17: MinorNegative\n",
      "175: ExtremelyNegative\n",
      "18: Positive\n",
      "19: Neutral\n",
      "20: Negative\n",
      "2000: MinorNegative\n",
      "2004: Negative\n",
      "2009: VeryNegative\n",
      "2013: ExtremelyNegative\n",
      "2014: Positive\n",
      "212318: ExtremelyNegative\n",
      "212596: Positive\n",
      "23: Positive\n",
      "24: ExtremelyNegative\n",
      "25: ExtremelyNegative\n",
      "2986: MinorNegative\n",
      "30: MinorNegative\n",
      "300: ExtremelyNegative\n",
      "333: Negative\n",
      "334: Positive\n",
      "34: MinorNegative\n",
      "36: Positive\n",
      "386312: MinorNegative\n",
      "41: Negative\n",
      "410: MinorNegative\n",
      "43: Positive\n",
      "444: Negative\n",
      "444033: Negative\n",
      "45: ExtremelyNegative\n",
      "46: Negative\n",
      "50: MinorNegative\n",
      "5000: ExtremelyNegative\n",
      "507: MinorNegative\n",
      "5127: Positive\n",
      "532: Positive\n",
      "535637: Positive\n",
      "55: ExtremelyNegative\n",
      "576: Positive\n",
      "58: MinorNegative\n",
      "60: ExtremelyNegative\n",
      "610305: Neutral\n",
      "619: Positive\n",
      "630: VeryNegative\n",
      "640: Positive\n",
      "65: Positive\n",
      "656: MinorNegative\n",
      "68: MinorNegative\n",
      "686883: ExtremelyNegative\n",
      "69: MinorNegative\n",
      "694: Positive\n",
      "70: ExtremelyNegative\n",
      "71: Positive\n",
      "73: Positive\n",
      "77: Positive\n",
      "787: Positive\n",
      "94: MinorNegative\n",
      "ab: Positive\n",
      "abdull: ExtremelyNegative\n",
      "abi: VeryNegative\n",
      "about: ExtremelyNegative\n",
      "acil: Neutral\n",
      "acilen: ExtremelyNegative\n",
      "aciz: ExtremelyNegative\n",
      "acımak: ExtremelyNegative\n",
      "ad: VeryNegative\n",
      "ada: ExtremelyNegative\n",
      "adet: Positive\n",
      "adres: Negative\n",
      "adına: ExtremelyNegative\n",
      "afeder: Positive\n",
      "aidat: Negative\n",
      "ak: ExtremelyNegative\n",
      "akbank: MinorNegative\n",
      "akbaş: Neutral\n",
      "akra: MinorNegative\n",
      "akrep: ExtremelyNegative\n",
      "aksi: ExtremelyNegative\n",
      "aksu: Positive\n",
      "aktarm: ExtremelyNegative\n",
      "aktif: Neutral\n",
      "aktive: Positive\n",
      "akıllı: ExtremelyNegative\n",
      "akşam: Neutral\n",
      "al: Neutral\n",
      "ala: Negative\n",
      "alaka: Positive\n",
      "alaçam: Positive\n",
      "ali: ExtremelyNegative\n",
      "alkışl: ExtremelyNegative\n",
      "allah: VeryNegative\n",
      "almak: MinorNegative\n",
      "alo: Negative\n",
      "alper: MinorNegative\n",
      "alt: VeryNegative\n",
      "altern: Neutral\n",
      "altyap: ExtremelyNegative\n",
      "alçak: ExtremelyNegative\n",
      "alınma: Negative\n",
      "alışka: ExtremelyNegative\n",
      "alışve: MinorNegative\n",
      "amaç: VeryNegative\n",
      "ankara: Neutral\n",
      "anlam: Negative\n",
      "anlama: Neutral\n",
      "anlatm: Neutral\n",
      "anlayı: Negative\n",
      "anlaşm: Positive\n",
      "anne: Positive\n",
      "anında: Positive\n",
      "applic: ExtremelyNegative\n",
      "ar: ExtremelyNegative\n",
      "ara: Neutral\n",
      "aracı: ExtremelyNegative\n",
      "aracıl: Positive\n",
      "aramak: Neutral\n",
      "arami: ExtremelyNegative\n",
      "aranma: Negative\n",
      "araştı: VeryNegative\n",
      "arefe: Neutral\n",
      "arkada: MinorNegative\n",
      "artik: ExtremelyNegative\n",
      "artmak: VeryNegative\n",
      "arttır: ExtremelyNegative\n",
      "artçı: ExtremelyNegative\n",
      "artı: ExtremelyNegative\n",
      "artık: Negative\n",
      "artırı: Positive\n",
      "arz: MinorNegative\n",
      "arzu: MinorNegative\n",
      "arıza: Neutral\n",
      "aslî: Positive\n",
      "asıl: Positive\n",
      "at: ExtremelyNegative\n",
      "atamak: MinorNegative\n",
      "atatür: ExtremelyNegative\n",
      "ataşeh: ExtremelyNegative\n",
      "atm: Neutral\n",
      "atmak: MinorNegative\n",
      "atme: MinorNegative\n",
      "atmış: ExtremelyNegative\n",
      "ato: MinorNegative\n",
      "atrium: Negative\n",
      "avans: MinorNegative\n",
      "avanta: Neutral\n",
      "avm: ExtremelyNegative\n",
      "axess: Neutral\n",
      "ay: VeryNegative\n",
      "aylama: MinorNegative\n",
      "aylık: Negative\n",
      "aymak: Negative\n",
      "aynen: Neutral\n",
      "aynı: VeryNegative\n",
      "ayrıca: Neutral\n",
      "ayrılm: ExtremelyNegative\n",
      "ayıp: VeryNegative\n",
      "ayırma: ExtremelyNegative\n",
      "az: MinorNegative\n",
      "aç: Negative\n",
      "açmak: Negative\n",
      "açı: Positive\n",
      "açık: MinorNegative\n",
      "açıkla: Negative\n",
      "açıkça: Neutral\n",
      "ağaç: ExtremelyNegative\n",
      "ağır: Negative\n",
      "aşama: MinorNegative\n",
      "aşk: MinorNegative\n",
      "ba: Negative\n",
      "baba: ExtremelyNegative\n",
      "bahane: ExtremelyNegative\n",
      "bahis: MinorNegative\n",
      "bahset: Positive\n",
      "bakan: ExtremelyNegative\n",
      "baki: Positive\n",
      "bakiye: Negative\n",
      "bakmak: MinorNegative\n",
      "balçov: Positive\n",
      "bamya: Positive\n",
      "bank: ExtremelyNegative\n",
      "banka: Negative\n",
      "bankam: VeryNegative\n",
      "bara: Neutral\n",
      "barbar: Positive\n",
      "bari: VeryNegative\n",
      "bas: Positive\n",
      "basit: Negative\n",
      "batmak: ExtremelyNegative\n",
      "bayan: MinorNegative\n",
      "bayram: Neutral\n",
      "bağ: ExtremelyNegative\n",
      "bağlam: MinorNegative\n",
      "bağım: Positive\n",
      "baş: ExtremelyNegative\n",
      "başarm: ExtremelyNegative\n",
      "başarı: VeryPositive\n",
      "başbak: ExtremelyNegative\n",
      "başka: Neutral\n",
      "başlam: MinorNegative\n",
      "başlık: ExtremelyNegative\n",
      "başta: ExtremelyNegative\n",
      "başvur: MinorNegative\n",
      "be: Negative\n",
      "bebek: Positive\n",
      "beceri: ExtremelyNegative\n",
      "becerm: MinorNegative\n",
      "bedel: Negative\n",
      "bek: VeryPositive\n",
      "beklem: MinorNegative\n",
      "bekçi: ExtremelyNegative\n",
      "belirt: MinorNegative\n",
      "belli: Neutral\n",
      "ben: ExtremelyNegative\n",
      "bence: MinorNegative\n",
      "benzer: VeryPositive\n",
      "berabe: ExtremelyNegative\n",
      "berbat: ExtremelyNegative\n",
      "beri: Negative\n",
      "bey: VeryPositive\n",
      "beyan: Neutral\n",
      "bihabe: ExtremelyNegative\n",
      "bildik: ExtremelyNegative\n",
      "bildir: MinorNegative\n",
      "bile: Negative\n",
      "bileme: MinorNegative\n",
      "bilet: Neutral\n",
      "bilgi: Neutral\n",
      "bilgil: Neutral\n",
      "bili: ExtremelyNegative\n",
      "bilinç: ExtremelyNegative\n",
      "bilmek: MinorNegative\n",
      "bin: Negative\n",
      "bina: ExtremelyNegative\n",
      "bindir: VeryPositive\n",
      "bir: Negative\n",
      "biraz: Neutral\n",
      "birbir: Positive\n",
      "birden: Neutral\n",
      "birey: Positive\n",
      "bireys: ExtremelyNegative\n",
      "biri: Positive\n",
      "birikm: Neutral\n",
      "birlik: MinorNegative\n",
      "birşey: VeryNegative\n",
      "bitene: Positive\n",
      "bitirm: Negative\n",
      "bitmek: Negative\n",
      "biçim: VeryNegative\n",
      "blokla: ExtremelyNegative\n",
      "bm: MinorNegative\n",
      "bonus: Neutral\n",
      "borç: Negative\n",
      "boy: MinorNegative\n",
      "boyunc: Neutral\n",
      "bozdur: ExtremelyNegative\n",
      "bozmak: VeryNegative\n",
      "bozuk: MinorNegative\n",
      "bozulm: ExtremelyNegative\n",
      "boş: ExtremelyNegative\n",
      "boşuna: ExtremelyNegative\n",
      "br: VeryPositive\n",
      "brave: Positive\n",
      "bravo: ExtremelyNegative\n",
      "brunch: ExtremelyNegative\n",
      "bu: ExtremelyNegative\n",
      "bugün: MinorNegative\n",
      "buket: Positive\n",
      "bul: ExtremelyNegative\n",
      "bulama: Negative\n",
      "bulmak: Positive\n",
      "bulunm: MinorNegative\n",
      "bur: ExtremelyNegative\n",
      "bura: Neutral\n",
      "burada: Neutral\n",
      "burmak: ExtremelyNegative\n",
      "burs: ExtremelyNegative\n",
      "buçuk: ExtremelyNegative\n",
      "bölüm: MinorNegative\n",
      "bölünm: MinorNegative\n",
      "böyles: ExtremelyNegative\n",
      "bürokr: Negative\n",
      "büyük: MinorNegative\n",
      "büyütm: Neutral\n",
      "bıkmak: ExtremelyNegative\n",
      "bırakm: VeryNegative\n",
      "cadde: Positive\n",
      "campai: ExtremelyNegative\n",
      "can: Negative\n",
      "cari: MinorNegative\n",
      "cart: VeryPositive\n",
      "cc: VeryPositive\n",
      "ce: Positive\n",
      "center: Negative\n",
      "cep: Negative\n",
      "cevap: Negative\n",
      "cevapl: VeryPositive\n",
      "ceza: Negative\n",
      "chp: MinorNegative\n",
      "chuck: Neutral\n",
      "cihaz: Negative\n",
      "cinnet: VeryNegative\n",
      "cu: MinorNegative\n",
      "cuma: MinorNegative\n",
      "cumhur: ExtremelyNegative\n",
      "cüzdan: MinorNegative\n",
      "da: Positive\n",
      "dahası: ExtremelyNegative\n",
      "dair: MinorNegative\n",
      "dakika: MinorNegative\n",
      "dalga: ExtremelyNegative\n",
      "dan: Neutral\n",
      "danışm: Neutral\n",
      "davran: Positive\n",
      "ddk: ExtremelyNegative\n",
      "de: MinorNegative\n",
      "dediği: Negative\n",
      "deezer: Neutral\n",
      "defa: Negative\n",
      "defolm: VeryNegative\n",
      "dek: Neutral\n",
      "deli: ExtremelyNegative\n",
      "deme: Negative\n",
      "demek: Negative\n",
      "denizb: Neutral\n",
      "denmek: Negative\n",
      "derin: Positive\n",
      "dermek: MinorNegative\n",
      "dert: ExtremelyNegative\n",
      "destek: MinorNegative\n",
      "detay: ExtremelyNegative\n",
      "devam: Negative\n",
      "devlet: ExtremelyNegative\n",
      "değer: MinorNegative\n",
      "değil: Negative\n",
      "değilm: Neutral\n",
      "değişi: Neutral\n",
      "değişm: MinorNegative\n",
      "dide: Neutral\n",
      "digitü: Neutral\n",
      "dikkat: Neutral\n",
      "dil: ExtremelyNegative\n",
      "dilek: Negative\n",
      "dileme: VeryPositive\n",
      "dilmek: MinorNegative\n",
      "dink: ExtremelyNegative\n",
      "dinlem: ExtremelyNegative\n",
      "direk: Neutral\n",
      "direkt: Negative\n",
      "diye: ExtremelyNegative\n",
      "diğer: ExtremelyNegative\n",
      "dk: Negative\n",
      "dokuma: MinorNegative\n",
      "dokunm: ExtremelyNegative\n",
      "dokuz: ExtremelyNegative\n",
      "doland: VeryNegative\n",
      "doldur: Neutral\n",
      "dolmak: VeryPositive\n",
      "dost: ExtremelyNegative\n",
      "dosya: Neutral\n",
      "doğanc: VeryNegative\n",
      "doğru: Negative\n",
      "doğrus: Neutral\n",
      "dua: MinorNegative\n",
      "dur: ExtremelyNegative\n",
      "durmak: Negative\n",
      "durum: ExtremelyNegative\n",
      "duyarl: Positive\n",
      "duygu: ExtremelyNegative\n",
      "duymak: Neutral\n",
      "duyurm: Negative\n",
      "duyuru: Positive\n",
      "dâhi: Positive\n",
      "dâhil: Neutral\n",
      "dönem: Negative\n",
      "dönmek: Negative\n",
      "dönüşm: Positive\n",
      "döviz: ExtremelyNegative\n",
      "dük: ExtremelyNegative\n",
      "dümen: ExtremelyNegative\n",
      "dün: Neutral\n",
      "dünya: VeryNegative\n",
      "düzelm: Negative\n",
      "düzelt: Neutral\n",
      "düş: Positive\n",
      "düşman: MinorNegative\n",
      "düşmek: Neutral\n",
      "düşük: MinorNegative\n",
      "düşünm: Negative\n",
      "düşürm: Negative\n",
      "dış: MinorNegative\n",
      "ebe: ExtremelyNegative\n",
      "edi: ExtremelyNegative\n",
      "edil: ExtremelyNegative\n",
      "edinme: VeryPositive\n",
      "efe: Positive\n",
      "efendi: Negative\n",
      "ek: Neutral\n",
      "ekip: Positive\n",
      "ekleme: ExtremelyNegative\n",
      "ekran: Neutral\n",
      "eksi: Negative\n",
      "ekstre: Negative\n",
      "el: Negative\n",
      "elektr: MinorNegative\n",
      "elma: Positive\n",
      "emekli: Positive\n",
      "emin: Positive\n",
      "en: ExtremelyNegative\n",
      "enayi: ExtremelyNegative\n",
      "enfes: Positive\n",
      "engel: Positive\n",
      "enkaz: Neutral\n",
      "entere: Negative\n",
      "esen: VeryPositive\n",
      "eski: Neutral\n",
      "eskort: ExtremelyNegative\n",
      "esra: VeryPositive\n",
      "et: Negative\n",
      "etkile: Neutral\n",
      "etmek: MinorNegative\n",
      "etmen: Positive\n",
      "euro: ExtremelyNegative\n",
      "ev: VeryPositive\n",
      "evet: MinorNegative\n",
      "evvel: ExtremelyNegative\n",
      "exclamationmark: VeryNegative\n",
      "ezgi: Positive\n",
      "eğer: MinorNegative\n",
      "fahiş: ExtremelyNegative\n",
      "fail: Neutral\n",
      "faiz: MinorNegative\n",
      "faks: Positive\n",
      "fark: Neutral\n",
      "farket: Neutral\n",
      "fatura: MinorNegative\n",
      "fazla: Negative\n",
      "fazlas: Negative\n",
      "fed: Negative\n",
      "ferit: ExtremelyNegative\n",
      "fikir: VeryPositive\n",
      "firma: Neutral\n",
      "fiyat: ExtremelyNegative\n",
      "flex: VeryPositive\n",
      "follow: ExtremelyNegative\n",
      "fon: Negative\n",
      "fırsat: VeryNegative\n",
      "fırça: VeryNegative\n",
      "galata: Neutral\n",
      "garant: Negative\n",
      "gayet: Positive\n",
      "gaz: ExtremelyNegative\n",
      "gazete: ExtremelyNegative\n",
      "gece: Negative\n",
      "gecikm: MinorNegative\n",
      "gedi: ExtremelyNegative\n",
      "gedik: MinorNegative\n",
      "gele: ExtremelyNegative\n",
      "gelece: MinorNegative\n",
      "gelen: Negative\n",
      "gelişm: ExtremelyNegative\n",
      "gelmek: MinorNegative\n",
      "gelmiç: VeryNegative\n",
      "genel: VeryNegative\n",
      "genç: Neutral\n",
      "gerek: Neutral\n",
      "gerekl: MinorNegative\n",
      "gerekm: MinorNegative\n",
      "geri: Neutral\n",
      "gerize: ExtremelyNegative\n",
      "gerçek: MinorNegative\n",
      "geç: Negative\n",
      "geçen: Neutral\n",
      "geçici: Neutral\n",
      "geçilm: ExtremelyNegative\n",
      "geçinm: ExtremelyNegative\n",
      "geçirm: VeryNegative\n",
      "geçişt: Negative\n",
      "geçmek: Negative\n",
      "gibi: Neutral\n",
      "gibisi: MinorNegative\n",
      "giderm: Negative\n",
      "gine: ExtremelyNegative\n",
      "girmek: MinorNegative\n",
      "gitmek: MinorNegative\n",
      "gizli: ExtremelyNegative\n",
      "gişe: ExtremelyNegative\n",
      "grip: Positive\n",
      "gönder: MinorNegative\n",
      "gönül: VeryPositive\n",
      "göre: Neutral\n",
      "görev: VeryNegative\n",
      "görmek: Negative\n",
      "görünm: Negative\n",
      "görünt: ExtremelyNegative\n",
      "görüş: Positive\n",
      "görüşm: Positive\n",
      "göster: MinorNegative\n",
      "götürm: ExtremelyNegative\n",
      "göz: VeryNegative\n",
      "göztep: ExtremelyNegative\n",
      "gözükm: MinorNegative\n",
      "gü: Neutral\n",
      "gün: MinorNegative\n",
      "güncel: MinorNegative\n",
      "günde: Negative\n",
      "gündem: ExtremelyNegative\n",
      "gündüz: Positive\n",
      "günlem: ExtremelyNegative\n",
      "güve: ExtremelyNegative\n",
      "güvenl: VeryNegative\n",
      "güvenm: ExtremelyNegative\n",
      "güzel: Negative\n",
      "güç: ExtremelyNegative\n",
      "ha: MinorNegative\n",
      "haber: Negative\n",
      "hacı: MinorNegative\n",
      "had: ExtremelyNegative\n",
      "hadi: MinorNegative\n",
      "haf: MinorNegative\n",
      "hafta: MinorNegative\n",
      "haftas: Negative\n",
      "hak: MinorNegative\n",
      "hakem: Negative\n",
      "hakkın: MinorNegative\n",
      "hal: Negative\n",
      "hallet: Positive\n",
      "hamil: VeryNegative\n",
      "han: Positive\n",
      "hangis: VeryPositive\n",
      "hanım: Positive\n",
      "haraç: MinorNegative\n",
      "harcam: MinorNegative\n",
      "hareke: MinorNegative\n",
      "hariç: ExtremelyNegative\n",
      "has: ExtremelyNegative\n",
      "hassas: VeryPositive\n",
      "hasta: Negative\n",
      "hasır: ExtremelyNegative\n",
      "hat: Negative\n",
      "hata: Neutral\n",
      "hatice: VeryPositive\n",
      "hatırl: MinorNegative\n",
      "hava: Neutral\n",
      "havale: Negative\n",
      "havali: ExtremelyNegative\n",
      "hayal: ExtremelyNegative\n",
      "hayat: ExtremelyNegative\n",
      "hayhay: ExtremelyNegative\n",
      "hayran: Positive\n",
      "hayır: MinorNegative\n",
      "hazır: MinorNegative\n",
      "hele: Positive\n",
      "hemen: Positive\n",
      "hep: Neutral\n",
      "hergün: ExtremelyNegative\n",
      "herhan: Neutral\n",
      "herhâl: MinorNegative\n",
      "heryer: ExtremelyNegative\n",
      "herşey: MinorNegative\n",
      "hesap: Negative\n",
      "hesapl: MinorNegative\n",
      "heyet: Negative\n",
      "hizmet: Negative\n",
      "hiç: ExtremelyNegative\n",
      "hiçbir: ExtremelyNegative\n",
      "hiçbiş: ExtremelyNegative\n",
      "hoş: VeryPositive\n",
      "huzur: ExtremelyNegative\n",
      "hâlen: MinorNegative\n",
      "hâlâ: Negative\n",
      "hız: Neutral\n",
      "hızlan: VeryPositive\n",
      "hızlı: VeryPositive\n",
      "iade: MinorNegative\n",
      "ibare: Neutral\n",
      "ibaret: ExtremelyNegative\n",
      "iflâs: ExtremelyNegative\n",
      "ihbar: VeryPositive\n",
      "ihtar: ExtremelyNegative\n",
      "ihtima: ExtremelyNegative\n",
      "ihtiya: MinorNegative\n",
      "ikinci: ExtremelyNegative\n",
      "il: MinorNegative\n",
      "ileti: Negative\n",
      "iletiş: MinorNegative\n",
      "iletme: MinorNegative\n",
      "ilgi: Positive\n",
      "ilgile: MinorNegative\n",
      "ilişki: VeryNegative\n",
      "ilk: ExtremelyNegative\n",
      "illet: MinorNegative\n",
      "illâ: VeryNegative\n",
      "ilçe: ExtremelyNegative\n",
      "imek: Neutral\n",
      "inadın: ExtremelyNegative\n",
      "ince: MinorNegative\n",
      "indirm: ExtremelyNegative\n",
      "inmek: Positive\n",
      "insaf: Negative\n",
      "insan: Negative\n",
      "inşall: MinorNegative\n",
      "iptal: Negative\n",
      "irtiba: Negative\n",
      "is: MinorNegative\n",
      "isim: MinorNegative\n",
      "ispat: ExtremelyNegative\n",
      "istek: Negative\n",
      "isteme: MinorNegative\n",
      "ister: MinorNegative\n",
      "istirh: ExtremelyNegative\n",
      "itibar: Neutral\n",
      "itiraz: Neutral\n",
      "iyi: Neutral\n",
      "iz: Negative\n",
      "izah: ExtremelyNegative\n",
      "izin: VeryNegative\n",
      "iç: Negative\n",
      "içeri: Neutral\n",
      "için: VeryPositive\n",
      "içmek: ExtremelyNegative\n",
      "içtenl: VeryPositive\n",
      "iş: Negative\n",
      "işlem: Neutral\n",
      "işleti: Negative\n",
      "kabul: Positive\n",
      "kadar: Neutral\n",
      "kaf: ExtremelyNegative\n",
      "kafa: ExtremelyNegative\n",
      "kahram: Positive\n",
      "kaldır: Positive\n",
      "kalite: VeryNegative\n",
      "kalkma: ExtremelyNegative\n",
      "kalmak: MinorNegative\n",
      "kalın: VeryNegative\n",
      "kampan: Negative\n",
      "kan: ExtremelyNegative\n",
      "kana: ExtremelyNegative\n",
      "kanal: Neutral\n",
      "kapalı: MinorNegative\n",
      "kapanm: MinorNegative\n",
      "kapatm: Negative\n",
      "kapı: VeryNegative\n",
      "kara: Neutral\n",
      "karar: Negative\n",
      "kardeş: MinorNegative\n",
      "kargo: VeryPositive\n",
      "karmak: Negative\n",
      "kart: MinorNegative\n",
      "karşı: MinorNegative\n",
      "karşıl: ExtremelyNegative\n",
      "kas: Neutral\n",
      "kasım: ExtremelyNegative\n",
      "kasıt: Negative\n",
      "kat: MinorNegative\n",
      "katı: Negative\n",
      "katılm: ExtremelyNegative\n",
      "kavram: VeryNegative\n",
      "kaybet: Negative\n",
      "kaybol: Neutral\n",
      "kaymak: MinorNegative\n",
      "kayıt: ExtremelyNegative\n",
      "kazanç: ExtremelyNegative\n",
      "kaçta: ExtremelyNegative\n",
      "kedi: ExtremelyNegative\n",
      "keklic: ExtremelyNegative\n",
      "kemerk: Positive\n",
      "kendi: Neutral\n",
      "ker: Negative\n",
      "kesin: VeryPositive\n",
      "kesinl: ExtremelyNegative\n",
      "kesmek: Negative\n",
      "kez: Negative\n",
      "kezban: MinorNegative\n",
      "keşke: ExtremelyNegative\n",
      "ki: Negative\n",
      "kilit: Neutral\n",
      "kilitl: ExtremelyNegative\n",
      "kim: MinorNegative\n",
      "kimse: Negative\n",
      "king: Neutral\n",
      "kings: Neutral\n",
      "kiş: Negative\n",
      "kişi: ExtremelyNegative\n",
      "kk: Neutral\n",
      "kktc: Neutral\n",
      "ko: MinorNegative\n",
      "kocama: ExtremelyNegative\n",
      "kod: MinorNegative\n",
      "kol: ExtremelyNegative\n",
      "kolay: MinorNegative\n",
      "kolayl: Neutral\n",
      "komisy: ExtremelyNegative\n",
      "komple: ExtremelyNegative\n",
      "kontro: Neutral\n",
      "kontör: MinorNegative\n",
      "konu: Neutral\n",
      "konuşm: Negative\n",
      "kopya: Neutral\n",
      "koruma: ExtremelyNegative\n",
      "kot: Positive\n",
      "kovmak: VeryNegative\n",
      "koymak: Negative\n",
      "kredi: MinorNegative\n",
      "kriz: ExtremelyNegative\n",
      "kulak: ExtremelyNegative\n",
      "kullan: MinorNegative\n",
      "kulüp: Positive\n",
      "kumbar: VeryPositive\n",
      "kur: VeryNegative\n",
      "kurban: Neutral\n",
      "kurtar: ExtremelyNegative\n",
      "kurtul: Negative\n",
      "kuru: MinorNegative\n",
      "kuruş: MinorNegative\n",
      "kurye: MinorNegative\n",
      "kuryen: ExtremelyNegative\n",
      "kusur: Negative\n",
      "kutlam: MinorNegative\n",
      "kuzen: MinorNegative\n",
      "köklü: ExtremelyNegative\n",
      "köprü: Positive\n",
      "kötü: ExtremelyNegative\n",
      "küfür: ExtremelyNegative\n",
      "küp: VeryPositive\n",
      "küçük: ExtremelyNegative\n",
      "küçülm: Neutral\n",
      "kıpmak: MinorNegative\n",
      "kır: ExtremelyNegative\n",
      "kırık: ExtremelyNegative\n",
      "kısa: Neutral\n",
      "kıvanç: ExtremelyNegative\n",
      "kıvrak: Negative\n",
      "kıymet: ExtremelyNegative\n",
      "kız: VeryPositive\n",
      "la: MinorNegative\n",
      "laf: MinorNegative\n",
      "lahana: ExtremelyNegative\n",
      "lakin: MinorNegative\n",
      "lan: ExtremelyNegative\n",
      "lazım: Positive\n",
      "limit: Negative\n",
      "link: MinorNegative\n",
      "lira: VeryNegative\n",
      "lise: Neutral\n",
      "list: ExtremelyNegative\n",
      "liste: Negative\n",
      "lokasy: VeryPositive\n",
      "los: Neutral\n",
      "lumia: Positive\n",
      "lütfen: Neutral\n",
      "maales: Neutral\n",
      "maaş: Negative\n",
      "mafya: ExtremelyNegative\n",
      "mah: Positive\n",
      "mahke: MinorNegative\n",
      "mahkem: ExtremelyNegative\n",
      "mail: MinorNegative\n",
      "mal: ExtremelyNegative\n",
      "maltep: Positive\n",
      "malum: ExtremelyNegative\n",
      "mangır: ExtremelyNegative\n",
      "mantık: ExtremelyNegative\n",
      "marife: MinorNegative\n",
      "market: Negative\n",
      "mart: ExtremelyNegative\n",
      "maslak: VeryPositive\n",
      "masraf: MinorNegative\n",
      "mazere: ExtremelyNegative\n",
      "mağdur: Negative\n",
      "meb: MinorNegative\n",
      "mecbur: ExtremelyNegative\n",
      "mecidi: Positive\n",
      "medya: Positive\n",
      "mehmet: Positive\n",
      "mekik: MinorNegative\n",
      "mektup: ExtremelyNegative\n",
      "memnun: Positive\n",
      "memur: ExtremelyNegative\n",
      "menü: ExtremelyNegative\n",
      "merak: VeryNegative\n",
      "merhab: Neutral\n",
      "merkez: Negative\n",
      "mesai: Neutral\n",
      "mesaj: MinorNegative\n",
      "mesel: MinorNegative\n",
      "mesele: Negative\n",
      "meselâ: Positive\n",
      "mesut: VeryPositive\n",
      "mevcut: ExtremelyNegative\n",
      "mevdua: ExtremelyNegative\n",
      "meyve: Neutral\n",
      "meşgul: Negative\n",
      "mi: MinorNegative\n",
      "miktar: Positive\n",
      "mil: MinorNegative\n",
      "miles: Positive\n",
      "millet: ExtremelyNegative\n",
      "milâs: Positive\n",
      "mis: Neutral\n",
      "mobil: Neutral\n",
      "mod: ExtremelyNegative\n",
      "moment: Negative\n",
      "mother: Neutral\n",
      "ms: MinorNegative\n",
      "mu: ExtremelyNegative\n",
      "muamel: ExtremelyNegative\n",
      "muhata: ExtremelyNegative\n",
      "mukabi: ExtremelyNegative\n",
      "murat: Positive\n",
      "mus: MinorNegative\n",
      "mutsuz: Negative\n",
      "muş: MinorNegative\n",
      "müdür: VeryNegative\n",
      "mümkün: Neutral\n",
      "müsait: Neutral\n",
      "müzik: ExtremelyNegative\n",
      "müşter: Negative\n",
      "mı: Neutral\n",
      "nakit: Neutral\n",
      "nasıl: Neutral\n",
      "nasıls: ExtremelyNegative\n",
      "ne: Negative\n",
      "neden: Positive\n",
      "nedens: ExtremelyNegative\n",
      "nefes: ExtremelyNegative\n",
      "negativesmiley: Negative\n",
      "nekada: VeryPositive\n",
      "nerede: VeryNegative\n",
      "net: Positive\n",
      "ney: ExtremelyNegative\n",
      "nokta: Positive\n",
      "normal: MinorNegative\n",
      "not: Neutral\n",
      "now: ExtremelyNegative\n",
      "nsa: Positive\n",
      "nter: Positive\n",
      "ntern: Positive\n",
      "numara: MinorNegative\n",
      "nüfus: Negative\n",
      "odak: VeryPositive\n",
      "ofer: Neutral\n",
      "ofis: ExtremelyNegative\n",
      "okumak: VeryNegative\n",
      "olabil: Neutral\n",
      "olacak: MinorNegative\n",
      "olasıl: MinorNegative\n",
      "olay: Neutral\n",
      "oldu: Negative\n",
      "oldukç: VeryPositive\n",
      "olmadı: MinorNegative\n",
      "olmak: MinorNegative\n",
      "olmaz: MinorNegative\n",
      "olumlu: MinorNegative\n",
      "olumsu: MinorNegative\n",
      "olur: Neutral\n",
      "oluşma: Neutral\n",
      "oluşum: Neutral\n",
      "on: ExtremelyNegative\n",
      "onay: Negative\n",
      "onayla: Negative\n",
      "onca: MinorNegative\n",
      "online: Neutral\n",
      "ons: VeryPositive\n",
      "onu: ExtremelyNegative\n",
      "operat: Neutral\n",
      "or: MinorNegative\n",
      "ora: Negative\n",
      "oradan: Neutral\n",
      "oral: ExtremelyNegative\n",
      "oran: ExtremelyNegative\n",
      "orman: Negative\n",
      "orta: VeryPositive\n",
      "ortak: ExtremelyNegative\n",
      "ortala: ExtremelyNegative\n",
      "osurma: Negative\n",
      "otomat: MinorNegative\n",
      "oturma: Negative\n",
      "oy: ExtremelyNegative\n",
      "oyun: Positive\n",
      "pa: ExtremelyNegative\n",
      "paket: ExtremelyNegative\n",
      "par: Negative\n",
      "para: Negative\n",
      "paraca: MinorNegative\n",
      "parama: Negative\n",
      "pardo: ExtremelyNegative\n",
      "parmak: ExtremelyNegative\n",
      "parola: Positive\n",
      "parti: Negative\n",
      "parça: ExtremelyNegative\n",
      "parçal: MinorNegative\n",
      "patron: ExtremelyNegative\n",
      "paylaş: MinorNegative\n",
      "pazar: Positive\n",
      "pazart: Neutral\n",
      "peki: VeryPositive\n",
      "perhiz: ExtremelyNegative\n",
      "person: MinorNegative\n",
      "perşem: Positive\n",
      "peş: VeryNegative\n",
      "peşin: MinorNegative\n",
      "pir: Positive\n",
      "platfo: Neutral\n",
      "platin: ExtremelyNegative\n",
      "positivesmiley: Positive\n",
      "premiu: Neutral\n",
      "proble: Neutral\n",
      "profil: VeryNegative\n",
      "progra: ExtremelyNegative\n",
      "promos: Neutral\n",
      "protes: ExtremelyNegative\n",
      "psikol: ExtremelyNegative\n",
      "puan: Neutral\n",
      "pürüz: VeryPositive\n",
      "questionmark: MinorNegative\n",
      "rahat: Negative\n",
      "rakam: Neutral\n",
      "rapor: Neutral\n",
      "reddol: ExtremelyNegative\n",
      "reflü: MinorNegative\n",
      "reklâm: Negative\n",
      "renk: ExtremelyNegative\n",
      "resmen: MinorNegative\n",
      "resmî: MinorNegative\n",
      "ret: MinorNegative\n",
      "reva: ExtremelyNegative\n",
      "rezale: Negative\n",
      "rezil: VeryNegative\n",
      "rica: Neutral\n",
      "robot: ExtremelyNegative\n",
      "ruhsat: Positive\n",
      "saat: Neutral\n",
      "saatle: Negative\n",
      "sabah: MinorNegative\n",
      "sabaht: ExtremelyNegative\n",
      "sabri: ExtremelyNegative\n",
      "sabırl: VeryPositive\n",
      "sadece: Negative\n",
      "saha: ExtremelyNegative\n",
      "sahip: MinorNegative\n",
      "sallam: ExtremelyNegative\n",
      "sanal: MinorNegative\n",
      "sanki: ExtremelyNegative\n",
      "sanmak: Negative\n",
      "sarıye: ExtremelyNegative\n",
      "satmak: Negative\n",
      "satış: Positive\n",
      "savcı: Positive\n",
      "savsak: Negative\n",
      "sayama: ExtremelyNegative\n",
      "saye: ExtremelyNegative\n",
      "sayfa: MinorNegative\n",
      "saygı: VeryNegative\n",
      "saymak: ExtremelyNegative\n",
      "sayı: ExtremelyNegative\n",
      "sayın: Negative\n",
      "saçma: Negative\n",
      "sağlam: Positive\n",
      "sağlık: MinorNegative\n",
      "sağmak: MinorNegative\n",
      "sağolm: Positive\n",
      "sbs: Positive\n",
      "se: Negative\n",
      "sebep: Negative\n",
      "sefer: MinorNegative\n",
      "sel: ExtremelyNegative\n",
      "sele: ExtremelyNegative\n",
      "self: ExtremelyNegative\n",
      "sema: Neutral\n",
      "semt: VeryPositive\n",
      "sene: Neutral\n",
      "serry: Neutral\n",
      "ses: Positive\n",
      "sesli: VeryNegative\n",
      "sevgi: Negative\n",
      "sevinm: Positive\n",
      "seçmek: ExtremelyNegative\n",
      "sigar: ExtremelyNegative\n",
      "sigort: ExtremelyNegative\n",
      "sikke: Neutral\n",
      "silmek: ExtremelyNegative\n",
      "sinirl: ExtremelyNegative\n",
      "sirkec: MinorNegative\n",
      "sistem: Negative\n",
      "site: Positive\n",
      "sitem: ExtremelyNegative\n",
      "siz: Negative\n",
      "sizsin: Negative\n",
      "slim: MinorNegative\n",
      "sol: VeryPositive\n",
      "solmak: MinorNegative\n",
      "sonlan: Negative\n",
      "sonra: Negative\n",
      "sonsuz: VeryPositive\n",
      "sonund: ExtremelyNegative\n",
      "sonuç: MinorNegative\n",
      "sonuçl: Positive\n",
      "sor: Neutral\n",
      "sormak: MinorNegative\n",
      "soru: Positive\n",
      "soruma: Negative\n",
      "soruml: ExtremelyNegative\n",
      "sorun: MinorNegative\n",
      "sosyal: Positive\n",
      "soyad: Positive\n",
      "soygun: VeryNegative\n",
      "soğuma: Positive\n",
      "specia: Neutral\n",
      "standa: ExtremelyNegative\n",
      "su: Positive\n",
      "surat: VeryNegative\n",
      "suç: Positive\n",
      "swift: Neutral\n",
      "sövmek: ExtremelyNegative\n",
      "söylem: MinorNegative\n",
      "söz: MinorNegative\n",
      "süper: VeryPositive\n",
      "süre: MinorNegative\n",
      "sürekl: ExtremelyNegative\n",
      "süreç: Neutral\n",
      "sürmek: MinorNegative\n",
      "sıfır: ExtremelyNegative\n",
      "sıkı: ExtremelyNegative\n",
      "sınıf: ExtremelyNegative\n",
      "sınır: VeryNegative\n",
      "sır: Negative\n",
      "sıra: ExtremelyNegative\n",
      "sırada: ExtremelyNegative\n",
      "sırf: ExtremelyNegative\n",
      "sığmak: ExtremelyNegative\n",
      "t1: Positive\n",
      "ta: MinorNegative\n",
      "taa: Negative\n",
      "tabiî: ExtremelyNegative\n",
      "taciz: ExtremelyNegative\n",
      "tahakk: ExtremelyNegative\n",
      "tahrik: ExtremelyNegative\n",
      "tahsil: Negative\n",
      "tak: ExtremelyNegative\n",
      "takdir: Positive\n",
      "takip: Neutral\n",
      "taksit: MinorNegative\n",
      "taktik: MinorNegative\n",
      "talep: Negative\n",
      "talima: Negative\n",
      "tam: Negative\n",
      "tamam: Positive\n",
      "tamame: ExtremelyNegative\n",
      "tamaml: ExtremelyNegative\n",
      "tane: ExtremelyNegative\n",
      "tanyer: MinorNegative\n",
      "tanıml: Neutral\n",
      "taraf: Negative\n",
      "tarafı: Neutral\n",
      "tarihî: Negative\n",
      "tarz: VeryNegative\n",
      "tasarl: ExtremelyNegative\n",
      "tatbik: MinorNegative\n",
      "tatil: Neutral\n",
      "tatlı: ExtremelyNegative\n",
      "tavsiy: Neutral\n",
      "tazmin: ExtremelyNegative\n",
      "taşıma: ExtremelyNegative\n",
      "te: Neutral\n",
      "tebrik: Positive\n",
      "tefeci: ExtremelyNegative\n",
      "tehdit: ExtremelyNegative\n",
      "tehir: ExtremelyNegative\n",
      "tehlik: ExtremelyNegative\n",
      "teiaş: Positive\n",
      "tek: Neutral\n",
      "teklif: ExtremelyNegative\n",
      "teknik: Positive\n",
      "tekrar: Positive\n",
      "tel: Negative\n",
      "telefo: MinorNegative\n",
      "telese: Neutral\n",
      "tem: ExtremelyNegative\n",
      "tembel: Negative\n",
      "tembih: VeryNegative\n",
      "temsil: MinorNegative\n",
      "tesekk: VeryPositive\n",
      "teslim: MinorNegative\n",
      "teşekk: Positive\n",
      "the: ExtremelyNegative\n",
      "this: Neutral\n",
      "ti: Positive\n",
      "tip: ExtremelyNegative\n",
      "tl: Negative\n",
      "tobb: ExtremelyNegative\n",
      "toplam: VeryNegative\n",
      "total: ExtremelyNegative\n",
      "trabzo: Neutral\n",
      "transf: MinorNegative\n",
      "tufan: Positive\n",
      "tuhaf: MinorNegative\n",
      "tura: Positive\n",
      "turkey: ExtremelyNegative\n",
      "turşu: ExtremelyNegative\n",
      "tutar: Neutral\n",
      "tutmak: ExtremelyNegative\n",
      "tuğba: MinorNegative\n",
      "tuş: Neutral\n",
      "tv: ExtremelyNegative\n",
      "tweet: MinorNegative\n",
      "tweete: ExtremelyNegative\n",
      "twitte: Positive\n",
      "tüketm: Negative\n",
      "türki: ExtremelyNegative\n",
      "türlü: MinorNegative\n",
      "tıkmak: ExtremelyNegative\n",
      "tıp: ExtremelyNegative\n",
      "ufacık: MinorNegative\n",
      "ula: ExtremelyNegative\n",
      "ulamak: Negative\n",
      "ulaşma: MinorNegative\n",
      "ulaşım: Neutral\n",
      "umar: Negative\n",
      "ummak: Positive\n",
      "umut: Negative\n",
      "usb: MinorNegative\n",
      "utanma: VeryPositive\n",
      "uyarma: ExtremelyNegative\n",
      "uyarı: Neutral\n",
      "uyduru: MinorNegative\n",
      "uygula: Negative\n",
      "uygun: Positive\n",
      "uymak: ExtremelyNegative\n",
      "uzatma: MinorNegative\n",
      "uzay: ExtremelyNegative\n",
      "uzun: VeryNegative\n",
      "uğraş: ExtremelyNegative\n",
      "uğraşm: VeryPositive\n",
      "vaat: VeryNegative\n",
      "vade: MinorNegative\n",
      "vakit: Negative\n",
      "var: MinorNegative\n",
      "varmak: VeryPositive\n",
      "vatand: ExtremelyNegative\n",
      "ve: ExtremelyNegative\n",
      "vergi: MinorNegative\n",
      "vermek: MinorNegative\n",
      "vicdan: ExtremelyNegative\n",
      "wall: Negative\n",
      "we: Positive\n",
      "web: MinorNegative\n",
      "window: Neutral\n",
      "yaa: VeryPositive\n",
      "yaaa: ExtremelyNegative\n",
      "yabanc: ExtremelyNegative\n",
      "yahu: ExtremelyNegative\n",
      "yak: ExtremelyNegative\n",
      "yaka: VeryNegative\n",
      "yaklaş: Positive\n",
      "yakın: MinorNegative\n",
      "yalan: ExtremelyNegative\n",
      "yan: Negative\n",
      "yanlış: MinorNegative\n",
      "yansım: Positive\n",
      "yanılm: VeryNegative\n",
      "yanıt: VeryNegative\n",
      "yanıtl: Negative\n",
      "yapmak: MinorNegative\n",
      "yapı: Negative\n",
      "yapıla: Neutral\n",
      "yapışm: Negative\n",
      "yarama: ExtremelyNegative\n",
      "yarar: ExtremelyNegative\n",
      "yard: Neutral\n",
      "yardım: MinorNegative\n",
      "yarmak: MinorNegative\n",
      "yarım: Negative\n",
      "yarın: Positive\n",
      "yarışm: Positive\n",
      "yasa: MinorNegative\n",
      "yasak: ExtremelyNegative\n",
      "yasal: ExtremelyNegative\n",
      "yatırm: Positive\n",
      "yava: ExtremelyNegative\n",
      "yavşak: ExtremelyNegative\n",
      "yaz: ExtremelyNegative\n",
      "yazar: Positive\n",
      "yazmak: Neutral\n",
      "yazı: ExtremelyNegative\n",
      "yazık: ExtremelyNegative\n",
      "yağlı: ExtremelyNegative\n",
      "yaş: Positive\n",
      "yaşama: MinorNegative\n",
      "yemek: ExtremelyNegative\n",
      "yeni: Negative\n",
      "yenide: VeryNegative\n",
      "yenike: Positive\n",
      "yenile: MinorNegative\n",
      "yer: Negative\n",
      "yeter: Negative\n",
      "yeteri: ExtremelyNegative\n",
      "yeterl: MinorNegative\n",
      "yetişm: Positive\n",
      "yetki: Neutral\n",
      "yetmek: VeryNegative\n",
      "yeşil: ExtremelyNegative\n",
      "ygs: Negative\n",
      "yirmi: ExtremelyNegative\n",
      "yiyici: ExtremelyNegative\n",
      "yok: Negative\n",
      "yol: Negative\n",
      "yollam: Negative\n",
      "yorum: MinorNegative\n",
      "you: ExtremelyNegative\n",
      "yoğ: ExtremelyNegative\n",
      "yoğun: MinorNegative\n",
      "yumak: ExtremelyNegative\n",
      "yurt: Positive\n",
      "yurtdı: Neutral\n",
      "yuvarl: ExtremelyNegative\n",
      "yâd: Neutral\n",
      "yâr: ExtremelyNegative\n",
      "yöneti: ExtremelyNegative\n",
      "yönetm: ExtremelyNegative\n",
      "yönlen: Neutral\n",
      "yüklem: MinorNegative\n",
      "yüklü: Neutral\n",
      "yürüme: ExtremelyNegative\n",
      "yürütm: ExtremelyNegative\n",
      "yüz: Neutral\n",
      "yüzünd: Negative\n",
      "yıl: MinorNegative\n",
      "yılbaş: ExtremelyNegative\n",
      "yılmak: ExtremelyNegative\n",
      "yırtma: Negative\n",
      "zaman: Neutral\n",
      "zan: ExtremelyNegative\n",
      "zana: Positive\n",
      "zarar: ExtremelyNegative\n",
      "zekâ: Negative\n",
      "zor: Negative\n",
      "zorunl: ExtremelyNegative\n",
      "âciz: ExtremelyNegative\n",
      "âmâ: Negative\n",
      "çabuk: VeryPositive\n",
      "çaktır: ExtremelyNegative\n",
      "çalmak: MinorNegative\n",
      "çalışa: Positive\n",
      "çalışm: MinorNegative\n",
      "çare: ExtremelyNegative\n",
      "çarşam: Positive\n",
      "çaycıl: ExtremelyNegative\n",
      "çağ: Positive\n",
      "çağrı: MinorNegative\n",
      "çek: ExtremelyNegative\n",
      "çekeme: ExtremelyNegative\n",
      "çekilm: ExtremelyNegative\n",
      "çekinm: MinorNegative\n",
      "çekme: Positive\n",
      "çekmek: Negative\n",
      "çevirm: Positive\n",
      "çeyrek: Neutral\n",
      "çifte: ExtremelyNegative\n",
      "çorlu: MinorNegative\n",
      "çökmek: ExtremelyNegative\n",
      "çöz: Positive\n",
      "çözmek: MinorNegative\n",
      "çözüml: Neutral\n",
      "çıkarm: MinorNegative\n",
      "çıkmak: MinorNegative\n",
      "çıkmaz: Positive\n",
      "çıldır: ExtremelyNegative\n",
      "ödemek: Negative\n",
      "ödenme: Negative\n",
      "öldürm: ExtremelyNegative\n",
      "ölmek: ExtremelyNegative\n",
      "ölüm: ExtremelyNegative\n",
      "ömer: Positive\n",
      "ömür: ExtremelyNegative\n",
      "ön: ExtremelyNegative\n",
      "önceli: ExtremelyNegative\n",
      "önem: Positive\n",
      "öner: Positive\n",
      "önerme: MinorNegative\n",
      "örnek: VeryPositive\n",
      "öte: VeryPositive\n",
      "öze: MinorNegative\n",
      "özel: Negative\n",
      "özelli: Neutral\n",
      "özet: Positive\n",
      "özkes: Positive\n",
      "öğle: Neutral\n",
      "öğrenc: Negative\n",
      "öğrenm: Neutral\n",
      "ücret: MinorNegative\n",
      "ülke: ExtremelyNegative\n",
      "ün: Negative\n",
      "üretme: VeryPositive\n",
      "ürün: ExtremelyNegative\n",
      "üsküda: Positive\n",
      "üslup: VeryPositive\n",
      "üst: MinorNegative\n",
      "üsteli: ExtremelyNegative\n",
      "üstüne: Negative\n",
      "üye: MinorNegative\n",
      "üzer: Neutral\n",
      "üzerin: Neutral\n",
      "üzüntü: ExtremelyNegative\n",
      "üç: ExtremelyNegative\n",
      "ısrar: Positive\n",
      "şahenk: ExtremelyNegative\n",
      "şahsen: Positive\n",
      "şaka: MinorNegative\n",
      "şans: Positive\n",
      "şaşkın: Neutral\n",
      "şaşırm: Positive\n",
      "şefik: Positive\n",
      "şekil: Neutral\n",
      "şeref: ExtremelyNegative\n",
      "şiddet: ExtremelyNegative\n",
      "şifre: Neutral\n",
      "şiir: ExtremelyNegative\n",
      "şikâye: Negative\n",
      "şimdi: MinorNegative\n",
      "şimdid: VeryPositive\n",
      "şimdil: Negative\n",
      "şirket: VeryNegative\n",
      "şişmek: ExtremelyNegative\n",
      "şua: Positive\n",
      "şube: MinorNegative\n",
      "şut: Neutral\n",
      "şükür: ExtremelyNegative\n",
      "şüphe: ExtremelyNegative\n"
     ]
    }
   ],
   "source": [
    "for word in word_sentiment_dictionary:\n",
    "    print(word + \": \" + word_sentiment_dictionary[word])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "training_data_bucket_feature_extractor = BucketFeatureExtractor(word_sentiment_dictionary,\n",
    "                                                                features_to_bucketize,\n",
    "                                                                sentence_list,\n",
    "                                                                score_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 0.          0.          0.         ...,  0.          0.         -0.13056261]\n",
      " [ 0.          0.          0.         ...,  0.          0.         -0.37153547]\n",
      " [ 1.          0.          0.         ...,  0.          0.         -0.2648446 ]\n",
      " ..., \n",
      " [ 0.          0.          0.         ...,  2.          2.         -0.68920274]\n",
      " [ 0.          1.          0.         ...,  0.          0.         -0.53967993]\n",
      " [ 0.          0.          0.         ...,  0.          1.         -0.41639407]]\n"
     ]
    }
   ],
   "source": [
    "training_data_extracted_features_x = training_data_bucket_feature_extractor.extract_features()\n",
    "training_data_extracted_features_x = numpy.array(training_data_extracted_features_x)\n",
    "print(training_data_extracted_features_x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 1.          0.          0.         ...,  0.          0.         -0.37644361]\n",
      " [ 0.          0.          0.         ...,  0.          0.         -0.03146927]\n",
      " [ 0.          0.          0.         ...,  0.          0.         -0.24430867]\n",
      " ..., \n",
      " [ 0.          0.          0.         ...,  1.          0.         -0.44360345]\n",
      " [ 0.          0.          0.         ...,  0.          0.          0.06276042]\n",
      " [ 0.          0.          0.         ...,  0.          0.         -0.23870191]]\n"
     ]
    }
   ],
   "source": [
    "# Feature Extraction for the Test Data using the Buckets and pre-processed data\n",
    "\n",
    "test_data_bucket_feature_extractor = BucketFeatureExtractor(word_sentiment_dictionary,\n",
    "                                                            features_to_bucketize,\n",
    "                                                            test_sentence_list,\n",
    "                                                            test_score_list)\n",
    "\n",
    "test_data_extracted_features_x = test_data_bucket_feature_extractor.extract_features()\n",
    "test_data_extracted_features_x = numpy.array(test_data_extracted_features_x)\n",
    "print(test_data_extracted_features_x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1.        ,  0.        ,  0.        , ...,  0.        ,\n",
       "         0.        , -0.37644361],\n",
       "       [ 0.        ,  0.        ,  0.        , ...,  0.        ,\n",
       "         0.        , -0.03146927],\n",
       "       [ 0.        ,  0.        ,  0.        , ...,  0.        ,\n",
       "         0.        , -0.24430867],\n",
       "       ..., \n",
       "       [ 0.        ,  0.        ,  0.        , ...,  1.        ,\n",
       "         0.        , -0.44360345],\n",
       "       [ 0.        ,  0.        ,  0.        , ...,  0.        ,\n",
       "         0.        ,  0.06276042],\n",
       "       [ 0.        ,  0.        ,  0.        , ...,  0.        ,\n",
       "         0.        , -0.23870191]])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data_extracted_features_x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decision Tree Regression score: -0.0311006708616\n"
     ]
    }
   ],
   "source": [
    "# Decision Tree Regression\n",
    "\n",
    "decision_tree_regressor = tree.DecisionTreeRegressor(max_depth=7, min_samples_leaf=17)\n",
    "decision_tree_regressor.fit(training_data_extracted_features_x, score_array)\n",
    "\n",
    "# Test Decision Tree Regression on Test Data\n",
    "\n",
    "print('Decision Tree Regression score: '\n",
    "      + str(decision_tree_regressor.score(test_data_extracted_features_x, test_score_array)))\n",
    "# Score: -0.759753880839\n",
    "# After adjusting values, score improved, but still very bad. Score: -0.193423357515\n",
    "\n",
    "# Get Feature Importances of Decision Tree\n",
    "\n",
    "# print(decision_tree_regressor.feature_importances_)\n",
    "\n",
    "# Try Regression based on k-nearest neighbors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "K-Nearest Neighbours Regression score: 0.211669259898\n"
     ]
    }
   ],
   "source": [
    "# Try Regression based on k-nearest neighbors.\n",
    "\n",
    "k_nearest_neighbors_regressor = neighbors.KNeighborsRegressor(n_neighbors=248, p=1)\n",
    "k_nearest_neighbors_regressor.fit(training_data_extracted_features_x, score_array)\n",
    "\n",
    "# Test K-Nearest Neighbours Regression on Test Data\n",
    "\n",
    "print('K-Nearest Neighbours Regression score: '\n",
    "      + str(k_nearest_neighbors_regressor.score(test_data_extracted_features_x, test_score_array)))\n",
    "# Score: -0.0961322606566\n",
    "# When I changed n_neighbors from default of 5 to 248 score increased dramatically\n",
    "# Changing algorithms didn't have anny effect\n",
    "# Score: 0.129813702549\n",
    "# When I changed p to 1 from the default value of 2, score increased again\n",
    "# Score: 0.161999595131"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Support Vector Machine Regressor Score: 0.277475962127\n"
     ]
    }
   ],
   "source": [
    "# Try Support Vector Machine Regression\n",
    "\n",
    "support_vector_machine_regressor = svm.SVR(kernel='linear', epsilon=0.2)\n",
    "support_vector_machine_regressor.fit(training_data_extracted_features_x, score_array)\n",
    "\n",
    "# Test Support Vector Machine Regression on Test Data\n",
    "\n",
    "print('Support Vector Machine Regressor Score: '\n",
    "      + str(support_vector_machine_regressor.score(test_data_extracted_features_x, test_score_array)))\n",
    "# Score: -0.101547661324\n",
    "# after changing the kernel to 'linear', score improved.\n",
    "# Score: 0.117806253477\n",
    "# after changing epsilon value to 0.2, score improved again\n",
    "# Score: 0.133648477067\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stochastic Gradient Descent Regressor Score: 0.258230410913\n"
     ]
    }
   ],
   "source": [
    "# Try Stochastic Gradient Descent Regression\n",
    "\n",
    "stochastic_gradient_descent_regressor = linear_model.SGDRegressor(tol=0.01)\n",
    "stochastic_gradient_descent_regressor.fit(training_data_extracted_features_x, score_array)\n",
    "\n",
    "# Test Stochastic Gradient Descent Regression on Test Data\n",
    "\n",
    "print('Stochastic Gradient Descent Regressor Score: '\n",
    "      + str(stochastic_gradient_descent_regressor.score(test_data_extracted_features_x, test_score_array)))\n",
    "# Score: 0.176217008989"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Random Forests Regressor score: -0.00112699961601\n"
     ]
    }
   ],
   "source": [
    "# Try Random Forests Regression\n",
    "\n",
    "random_forests_regressor = ensemble.RandomForestRegressor(max_depth=7, min_samples_leaf=17)\n",
    "random_forests_regressor.fit(training_data_extracted_features_x, score_array)\n",
    "\n",
    "# Test Random Forest Regression on Test Data\n",
    "\n",
    "print('Random Forests Regressor score: ' + str(random_forests_regressor.score(test_data_extracted_features_x,\n",
    "                                                                              test_score_array)))\n",
    "# Score: -0.334794427196\n",
    "# After changing parameters, score improved but still very bad\n",
    "# Score: -0.193607366878"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Multi-layer Perceptron score: 0.239079436605\n"
     ]
    }
   ],
   "source": [
    "# Try Multi-layer Perceptron Regression\n",
    "\n",
    "multi_layer_perceptron_regressor = neural_network.MLPRegressor(solver='sgd')\n",
    "multi_layer_perceptron_regressor.fit(training_data_extracted_features_x, score_array)\n",
    "\n",
    "# Test Multi-layer Perceptron on Test Data\n",
    "\n",
    "print('Multi-layer Perceptron score: ' + str(multi_layer_perceptron_regressor.score(test_data_extracted_features_x,\n",
    "                                                                                    test_score_array)))\n",
    "# Score: 0.00620729465159\n",
    "# It got a lot better after I changed to solver to 'sgd': stochastic gradient descent.\n",
    "# Score: 0.154938217153"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recursive Feature Selection score. 0.226363259055\n"
     ]
    }
   ],
   "source": [
    "# Try Recursive Feature Selection\n",
    "estimator = svm.SVR(kernel=\"linear\")\n",
    "recursive_feature_selection = feature_selection.RFE(estimator)\n",
    "recursive_feature_selection.fit(training_data_extracted_features_x, score_array)\n",
    "\n",
    "# Test Recursive Feature Selection on Test Data\n",
    "\n",
    "print('Recursive Feature Selection score. ' + str(recursive_feature_selection.score(test_data_extracted_features_x,\n",
    "                                                                                    test_score_array)))\n",
    "# Score: 0.0631286115014"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ridge Regressor score: 0.296883000765\n"
     ]
    }
   ],
   "source": [
    "# Try Ridge Regression\n",
    "\n",
    "ridge_regressor = linear_model.Ridge(solver='auto', normalize=True)\n",
    "ridge_regressor.fit(training_data_extracted_features_x, score_array)\n",
    "\n",
    "# Test Rigde Regression on Test Data\n",
    "\n",
    "print('Ridge Regressor score: ' + str(ridge_regressor.score(test_data_extracted_features_x, test_score_array)))\n",
    "# Score: 0.140327821678\n",
    "# It slightly improved when I changed the solver to saga (Stochastic Average Gradient Descent)\n",
    "# When I turned on normalize ,after changing the solver to saga, score improved; however before that, it didn't help.\n",
    "# Score: 0.191242391892"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Todo: Merge features from the Excel file with the generated features\n",
    "# Todo: Run all the Regressors and Classifiers with the dataset containing combined features\n",
    "# Todo: Try Naive Bayes Classifiers from the Scikit Learn\n",
    "# Todo: (Gaussian Naive Bayes, Multinomial Naive Bayes, Bernoulli Naive Bayes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "trainExcelFileName = 'train21-Onlyfeatures.xlsx'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "trainExcel = pd.ExcelFile(trainExcelFileName)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Bank_Train']\n"
     ]
    }
   ],
   "source": [
    "print(trainExcel.sheet_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "Traindf = trainExcel.parse('Bank_Train')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['F1', 'F2', 'F3', 'F4', 'F5', 'F6', 'F7', 'F8', 'F9', 'F10', 'F11',\n",
       "       'F12', 'F13', 'F14', 'F15', 'F16', 'F17', 'F18', 'F19', 'F20', 'F21'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Traindf.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
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       "      <th>F21</th>\n",
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       "  </thead>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.422500</td>\n",
       "      <td>0.734000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.436667</td>\n",
       "      <td>0.920000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>-0.231702</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.364286</td>\n",
       "      <td>0.907500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-0.126504</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.432000</td>\n",
       "      <td>0.926667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>-0.136235</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.448000</td>\n",
       "      <td>0.835385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>-0.098392</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.436667</td>\n",
       "      <td>0.896667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.386000</td>\n",
       "      <td>0.902500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.126504</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.428000</td>\n",
       "      <td>0.877500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>-0.194622</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.359000</td>\n",
       "      <td>0.834545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>-0.151630</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.425714</td>\n",
       "      <td>0.784000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>-0.137533</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.408000</td>\n",
       "      <td>0.844545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>-0.247258</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.426000</td>\n",
       "      <td>0.863000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>-0.195506</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.455000</td>\n",
       "      <td>0.904000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>-0.217165</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.452500</td>\n",
       "      <td>0.764286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>-0.222340</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.436667</td>\n",
       "      <td>0.885000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>-0.143371</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.437500</td>\n",
       "      <td>0.886667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>-0.253008</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.372222</td>\n",
       "      <td>0.876000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.005390</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.472500</td>\n",
       "      <td>0.866667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>-0.221382</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.335714</td>\n",
       "      <td>0.798889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>-0.112448</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.415000</td>\n",
       "      <td>0.896667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>-0.197971</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.426667</td>\n",
       "      <td>0.790000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>-0.139154</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.488000</td>\n",
       "      <td>0.796667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.084336</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.394286</td>\n",
       "      <td>0.894000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>-0.171316</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.384444</td>\n",
       "      <td>0.885556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>-0.161137</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.348750</td>\n",
       "      <td>0.820000</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",
       "      <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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>727</th>\n",
       "      <td>-0.151805</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.447273</td>\n",
       "      <td>0.902000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>728</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.430000</td>\n",
       "      <td>0.824286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>729</th>\n",
       "      <td>-0.063252</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.440000</td>\n",
       "      <td>0.860000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>730</th>\n",
       "      <td>-0.253008</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.450000</td>\n",
       "      <td>0.895000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>731</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.448000</td>\n",
       "      <td>0.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>732</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.436667</td>\n",
       "      <td>0.885000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>733</th>\n",
       "      <td>0.101203</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.476000</td>\n",
       "      <td>0.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>734</th>\n",
       "      <td>-0.038924</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.414545</td>\n",
       "      <td>0.801818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>735</th>\n",
       "      <td>-0.253008</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.436667</td>\n",
       "      <td>0.920000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>736</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.450000</td>\n",
       "      <td>0.920000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>737</th>\n",
       "      <td>0.126504</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.452500</td>\n",
       "      <td>0.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>738</th>\n",
       "      <td>-0.050602</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.452500</td>\n",
       "      <td>0.811429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>739</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.436667</td>\n",
       "      <td>0.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>740</th>\n",
       "      <td>-0.126504</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.386000</td>\n",
       "      <td>0.893333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>741</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.444286</td>\n",
       "      <td>0.903333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>742</th>\n",
       "      <td>-0.069002</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.407500</td>\n",
       "      <td>0.840000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>743</th>\n",
       "      <td>-0.042168</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.408333</td>\n",
       "      <td>0.854286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>744</th>\n",
       "      <td>-0.063252</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.386667</td>\n",
       "      <td>0.885000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>745</th>\n",
       "      <td>0.090360</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.442727</td>\n",
       "      <td>0.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>746</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.435000</td>\n",
       "      <td>0.767500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>747</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.436667</td>\n",
       "      <td>0.885000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>748</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.436667</td>\n",
       "      <td>0.885000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>749</th>\n",
       "      <td>0.058386</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.420000</td>\n",
       "      <td>0.844545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>750</th>\n",
       "      <td>0.136235</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.404000</td>\n",
       "      <td>0.822857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>751</th>\n",
       "      <td>-0.253008</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.436667</td>\n",
       "      <td>0.920000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752</th>\n",
       "      <td>-0.168672</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.370000</td>\n",
       "      <td>0.922500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>753</th>\n",
       "      <td>0.084336</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.441667</td>\n",
       "      <td>0.880000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>754</th>\n",
       "      <td>-0.077849</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.367692</td>\n",
       "      <td>0.864545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.377500</td>\n",
       "      <td>0.793333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>756</th>\n",
       "      <td>-0.189756</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.515000</td>\n",
       "      <td>0.850000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>757 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           F1   F2   F3   F4   F5   F6   F7    F8   F9  F10    ...     F12  \\\n",
       "0    0.104344  0.0  0.0  0.0  0.0  0.0  0.0   6.0  1.0  0.0    ...     0.0   \n",
       "1   -0.199180  0.0  0.0  0.0  0.0  2.0  0.0   7.0  4.0  0.0    ...     0.0   \n",
       "2   -0.237453  0.0  0.0  0.0  0.0  1.0  0.0   7.0  2.0  0.0    ...     0.0   \n",
       "3   -0.201703  0.0  0.0  0.0  0.0  4.0  0.0   8.0  1.0  0.0    ...     0.0   \n",
       "4   -0.227058  0.0  0.0  0.0  0.0  0.0  0.0   5.0  1.0  0.0    ...     0.0   \n",
       "5   -0.253008  0.0  0.0  0.0  0.0  0.0  0.0   2.0  0.0  0.0    ...     0.0   \n",
       "6    0.000000  0.0  0.0  1.0  1.0  0.0  0.0   0.0  0.0  0.0    ...     0.0   \n",
       "7   -0.231702  0.0  0.0  0.0  0.0  1.0  0.0   3.0  1.0  0.0    ...     0.0   \n",
       "8   -0.126504  0.0  0.0  1.0  1.0  0.0  0.0   3.0  0.0  0.0    ...     0.0   \n",
       "9   -0.136235  0.0  0.0  1.0  1.0  1.0  0.0   8.0  4.0  0.0    ...     0.0   \n",
       "10  -0.098392  0.0  0.0  0.0  0.0  0.0  0.0   1.0  1.0  0.0    ...     0.0   \n",
       "11   0.000000  0.0  0.0  0.0  0.0  0.0  0.0   2.0  0.0  0.0    ...     0.0   \n",
       "12   0.126504  0.0  0.0  0.0  0.0  0.0  0.0   1.0  0.0  2.0    ...     0.0   \n",
       "13  -0.194622  0.0  0.0  0.0  0.0  1.0  0.0   9.0  2.0  0.0    ...     0.0   \n",
       "14  -0.151630  0.0  0.0  0.0  0.0  0.0  0.0   2.0  2.0  0.0    ...     0.0   \n",
       "15  -0.137533  0.0  0.0  0.0  0.0  0.0  0.0  10.0  3.0  0.0    ...     0.0   \n",
       "16  -0.247258  0.0  0.0  0.0  0.0  0.0  0.0   3.0  3.0  0.0    ...     0.0   \n",
       "17  -0.195506  0.0  0.0  0.0  0.0  1.0  0.0   4.0  1.0  0.0    ...     0.0   \n",
       "18  -0.217165  0.0  0.0  0.0  0.0  0.0  0.0   6.0  3.0  0.0    ...     0.0   \n",
       "19  -0.222340  0.0  0.0  0.0  0.0  0.0  0.0   0.0  1.0  0.0    ...     0.0   \n",
       "20  -0.143371  0.0  0.0  0.0  0.0  0.0  0.0   8.0  5.0  0.0    ...     0.0   \n",
       "21  -0.253008  0.0  0.0  0.0  0.0  1.0  0.0   3.0  3.0  0.0    ...     0.0   \n",
       "22   0.005390  0.0  0.0  0.0  0.0  0.0  0.0   9.0  4.0  0.0    ...     0.0   \n",
       "23  -0.221382  0.0  0.0  0.0  0.0  0.0  0.0   2.0  3.0  4.0    ...     0.0   \n",
       "24  -0.112448  0.0  0.0  0.0  0.0  0.0  0.0   2.0  2.0  0.0    ...     0.0   \n",
       "25  -0.197971  0.0  0.0  0.0  0.0  0.0  0.0   5.0  4.0  3.0    ...     0.0   \n",
       "26  -0.139154  0.0  0.0  0.0  0.0  1.0  0.0   1.0  3.0  0.0    ...     0.0   \n",
       "27   0.084336  0.0  0.0  0.0  0.0  0.0  0.0   4.0  1.0  0.0    ...     0.0   \n",
       "28  -0.171316  0.0  0.0  0.0  0.0  0.0  0.0   9.0  3.0  0.0    ...     0.0   \n",
       "29  -0.161137  0.0  0.0  0.0  0.0  0.0  0.0   4.0  3.0  0.0    ...     0.0   \n",
       "..        ...  ...  ...  ...  ...  ...  ...   ...  ...  ...    ...     ...   \n",
       "727 -0.151805  0.0  0.0  0.0  0.0  1.0  0.0   6.0  2.0  0.0    ...     0.0   \n",
       "728  0.000000  0.0  0.0  0.0  0.0  0.0  0.0   4.0  1.0  0.0    ...     0.0   \n",
       "729 -0.063252  0.0  0.0  0.0  0.0  0.0  0.0   2.0  2.0  0.0    ...     0.0   \n",
       "730 -0.253008  0.0  0.0  0.0  0.0  0.0  0.0   1.0  0.0  0.0    ...     0.0   \n",
       "731  0.000000  0.0  0.0  0.0  0.0  0.0  0.0   3.0  2.0  0.0    ...     0.0   \n",
       "732  0.000000  0.0  0.0  0.0  0.0  0.0  0.0   1.0  1.0  0.0    ...     0.0   \n",
       "733  0.101203  1.0  2.0  0.0  0.0  1.0  0.0   3.0  1.0  0.0    ...     0.0   \n",
       "734 -0.038924  0.0  0.0  0.0  0.0  0.0  0.0   5.0  6.0  0.0    ...     0.0   \n",
       "735 -0.253008  0.0  0.0  0.0  0.0  0.0  0.0   0.0  1.0  0.0    ...     0.0   \n",
       "736  0.000000  0.0  0.0  0.0  0.0  0.0  0.0   1.0  1.0  0.0    ...     0.0   \n",
       "737  0.126504  1.0  1.0  0.0  0.0  0.0  0.0   1.0  0.0  0.0    ...     0.0   \n",
       "738 -0.050602  0.0  0.0  0.0  0.0  0.0  0.0   5.0  4.0  0.0    ...     0.0   \n",
       "739  0.000000  0.0  0.0  0.0  0.0  0.0  0.0   0.0  1.0  0.0    ...     0.0   \n",
       "740 -0.126504  0.0  0.0  0.0  0.0  0.0  0.0   4.0  1.0  0.0    ...     0.0   \n",
       "741  0.000000  0.0  0.0  0.0  0.0  1.0  0.0   5.0  0.0  0.0    ...     0.0   \n",
       "742 -0.069002  0.0  0.0  0.0  0.0  0.0  0.0   3.0  4.0  0.0    ...     0.0   \n",
       "743 -0.042168  0.0  0.0  0.0  0.0  0.0  0.0   4.0  0.0  0.0    ...     0.0   \n",
       "744 -0.063252  0.0  0.0  0.0  0.0  0.0  0.0   2.0  2.0  0.0    ...     0.0   \n",
       "745  0.090360  1.0  1.0  0.0  0.0  1.0  0.0   6.0  5.0  0.0    ...     1.0   \n",
       "746  0.000000  0.0  0.0  0.0  0.0  1.0  0.0   1.0  1.0  0.0    ...     0.0   \n",
       "747  0.000000  0.0  0.0  0.0  0.0  0.0  0.0   0.0  1.0  0.0    ...     0.0   \n",
       "748  0.000000  0.0  0.0  0.0  0.0  0.0  0.0   0.0  1.0  0.0    ...     0.0   \n",
       "749  0.058386  0.0  0.0  0.0  0.0  0.0  0.0   9.0  2.0  0.0    ...     0.0   \n",
       "750  0.136235  0.0  0.0  0.0  0.0  0.0  0.0   7.0  5.0  0.0    ...     0.0   \n",
       "751 -0.253008  1.0  1.0  0.0  0.0  0.0  0.0   1.0  0.0  0.0    ...     0.0   \n",
       "752 -0.168672  1.0  1.0  0.0  0.0  0.0  0.0   2.0  1.0  0.0    ...     0.0   \n",
       "753  0.084336  0.0  0.0  0.0  0.0  0.0  0.0   4.0  0.0  0.0    ...     0.0   \n",
       "754 -0.077849  0.0  0.0  0.0  0.0  2.0  0.0   7.0  1.0  0.0    ...     0.0   \n",
       "755  0.000000  0.0  0.0  0.0  0.0  0.0  0.0   1.0  1.0  1.0    ...     0.0   \n",
       "756 -0.189756  0.0  0.0  0.0  0.0  0.0  0.0   4.0  1.0  0.0    ...     0.0   \n",
       "\n",
       "     F13  F14  F15  F16  F17   F18   F19       F20       F21  \n",
       "0    0.0  0.0  0.0  0.0  1.0   5.0   7.0  0.424286  0.880000  \n",
       "1    0.0  0.0  0.0  0.0  1.0  13.0  13.0  0.421538  0.897692  \n",
       "2    0.0  0.0  0.0  0.0  1.0   6.0   9.0  0.411111  0.833333  \n",
       "3    1.0  0.0  0.0  0.0  1.0  10.0  14.0  0.375714  0.845000  \n",
       "4    0.0  0.0  0.0  0.0  1.0   7.0   5.0  0.390000  0.834286  \n",
       "5    0.0  0.0  0.0  0.0  1.0   5.0   8.0  0.422500  0.734000  \n",
       "6    0.0  0.0  0.0  0.0  1.0   1.0   3.0  0.436667  0.920000  \n",
       "7    0.0  0.0  0.0  0.0  1.0   4.0   7.0  0.364286  0.907500  \n",
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       "16   0.0  0.0  0.0  0.0  1.0  10.0   5.0  0.426000  0.863000  \n",
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       "18   0.0  0.0  0.0  0.0  1.0   7.0   4.0  0.452500  0.764286  \n",
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       "24   0.0  0.0  0.0  0.0  1.0   6.0   4.0  0.415000  0.896667  \n",
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       "26   0.0  0.0  0.0  0.0  1.0   6.0   5.0  0.488000  0.796667  \n",
       "27   0.0  0.0  0.0  0.0  1.0   5.0   7.0  0.394286  0.894000  \n",
       "28   0.0  0.0  0.0  0.0  1.0   9.0   9.0  0.384444  0.885556  \n",
       "29   0.0  0.0  0.0  0.0  1.0   4.0   8.0  0.348750  0.820000  \n",
       "..   ...  ...  ...  ...  ...   ...   ...       ...       ...  \n",
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       "728  0.0  0.0  0.0  0.0  1.0   7.0   6.0  0.430000  0.824286  \n",
       "729  0.0  0.0  0.0  0.0  1.0   6.0   6.0  0.440000  0.860000  \n",
       "730  0.0  0.0  0.0  0.0  1.0   2.0   4.0  0.450000  0.895000  \n",
       "731  0.0  0.0  0.0  0.0  1.0   2.0   5.0  0.448000  0.900000  \n",
       "732  0.0  0.0  0.0  0.0  1.0   2.0   3.0  0.436667  0.885000  \n",
       "733  0.0  0.0  0.0  0.0  1.0   3.0   5.0  0.476000  0.800000  \n",
       "734  0.0  0.0  0.0  0.0  1.0  11.0  11.0  0.414545  0.801818  \n",
       "735  0.0  0.0  0.0  0.0  1.0   2.0   3.0  0.436667  0.920000  \n",
       "736  0.0  0.0  0.0  0.0  1.0   1.0   4.0  0.450000  0.920000  \n",
       "737  0.0  0.0  0.0  0.0  1.0   2.0   4.0  0.452500  0.900000  \n",
       "738  0.0  0.0  0.0  0.0  1.0   7.0   4.0  0.452500  0.811429  \n",
       "739  0.0  0.0  0.0  0.0  1.0   3.0   3.0  0.436667  0.800000  \n",
       "740  0.0  0.0  0.0  0.0  1.0   6.0   5.0  0.386000  0.893333  \n",
       "741  0.0  0.0  0.0  0.0  1.0   6.0   7.0  0.444286  0.903333  \n",
       "742  0.0  0.0  0.0  0.0  1.0   8.0   8.0  0.407500  0.840000  \n",
       "743  0.0  0.0  0.0  0.0  1.0   7.0   6.0  0.408333  0.854286  \n",
       "744  0.0  0.0  0.0  0.0  1.0   2.0   6.0  0.386667  0.885000  \n",
       "745  0.0  0.0  0.0  0.0  1.0  11.0  11.0  0.442727  0.900000  \n",
       "746  0.0  0.0  0.0  0.0  1.0   4.0   4.0  0.435000  0.767500  \n",
       "747  0.0  0.0  0.0  0.0  1.0   2.0   3.0  0.436667  0.885000  \n",
       "748  0.0  0.0  0.0  0.0  1.0   2.0   3.0  0.436667  0.885000  \n",
       "749  0.0  0.0  0.0  0.0  1.0  11.0  10.0  0.420000  0.844545  \n",
       "750  0.0  0.0  0.0  0.0  1.0   7.0  10.0  0.404000  0.822857  \n",
       "751  0.0  0.0  0.0  0.0  1.0   1.0   3.0  0.436667  0.920000  \n",
       "752  0.0  1.0  0.0  0.0  1.0   4.0   5.0  0.370000  0.922500  \n",
       "753  0.0  0.0  0.0  0.0  1.0   4.0   6.0  0.441667  0.880000  \n",
       "754  0.0  0.0  0.0  0.0  1.0  11.0  13.0  0.367692  0.864545  \n",
       "755  0.0  0.0  0.0  0.0  1.0   3.0   4.0  0.377500  0.793333  \n",
       "756  0.0  0.0  0.0  0.0  1.0   8.0   8.0  0.515000  0.850000  \n",
       "\n",
       "[757 rows x 21 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Traindf.astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "trainExcelNPArray = Traindf.as_matrix()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "trainAllFeatures=numpy.hstack((trainExcelNPArray,training_data_extracted_features_x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(757, 33)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trainAllFeatures.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "testExcelFileName = 'test-21-Onlyfeatures.xlsx'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "testExcel = pd.ExcelFile(testExcelFileName)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Bank_Test']\n"
     ]
    }
   ],
   "source": [
    "print(testExcel.sheet_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "Testdf = testExcel.parse('Bank_Test')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "      <td>8.833333e-01</td>\n",
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       "    <tr>\n",
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       "      <td>-0.001278</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
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       "      <td>5.0</td>\n",
       "      <td>0.476000</td>\n",
       "      <td>8.875000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>-0.151805</td>\n",
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       "      <td>1.0</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>8.600000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>-0.045831</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.490000</td>\n",
       "      <td>8.933333e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>-0.077117</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.428889</td>\n",
       "      <td>9.071429e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>-0.214084</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.436667</td>\n",
       "      <td>8.525000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>-0.090669</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.444286</td>\n",
       "      <td>8.725000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>-0.024644</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.436000</td>\n",
       "      <td>8.966667e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>-0.121269</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.397500</td>\n",
       "      <td>8.637500e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>-0.116962</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.342857</td>\n",
       "      <td>8.192308e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.012569</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.425714</td>\n",
       "      <td>8.000000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>-0.115419</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.395000</td>\n",
       "      <td>8.290000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>-0.143258</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.394286</td>\n",
       "      <td>8.455556e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>-0.162648</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.412500</td>\n",
       "      <td>8.480000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>-0.163396</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.363750</td>\n",
       "      <td>8.200000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>-0.202600</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.353636</td>\n",
       "      <td>8.550000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>-0.091866</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.403750</td>\n",
       "      <td>8.175000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>-0.102959</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.345000</td>\n",
       "      <td>8.322222e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>-0.065471</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.406250</td>\n",
       "      <td>8.814286e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.377500</td>\n",
       "      <td>9.033333e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>-0.127927</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.442857</td>\n",
       "      <td>8.710000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>-0.102699</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.471000</td>\n",
       "      <td>8.200000e-01</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",
       "      <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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>-0.096013</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.434444</td>\n",
       "      <td>1.494865e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>-0.115018</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.464286</td>\n",
       "      <td>7.837500e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>-0.079152</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.373750</td>\n",
       "      <td>9.025000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>-0.110025</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>8.200000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.386667</td>\n",
       "      <td>8.300000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>-0.069878</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.450000</td>\n",
       "      <td>7.600000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>-0.044276</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.455714</td>\n",
       "      <td>8.140000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>-0.101906</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.438333</td>\n",
       "      <td>8.500000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>-0.194622</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.450000</td>\n",
       "      <td>9.000000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.436667</td>\n",
       "      <td>9.200000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>-0.222340</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.436667</td>\n",
       "      <td>8.850000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>-0.027328</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.505294</td>\n",
       "      <td>8.108333e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>-0.047771</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.436667</td>\n",
       "      <td>8.925000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>-0.177468</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.502500</td>\n",
       "      <td>7.963636e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>-0.102225</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.407143</td>\n",
       "      <td>8.612500e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>-0.094878</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.415000</td>\n",
       "      <td>8.775000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>-0.158656</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.385714</td>\n",
       "      <td>1.494865e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>-0.134554</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.418000</td>\n",
       "      <td>9.200000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>-0.063891</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.437500</td>\n",
       "      <td>9.200000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>-0.119476</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.373333</td>\n",
       "      <td>8.144444e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>0.023939</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.400909</td>\n",
       "      <td>8.814286e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>-0.150679</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.425000</td>\n",
       "      <td>8.512500e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>-0.114299</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.386364</td>\n",
       "      <td>7.684615e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>0.134411</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.386000</td>\n",
       "      <td>9.025000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>-0.165052</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.373077</td>\n",
       "      <td>9.100000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>-0.097589</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.490000</td>\n",
       "      <td>8.850000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.467500</td>\n",
       "      <td>8.950000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>-0.084336</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.450000</td>\n",
       "      <td>8.570000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>-0.029901</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.392000</td>\n",
       "      <td>8.875000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>-0.068533</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.433636</td>\n",
       "      <td>6.272173e+12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           F1   F2   F3   F4   F5   F6   F7    F8   F9  F10      ...       \\\n",
       "0   -0.105420  0.0  0.0  0.0  0.0  0.0  0.0   4.0  3.0  0.0      ...        \n",
       "1   -0.089180  0.0  0.0  0.0  0.0  2.0  0.0   6.0  2.0  0.0      ...        \n",
       "2   -0.107677  0.0  0.0  0.0  0.0  0.0  0.0   4.0  3.0  0.0      ...        \n",
       "3    0.000000  0.0  0.0  0.0  0.0  0.0  0.0   0.0  0.0  0.0      ...        \n",
       "4   -0.084884  0.0  0.0  0.0  0.0  0.0  0.0   7.0  2.0  0.0      ...        \n",
       "5   -0.148431  0.0  0.0  0.0  0.0  0.0  0.0   2.0  0.0  0.0      ...        \n",
       "6   -0.075902  0.0  0.0  0.0  0.0  1.0  0.0   0.0  2.0  0.0      ...        \n",
       "7   -0.093208  0.0  0.0  0.0  0.0  1.0  0.0   8.0  6.0  0.0      ...        \n",
       "8   -0.119604  0.0  0.0  0.0  0.0  0.0  0.0  10.0  0.0  1.0      ...        \n",
       "9   -0.001278  0.0  0.0  0.0  0.0  1.0  0.0   1.0  1.0  0.0      ...        \n",
       "10  -0.151805  1.0  1.0  0.0  0.0  0.0  0.0   2.0  2.0  0.0      ...        \n",
       "11  -0.045831  1.0  1.0  0.0  0.0  0.0  0.0   3.0  2.0  0.0      ...        \n",
       "12  -0.077117  0.0  0.0  0.0  0.0  0.0  0.0   7.0  3.0  0.0      ...        \n",
       "13  -0.214084  0.0  0.0  0.0  0.0  0.0  0.0   2.0  0.0  0.0      ...        \n",
       "14  -0.090669  0.0  0.0  0.0  0.0  1.0  0.0   2.0  6.0  0.0      ...        \n",
       "15  -0.024644  0.0  0.0  0.0  0.0  0.0  0.0   1.0  3.0  0.0      ...        \n",
       "16  -0.121269  0.0  0.0  0.0  0.0  0.0  0.0   7.0  4.0  0.0      ...        \n",
       "17  -0.116962  0.0  0.0  0.0  0.0  0.0  0.0   9.0  2.0  0.0      ...        \n",
       "18   0.012569  0.0  0.0  0.0  0.0  0.0  0.0   3.0  1.0  0.0      ...        \n",
       "19  -0.115419  0.0  0.0  0.0  0.0  0.0  0.0   7.0  4.0  0.0      ...        \n",
       "20  -0.143258  0.0  0.0  0.0  0.0  3.0  0.0   8.0  2.0  0.0      ...        \n",
       "21  -0.162648  0.0  0.0  0.0  0.0  0.0  0.0   3.0  2.0  0.0      ...        \n",
       "22  -0.163396  0.0  0.0  0.0  0.0  0.0  0.0   8.0  3.0  3.0      ...        \n",
       "23  -0.202600  0.0  0.0  0.0  0.0  0.0  0.0   9.0  3.0  1.0      ...        \n",
       "24  -0.091866  0.0  0.0  0.0  0.0  0.0  0.0   3.0  2.0  0.0      ...        \n",
       "25  -0.102959  0.0  0.0  0.0  0.0  0.0  0.0  10.0  4.0  0.0      ...        \n",
       "26  -0.065471  0.0  0.0  0.0  0.0  1.0  0.0   5.0  2.0  0.0      ...        \n",
       "27   0.000000  0.0  0.0  0.0  0.0  0.0  0.0   0.0  1.0  0.0      ...        \n",
       "28  -0.127927  0.0  0.0  0.0  0.0  0.0  0.0   7.0  4.0  1.0      ...        \n",
       "29  -0.102699  0.0  0.0  0.0  0.0  1.0  0.0   7.0  3.0  0.0      ...        \n",
       "..        ...  ...  ...  ...  ...  ...  ...   ...  ...  ...      ...        \n",
       "170 -0.096013  0.0  0.0  0.0  0.0  2.0  0.0   7.0  2.0  1.0      ...        \n",
       "171 -0.115018  0.0  0.0  0.0  0.0  1.0  0.0   8.0  1.0  0.0      ...        \n",
       "172 -0.079152  0.0  0.0  0.0  0.0  0.0  0.0   8.0  1.0  0.0      ...        \n",
       "173 -0.110025  0.0  0.0  0.0  0.0  0.0  0.0   7.0  3.0  0.0      ...        \n",
       "174  0.000000  1.0  1.0  0.0  0.0  0.0  0.0   2.0  1.0  0.0      ...        \n",
       "175 -0.069878  0.0  0.0  1.0  1.0  0.0  0.0   1.0  0.0  0.0      ...        \n",
       "176 -0.044276  0.0  0.0  0.0  0.0  1.0  0.0   6.0  3.0  0.0      ...        \n",
       "177 -0.101906  0.0  0.0  0.0  0.0  0.0  0.0   7.0  3.0  0.0      ...        \n",
       "178 -0.194622  0.0  0.0  0.0  0.0  0.0  0.0   1.0  0.0  0.0      ...        \n",
       "179  0.000000  0.0  0.0  0.0  0.0  0.0  0.0   0.0  0.0  0.0      ...        \n",
       "180 -0.222340  0.0  0.0  0.0  0.0  0.0  0.0   0.0  1.0  0.0      ...        \n",
       "181 -0.027328  0.0  0.0  0.0  0.0  0.0  0.0  11.0  2.0  0.0      ...        \n",
       "182 -0.047771  0.0  0.0  0.0  0.0  0.0  0.0   1.0  1.0  0.0      ...        \n",
       "183 -0.177468  0.0  0.0  0.0  0.0  1.0  0.0   6.0  5.0  0.0      ...        \n",
       "184 -0.102225  0.0  0.0  0.0  0.0  0.0  0.0   4.0  3.0  0.0      ...        \n",
       "185 -0.094878  0.0  0.0  0.0  0.0  1.0  0.0   2.0  1.0  0.0      ...        \n",
       "186 -0.158656  0.0  0.0  0.0  0.0  0.0  0.0   9.0  2.0  0.0      ...        \n",
       "187 -0.134554  0.0  0.0  0.0  0.0  0.0  0.0   4.0  0.0  0.0      ...        \n",
       "188 -0.063891  0.0  0.0  0.0  0.0  0.0  0.0   1.0  0.0  0.0      ...        \n",
       "189 -0.119476  0.0  0.0  0.0  0.0  2.0  0.0   6.0  3.0  1.0      ...        \n",
       "190  0.023939  1.0  1.0  0.0  0.0  1.0  0.0   5.0  2.0  0.0      ...        \n",
       "191 -0.150679  0.0  0.0  0.0  0.0  0.0  0.0   9.0  4.0  1.0      ...        \n",
       "192 -0.114299  0.0  0.0  0.0  0.0  0.0  0.0   8.0  5.0  4.0      ...        \n",
       "193  0.134411  0.0  0.0  0.0  0.0  0.0  0.0   2.0  0.0  0.0      ...        \n",
       "194 -0.165052  0.0  0.0  0.0  0.0  0.0  0.0   6.0  3.0  0.0      ...        \n",
       "195 -0.097589  0.0  0.0  0.0  0.0  0.0  0.0   3.0  3.0  0.0      ...        \n",
       "196  0.000000  1.0  1.0  0.0  0.0  0.0  0.0   1.0  0.0  0.0      ...        \n",
       "197 -0.084336  0.0  0.0  0.0  0.0  1.0  0.0   4.0  3.0  0.0      ...        \n",
       "198 -0.029901  0.0  0.0  0.0  0.0  0.0  0.0   3.0  1.0  0.0      ...        \n",
       "199 -0.068533  0.0  0.0  0.0  0.0  2.0  0.0   8.0  2.0  0.0      ...        \n",
       "\n",
       "     F12  F13  F14  F15  F16  F17   F18   F19       F20           F21  \n",
       "0    0.0  0.0  0.0  0.0  0.0  1.0   5.0   7.0  0.428571  7.860000e-01  \n",
       "1    0.0  0.0  0.0  0.0  0.0  1.0   7.0   9.0  0.418889  8.671429e-01  \n",
       "2    0.0  0.0  0.0  0.0  0.0  1.0   4.0   8.0  0.380000  8.825000e-01  \n",
       "3    0.0  0.0  0.0  0.0  0.0  1.0   1.0   3.0  0.436667  9.200000e-01  \n",
       "4    0.0  0.0  0.0  0.0  0.0  1.0   6.0   9.0  0.428889  8.350000e-01  \n",
       "5    0.0  0.0  0.0  0.0  0.0  1.0   1.0   5.0  0.330000  9.200000e-01  \n",
       "6    2.0  0.0  0.0  0.0  0.0  1.0   6.0   4.0  0.425000  8.883333e-01  \n",
       "7    0.0  0.0  0.0  0.0  0.0  1.0   8.0  14.0  0.370000  8.687500e-01  \n",
       "8    0.0  0.0  0.0  0.0  0.0  1.0   9.0   7.0  0.474286  8.833333e-01  \n",
       "9    0.0  0.0  0.0  0.0  0.0  1.0   4.0   5.0  0.476000  8.875000e-01  \n",
       "10   0.0  0.0  0.0  0.0  0.0  1.0   4.0   9.0  0.416667  8.600000e-01  \n",
       "11   0.0  0.0  0.0  0.0  0.0  1.0   3.0   6.0  0.490000  8.933333e-01  \n",
       "12   0.0  0.0  0.0  0.0  0.0  1.0   7.0   9.0  0.428889  9.071429e-01  \n",
       "13   0.0  0.0  0.0  0.0  0.0  1.0   4.0   3.0  0.436667  8.525000e-01  \n",
       "14   0.0  0.0  0.0  0.0  0.0  1.0   8.0  14.0  0.444286  8.725000e-01  \n",
       "15   0.0  0.0  0.0  0.0  0.0  1.0   3.0   5.0  0.436000  8.966667e-01  \n",
       "16   0.0  1.0  0.0  0.0  0.0  1.0   8.0   8.0  0.397500  8.637500e-01  \n",
       "17   0.0  0.0  0.0  1.0  0.0  1.0  13.0   7.0  0.342857  8.192308e-01  \n",
       "18   0.0  0.0  0.0  0.0  0.0  1.0   3.0   7.0  0.425714  8.000000e-01  \n",
       "19   0.0  0.0  0.0  0.0  0.0  1.0  10.0   8.0  0.395000  8.290000e-01  \n",
       "20   0.0  0.0  0.0  0.0  0.0  1.0   9.0   7.0  0.394286  8.455556e-01  \n",
       "21   0.0  0.0  0.0  0.0  0.0  1.0   5.0   4.0  0.412500  8.480000e-01  \n",
       "22   0.0  0.0  0.0  1.0  0.0  1.0   9.0   8.0  0.363750  8.200000e-01  \n",
       "23   0.0  0.0  0.0  1.0  0.0  1.0  12.0  11.0  0.353636  8.550000e-01  \n",
       "24   0.0  0.0  0.0  0.0  0.0  1.0   4.0   8.0  0.403750  8.175000e-01  \n",
       "25   0.0  0.0  0.0  0.0  0.0  1.0   9.0  10.0  0.345000  8.322222e-01  \n",
       "26   0.0  0.0  0.0  0.0  0.0  1.0   7.0   8.0  0.406250  8.814286e-01  \n",
       "27   0.0  0.0  0.0  0.0  0.0  1.0   3.0   4.0  0.377500  9.033333e-01  \n",
       "28   0.0  0.0  0.0  0.0  0.0  1.0  10.0   7.0  0.442857  8.710000e-01  \n",
       "29   0.0  0.0  0.0  0.0  0.0  1.0  10.0  10.0  0.471000  8.200000e-01  \n",
       "..   ...  ...  ...  ...  ...  ...   ...   ...       ...           ...  \n",
       "170  2.0  1.0  0.0  0.0  0.0  1.0   7.0   9.0  0.434444  1.494865e+13  \n",
       "171  0.0  0.0  0.0  1.0  0.0  1.0   8.0   7.0  0.464286  7.837500e-01  \n",
       "172  0.0  0.0  0.0  0.0  0.0  1.0   4.0   8.0  0.373750  9.025000e-01  \n",
       "173  0.0  0.0  0.0  0.0  0.0  1.0  11.0   8.0  0.400000  8.200000e-01  \n",
       "174  0.0  0.0  0.0  0.0  0.0  1.0   5.0   6.0  0.386667  8.300000e-01  \n",
       "175  0.0  0.0  0.0  0.0  0.0  1.0   2.0   4.0  0.450000  7.600000e-01  \n",
       "176  0.0  0.0  0.0  0.0  0.0  1.0   5.0   7.0  0.455714  8.140000e-01  \n",
       "177  0.0  0.0  0.0  0.0  0.0  1.0   9.0   6.0  0.438333  8.500000e-01  \n",
       "178  0.0  0.0  0.0  0.0  0.0  1.0   2.0   4.0  0.450000  9.000000e-01  \n",
       "179  0.0  0.0  0.0  0.0  0.0  1.0   1.0   3.0  0.436667  9.200000e-01  \n",
       "180  0.0  0.0  0.0  0.0  0.0  1.0   2.0   3.0  0.436667  8.850000e-01  \n",
       "181  0.0  1.0  0.0  0.0  0.0  1.0  12.0  17.0  0.505294  8.108333e-01  \n",
       "182  0.0  0.0  0.0  0.0  0.0  1.0   4.0   3.0  0.436667  8.925000e-01  \n",
       "183  0.0  0.0  0.0  0.0  0.0  1.0  11.0   8.0  0.502500  7.963636e-01  \n",
       "184  0.0  0.0  0.0  0.0  0.0  1.0   8.0   7.0  0.407143  8.612500e-01  \n",
       "185  0.0  0.0  0.0  0.0  0.0  1.0   8.0   4.0  0.415000  8.775000e-01  \n",
       "186  0.0  0.0  0.0  0.0  0.0  1.0   7.0   7.0  0.385714  1.494865e+13  \n",
       "187  0.0  0.0  0.0  0.0  0.0  1.0   2.0   5.0  0.418000  9.200000e-01  \n",
       "188  0.0  0.0  0.0  0.0  0.0  1.0   2.0   4.0  0.437500  9.200000e-01  \n",
       "189  0.0  0.0  0.0  0.0  0.0  1.0   9.0   6.0  0.373333  8.144444e-01  \n",
       "190  0.0  0.0  0.0  0.0  0.0  1.0   7.0  11.0  0.400909  8.814286e-01  \n",
       "191  0.0  0.0  0.0  0.0  0.0  1.0   8.0  10.0  0.425000  8.512500e-01  \n",
       "192  0.0  0.0  0.0  0.0  0.0  1.0  13.0  11.0  0.386364  7.684615e-01  \n",
       "193  0.0  0.0  0.0  0.0  0.0  1.0   4.0   5.0  0.386000  9.025000e-01  \n",
       "194  0.0  0.0  0.0  0.0  0.0  1.0   5.0  13.0  0.373077  9.100000e-01  \n",
       "195  0.0  0.0  0.0  0.0  0.0  1.0   8.0   7.0  0.490000  8.850000e-01  \n",
       "196  0.0  0.0  0.0  0.0  0.0  1.0   2.0   4.0  0.467500  8.950000e-01  \n",
       "197  0.0  0.0  0.0  0.0  0.0  1.0  10.0  10.0  0.450000  8.570000e-01  \n",
       "198  0.0  0.0  0.0  0.0  0.0  1.0   4.0   5.0  0.392000  8.875000e-01  \n",
       "199  1.0  0.0  0.0  0.0  0.0  1.0  16.0  11.0  0.433636  6.272173e+12  \n",
       "\n",
       "[200 rows x 21 columns]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Testdf.astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "testExcelNPArray = Testdf.as_matrix()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(200, 21)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testExcelNPArray.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "testFeaturesPruned = test_data_extracted_features_x[0:200]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(200, 12)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testFeaturesPruned.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "testScorePruned = test_score_array[0:200]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "testAllFeatures=numpy.hstack((testExcelNPArray,testFeaturesPruned))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(200, 33)"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testAllFeatures.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decision Tree Regression score: -0.059591080655\n"
     ]
    }
   ],
   "source": [
    "# Decision Tree Regression\n",
    "\n",
    "decision_tree_regressor = tree.DecisionTreeRegressor(max_depth=7, min_samples_leaf=17)\n",
    "decision_tree_regressor.fit(trainAllFeatures, score_array)\n",
    "\n",
    "# Test Decision Tree Regression on Test Data\n",
    "\n",
    "print('Decision Tree Regression score: '\n",
    "      + str(decision_tree_regressor.score(testAllFeatures, testScorePruned)))\n",
    "# Score: -0.759753880839\n",
    "# After adjusting values, score improved, but still very bad. Score: -0.193423357515\n",
    "\n",
    "# Get Feature Importances of Decision Tree\n",
    "\n",
    "# print(decision_tree_regressor.feature_importances_)\n",
    "\n",
    "# Try Regression based on k-nearest neighbors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "K-Nearest Neighbours Regression score: 0.201266713057\n"
     ]
    }
   ],
   "source": [
    "#Try Regression based on k-nearest neighbors.\n",
    "\n",
    "k_nearest_neighbors_regressor = neighbors.KNeighborsRegressor(n_neighbors=75, p=1)\n",
    "k_nearest_neighbors_regressor.fit(trainAllFeatures, score_array)\n",
    "\n",
    "# Test K-Nearest Neighbours Regression on Test Data\n",
    "\n",
    "print('K-Nearest Neighbours Regression score: '\n",
    "      + str(k_nearest_neighbors_regressor.score(testAllFeatures, testScorePruned)))\n",
    "# Score: -0.0961322606566\n",
    "# When I changed n_neighbors from default of 5 to 248 score increased dramatically Yet changing n_neighbors to 75 increased the score\n",
    "# Changing algorithms didn't have anny effect\n",
    "# Score: 0.129813702549\n",
    "# When I changed p to 1 from the default value of 2, score increased again\n",
    "# Score: 0.161999595131"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# # Try Support Vector Machine Regression\n",
    "\n",
    "# support_vector_machine_regressor = svm.LinearSVR(kernel='linear', epsilon=0.2,cache_size=7000)\n",
    "# support_vector_machine_regressor.fit(trainAllFeatures, score_array)\n",
    "\n",
    "# # Test Support Vector Machine Regression on Test Data\n",
    "\n",
    "# print('Support Vector Machine Regressor Score: '\n",
    "#       + str(support_vector_machine_regressor.score(testAllFeatures, testScorePruned)))\n",
    "# # Score: -0.101547661324\n",
    "# # after changing the kernel to 'linear', score improved.\n",
    "# # Score: 0.117806253477\n",
    "# # after changing epsilon value to 0.2, score improved again\n",
    "# # Score: 0.133648477067"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stochastic Gradient Descent Regressor Score: -1.44070301674e+68\n"
     ]
    }
   ],
   "source": [
    "# Try Stochastic Gradient Descent Regression\n",
    "\n",
    "stochastic_gradient_descent_regressor = linear_model.SGDRegressor(tol=1e-3)\n",
    "stochastic_gradient_descent_regressor.fit(trainAllFeatures, score_array)\n",
    "\n",
    "# Test Stochastic Gradient Descent Regression on Test Data\n",
    "\n",
    "print('Stochastic Gradient Descent Regressor Score: '\n",
    "      + str(stochastic_gradient_descent_regressor.score(testAllFeatures, testScorePruned)))\n",
    "# Score: 0.176217008989"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Random Forests Regressor score: 0.00384244734706\n"
     ]
    }
   ],
   "source": [
    "# Try Random Forests Regression\n",
    "\n",
    "random_forests_regressor = ensemble.RandomForestRegressor(max_depth=7, min_samples_leaf=17)\n",
    "random_forests_regressor.fit(trainAllFeatures, score_array)\n",
    "\n",
    "# Test Random Forest Regression on Test Data\n",
    "\n",
    "print('Random Forests Regressor score: ' + str(random_forests_regressor.score(testAllFeatures,\n",
    "                                                                              testScorePruned)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\user\\Anaconda3\\lib\\site-packages\\sklearn\\neural_network\\_base.py:194: RuntimeWarning: overflow encountered in square\n",
      "  return ((y_true - y_pred) ** 2).mean() / 2\n",
      "C:\\Users\\user\\Anaconda3\\lib\\site-packages\\sklearn\\neural_network\\multilayer_perceptron.py:564: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (200) reached and the optimization hasn't converged yet.\n",
      "  % self.max_iter, ConvergenceWarning)\n"
     ]
    },
    {
     "ename": "ValueError",
     "evalue": "Input contains NaN, infinity or a value too large for dtype('float64').",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-59-db3f4d71b100>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m print('Multi-layer Perceptron score: ' + str(multi_layer_perceptron_regressor.score(testAllFeatures,\n\u001b[0;32m----> 9\u001b[0;31m                                                                                     testScorePruned)))\n\u001b[0m\u001b[1;32m     10\u001b[0m \u001b[1;31m# Score: 0.00620729465159\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m     11\u001b[0m \u001b[1;31m# It got a lot better after I changed to solver to 'sgd': stochastic gradient descent.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\Users\\user\\Anaconda3\\lib\\site-packages\\sklearn\\base.py\u001b[0m in \u001b[0;36mscore\u001b[0;34m(self, X, y, sample_weight)\u001b[0m\n\u001b[1;32m    386\u001b[0m         \u001b[1;32mfrom\u001b[0m \u001b[1;33m.\u001b[0m\u001b[0mmetrics\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mr2_score\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    387\u001b[0m         return r2_score(y, self.predict(X), sample_weight=sample_weight,\n\u001b[0;32m--> 388\u001b[0;31m                         multioutput='variance_weighted')\n\u001b[0m\u001b[1;32m    389\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    390\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\Users\\user\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\regression.py\u001b[0m in \u001b[0;36mr2_score\u001b[0;34m(y_true, y_pred, sample_weight, multioutput)\u001b[0m\n\u001b[1;32m    528\u001b[0m     \"\"\"\n\u001b[1;32m    529\u001b[0m     y_type, y_true, y_pred, multioutput = _check_reg_targets(\n\u001b[0;32m--> 530\u001b[0;31m         y_true, y_pred, multioutput)\n\u001b[0m\u001b[1;32m    531\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    532\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0msample_weight\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\Users\\user\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\regression.py\u001b[0m in \u001b[0;36m_check_reg_targets\u001b[0;34m(y_true, y_pred, multioutput)\u001b[0m\n\u001b[1;32m     75\u001b[0m     \u001b[0mcheck_consistent_length\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my_true\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my_pred\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m     76\u001b[0m     \u001b[0my_true\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcheck_array\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my_true\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mensure_2d\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m---> 77\u001b[0;31m     \u001b[0my_pred\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcheck_array\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my_pred\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mensure_2d\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     78\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m     79\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0my_true\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\Users\\user\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\validation.py\u001b[0m in \u001b[0;36mcheck_array\u001b[0;34m(array, accept_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator)\u001b[0m\n\u001b[1;32m    420\u001b[0m                              % (array.ndim, estimator_name))\n\u001b[1;32m    421\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mforce_all_finite\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m--> 422\u001b[0;31m             \u001b[0m_assert_all_finite\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    423\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    424\u001b[0m     \u001b[0mshape_repr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_shape_repr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\Users\\user\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\validation.py\u001b[0m in \u001b[0;36m_assert_all_finite\u001b[0;34m(X)\u001b[0m\n\u001b[1;32m     41\u001b[0m             and not np.isfinite(X).all()):\n\u001b[1;32m     42\u001b[0m         raise ValueError(\"Input contains NaN, infinity\"\n\u001b[0;32m---> 43\u001b[0;31m                          \" or a value too large for %r.\" % X.dtype)\n\u001b[0m\u001b[1;32m     44\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m     45\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Input contains NaN, infinity or a value too large for dtype('float64')."
     ]
    }
   ],
   "source": [
    "# Try Multi-layer Perceptron Regression\n",
    "\n",
    "multi_layer_perceptron_regressor = neural_network.MLPRegressor(solver='sgd')\n",
    "multi_layer_perceptron_regressor.fit(trainAllFeatures, score_array)\n",
    "\n",
    "# Test Multi-layer Perceptron on Test Data\n",
    "\n",
    "print('Multi-layer Perceptron score: ' + str(multi_layer_perceptron_regressor.score(testAllFeatures,\n",
    "                                                                                    testScorePruned)))\n",
    "# Score: 0.00620729465159\n",
    "# It got a lot better after I changed to solver to 'sgd': stochastic gradient descent.\n",
    "# Score: 0.154938217153"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# # Try Recursive Feature Selection\n",
    "# estimator = svm.SVR(kernel=\"linear\")\n",
    "# recursive_feature_selection = feature_selection.RFE(estimator)\n",
    "# recursive_feature_selection.fit(trainAllFeatures, score_array)\n",
    "\n",
    "# # Test Recursive Feature Selection on Test Data\n",
    "\n",
    "# print('Recursive Feature Selection score. ' + str(recursive_feature_selection.score(testAllFeatures,\n",
    "#                                                                                     testScorePruned)))\n",
    "# # Score: 0.0631286115014"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ridge Regressor score: 0.299447255872\n"
     ]
    }
   ],
   "source": [
    "# Try Ridge Regression\n",
    "\n",
    "ridge_regressor = linear_model.Ridge(solver='sag', normalize=True)\n",
    "ridge_regressor.fit(trainAllFeatures, score_array)\n",
    "\n",
    "# Test Rigde Regression on Test Data\n",
    "\n",
    "print('Ridge Regressor score: ' + str(ridge_regressor.score(testAllFeatures, testScorePruned)))\n",
    "# Score: 0.140327821678\n",
    "# It slightly improved when I changed the solver to saga (Stochastic Average Gradient Descent)\n",
    "# When I turned on normalize ,after changing the solver to saga, score improved; however before that, it didn't help.\n",
    "# Score: 0.191242391892\n",
    "predictedListOne = ridge_regressor.predict(testAllFeatures)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ridge Regressor score: 0.247688599071\n"
     ]
    }
   ],
   "source": [
    "# Try Bayesian Ridge Regression\n",
    "\n",
    "ridge_regressor = linear_model.BayesianRidge(normalize=True)\n",
    "ridge_regressor.fit(trainAllFeatures, score_array)\n",
    "\n",
    "# Test Rigde Regression on Test Data\n",
    "\n",
    "print('Ridge Regressor score: ' + str(ridge_regressor.score(testAllFeatures, testScorePruned)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ensemble Regressor score: 0.00884248453279\n"
     ]
    }
   ],
   "source": [
    "# Try ensemble   Regression\n",
    "\n",
    "ensemble_regressor = ensemble.AdaBoostRegressor()\n",
    "ensemble_regressor.fit(trainAllFeatures, score_array)\n",
    "\n",
    "# Test ensemble Regression on Test Data\n",
    "\n",
    "print('ensemble Regressor score: ' + str(ensemble_regressor.score(testAllFeatures, testScorePruned)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ensemble Regressor score: -0.134421059862\n"
     ]
    }
   ],
   "source": [
    "# Try ensemble   Regression\n",
    "\n",
    "ensemble_regressor = ensemble.BaggingRegressor()\n",
    "ensemble_regressor.fit(trainAllFeatures, score_array)\n",
    "\n",
    "# Test ensemble Regression on Test Data\n",
    "\n",
    "print('ensemble Regressor score: ' + str(ensemble_regressor.score(testAllFeatures, testScorePruned)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ensemble Regressor score: -0.121393510604\n"
     ]
    }
   ],
   "source": [
    "# Try ensemble   Regression\n",
    "\n",
    "ensemble_regressor = ensemble.ExtraTreesRegressor()\n",
    "ensemble_regressor.fit(trainAllFeatures, score_array)\n",
    "\n",
    "# Test ensemble Regression on Test Data\n",
    "\n",
    "print('ensemble Regressor score: ' + str(ensemble_regressor.score(testAllFeatures, testScorePruned)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ensemble Regressor score: -0.102476098383\n"
     ]
    }
   ],
   "source": [
    "# Try ensemble   Regression\n",
    "\n",
    "ensemble_regressor = ensemble.GradientBoostingRegressor()\n",
    "ensemble_regressor.fit(trainAllFeatures, score_array)\n",
    "\n",
    "# Test ensemble Regression on Test Data\n",
    "\n",
    "print('ensemble Regressor score: ' + str(ensemble_regressor.score(testAllFeatures, testScorePruned)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ensemble Regressor score: -0.126840546635\n"
     ]
    }
   ],
   "source": [
    "# Try ensemble   Regression\n",
    "\n",
    "ensemble_regressor = ensemble.RandomForestRegressor()\n",
    "ensemble_regressor.fit(trainAllFeatures, score_array)\n",
    "\n",
    "# Test ensemble Regression on Test Data\n",
    "\n",
    "print('ensemble Regressor score: ' + str(ensemble_regressor.score(testAllFeatures, testScorePruned)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "###########************REGRESSION WITH 21 FEATURES STARTS HERE ********************************#################"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# testExcelNPArray.shape      testScorePruned\n",
    "\n",
    "# trainExcelNPArray    score_array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decision Tree Regression score: -0.149098427286\n"
     ]
    }
   ],
   "source": [
    "# Decision Tree Regression\n",
    "\n",
    "decision_tree_regressor = tree.DecisionTreeRegressor(max_depth=7, min_samples_leaf=17)\n",
    "decision_tree_regressor.fit(trainExcelNPArray, score_array)\n",
    "\n",
    "# Test Decision Tree Regression on Test Data\n",
    "\n",
    "print('Decision Tree Regression score: '\n",
    "      + str(decision_tree_regressor.score(testExcelNPArray, testScorePruned)))\n",
    "# Score: -0.759753880839\n",
    "# After adjusting values, score improved, but still very bad. Score: -0.193423357515 -> with only extracted features\n",
    "\n",
    "# with only given features it is better but still the score values is negative\n",
    "\n",
    "# Get Feature Importances of Decision Tree\n",
    "\n",
    "# print(decision_tree_regressor.feature_importances_)\n",
    "\n",
    "# Try Regression based on k-nearest neighbors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "K-Nearest Neighbours Regression score: 0.110167788494\n"
     ]
    }
   ],
   "source": [
    "# Try Regression based on k-nearest neighbors.\n",
    "\n",
    "k_nearest_neighbors_regressor = neighbors.KNeighborsRegressor(n_neighbors=248, p=1)\n",
    "k_nearest_neighbors_regressor.fit(trainExcelNPArray, score_array)\n",
    "\n",
    "# Test K-Nearest Neighbours Regression on Test Data\n",
    "\n",
    "print('K-Nearest Neighbours Regression score: '\n",
    "      + str(k_nearest_neighbors_regressor.score(testExcelNPArray, testScorePruned)))\n",
    "# Score: -0.0961322606566\n",
    "# When I changed n_neighbors from default of 5 to 248 score increased dramatically\n",
    "# Changing algorithms didn't have anny effect\n",
    "# Score: 0.129813702549\n",
    "# When I changed p to 1 from the default value of 2, score increased again\n",
    "# Score: 0.161999595131\n",
    "\n",
    "# with only given 21 features the score is slighly worse "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# # Try Support Vector Machine Regression\n",
    "\n",
    "# support_vector_machine_regressor = svm.SVR(kernel='linear', epsilon=0.2)\n",
    "# support_vector_machine_regressor.fit(trainExcelNPArray, score_array)\n",
    "\n",
    "# # Test Support Vector Machine Regression on Test Data\n",
    "\n",
    "# print('Support Vector Machine Regressor Score: '\n",
    "#       + str(support_vector_machine_regressor.score(testExcelNPArray, test_score_array)))\n",
    "# # Score: -0.101547661324\n",
    "# # after changing the kernel to 'linear', score improved.\n",
    "# # Score: 0.117806253477\n",
    "# # after changing epsilon value to 0.2, score improved again\n",
    "# # Score: 0.133648477067"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stochastic Gradient Descent Regressor Score: -7.49631133379e+68\n"
     ]
    }
   ],
   "source": [
    "# Try Stochastic Gradient Descent Regression\n",
    "\n",
    "stochastic_gradient_descent_regressor = linear_model.SGDRegressor(tol=1e-3)\n",
    "stochastic_gradient_descent_regressor.fit(trainExcelNPArray, score_array)\n",
    "\n",
    "# Test Stochastic Gradient Descent Regression on Test Data\n",
    "\n",
    "print('Stochastic Gradient Descent Regressor Score: '\n",
    "      + str(stochastic_gradient_descent_regressor.score(testExcelNPArray, testScorePruned)))\n",
    "# Score: 0.176217008989"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Random Forests Regressor score: -0.00608422740509\n"
     ]
    }
   ],
   "source": [
    "# Try Random Forests Regression\n",
    "\n",
    "random_forests_regressor = ensemble.RandomForestRegressor(max_depth=7, min_samples_leaf=17)\n",
    "random_forests_regressor.fit(trainExcelNPArray, score_array)\n",
    "\n",
    "# Test Random Forest Regression on Test Data\n",
    "\n",
    "print('Random Forests Regressor score: ' + str(random_forests_regressor.score(testExcelNPArray,\n",
    "                                                                              testScorePruned)))\n",
    "# Score: -0.334794427196\n",
    "# After changing parameters, score improved but still very bad\n",
    "# Score: -0.193607366878"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Multi-layer Perceptron score: -2.28490127452e+171\n"
     ]
    }
   ],
   "source": [
    "# Try Multi-layer Perceptron Regression\n",
    "\n",
    "multi_layer_perceptron_regressor = neural_network.MLPRegressor(solver='sgd')\n",
    "multi_layer_perceptron_regressor.fit(trainExcelNPArray, score_array)\n",
    "\n",
    "# Test Multi-layer Perceptron on Test Data\n",
    "\n",
    "print('Multi-layer Perceptron score: ' + str(multi_layer_perceptron_regressor.score(testExcelNPArray,\n",
    "                                                                                    testScorePruned)))\n",
    "# Score: 0.00620729465159\n",
    "# It got a lot better after I changed to solver to 'sgd': stochastic gradient descent.\n",
    "# Score: 0.154938217153"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ridge Regressor score: 0.146191396497\n"
     ]
    }
   ],
   "source": [
    "# Try Ridge Regression\n",
    "\n",
    "ridge_regressor = linear_model.Ridge(solver='auto', normalize=True)\n",
    "ridge_regressor.fit(trainExcelNPArray, score_array)\n",
    "\n",
    "# Test Rigde Regression on Test Data\n",
    "\n",
    "print('Ridge Regressor score: ' + str(ridge_regressor.score(testExcelNPArray, testScorePruned)))\n",
    "# Score: 0.140327821678\n",
    "# It slightly improved when I changed the solver to saga (Stochastic Average Gradient Descent)\n",
    "# When I turned on normalize ,after changing the solver to saga, score improved; however before that, it didn't help.\n",
    "# Score: 0.191242391892"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ridge Regressor score: 0.0310530631153\n"
     ]
    }
   ],
   "source": [
    "# Try Bayesian Ridge Regression\n",
    "\n",
    "ridge_regressor = linear_model.BayesianRidge(normalize=True)\n",
    "ridge_regressor.fit(trainExcelNPArray, score_array)\n",
    "\n",
    "# Test Rigde Regression on Test Data\n",
    "\n",
    "print('Ridge Regressor score: ' + str(ridge_regressor.score(testExcelNPArray, testScorePruned)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "####################***********FEATURE SElECTION FROM BAG OF WORDS MODEL ***************###########################"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# feature_array.shape  // score_array\n",
    "# test_feature_array -> take the first 200 samples // testScorePruned\n",
    "# model = SelectFromModel(reg, prefit=True, threshold=0.05)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "test_feature_array = test_feature_array[0:200]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ridge Regressor score: 0.216133793898\n"
     ]
    }
   ],
   "source": [
    "ridge_regressor = linear_model.Ridge(solver='auto', normalize=True)\n",
    "ridge_regressor.fit(feature_array, score_array)\n",
    "\n",
    "# Test Rigde Regression on Test Data\n",
    "\n",
    "print('Ridge Regressor score: ' + str(ridge_regressor.score(test_feature_array, testScorePruned)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "model = SelectFromModel(ridge_regressor, prefit=True, threshold=\"2*mean\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "selectedFeaturesFromBagOfWords = model.transform(feature_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "selectedTestFeaturesFromBagOfWords = model.transform(test_feature_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(757, 146)"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selectedFeaturesFromBagOfWords.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(200, 146)"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selectedTestFeaturesFromBagOfWords.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ridge Regressor score with selected features from bag of words: 0.101547209722\n"
     ]
    }
   ],
   "source": [
    "ridge_regressor = linear_model.Ridge(solver='auto', normalize=True)\n",
    "ridge_regressor.fit(selectedFeaturesFromBagOfWords, score_array)\n",
    "\n",
    "# Test Rigde Regression on Test Data\n",
    "\n",
    "print('Ridge Regressor score with selected features from bag of words: ' + str(ridge_regressor.score(selectedTestFeaturesFromBagOfWords, testScorePruned)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "##############************* LET'S COMBINE ALL THE FEATURES *********************######################"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "selectedFeaturesFromBagOfWordsArray =selectedFeaturesFromBagOfWords.toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "selectedTestFeaturesFromBagOfWordsArray = selectedTestFeaturesFromBagOfWords.toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "trainAllFeaturesCombined=numpy.hstack((trainAllFeatures,selectedFeaturesFromBagOfWordsArray))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "testAllFeaturesCombined=numpy.hstack((testAllFeatures,selectedTestFeaturesFromBagOfWordsArray))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(757, 179)"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trainAllFeaturesCombined.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(200, 179)"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testAllFeaturesCombined.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#########################*********** REGRESSION USING ALL THE FEATURES COMBINED *****************#################33"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decision Tree Regression score: -0.107075691865\n"
     ]
    }
   ],
   "source": [
    "# Decision Tree Regression\n",
    "\n",
    "decision_tree_regressor = tree.DecisionTreeRegressor(max_depth=7, min_samples_leaf=17)\n",
    "decision_tree_regressor.fit(trainAllFeaturesCombined, score_array)\n",
    "\n",
    "# Test Decision Tree Regression on Test Data\n",
    "\n",
    "print('Decision Tree Regression score: '\n",
    "      + str(decision_tree_regressor.score(testAllFeaturesCombined, testScorePruned)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "K-Nearest Neighbours Regression score: 0.213326574512\n"
     ]
    }
   ],
   "source": [
    "# Try Regression based on k-nearest neighbors.\n",
    "\n",
    "k_nearest_neighbors_regressor = neighbors.KNeighborsRegressor(n_neighbors=65, p=1)\n",
    "k_nearest_neighbors_regressor.fit(trainAllFeaturesCombined, score_array)\n",
    "\n",
    "# Test K-Nearest Neighbours Regression on Test Data\n",
    "\n",
    "print('K-Nearest Neighbours Regression score: '\n",
    "      + str(k_nearest_neighbors_regressor.score(testAllFeaturesCombined, testScorePruned)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stochastic Gradient Descent Regressor Score: -1.27924009544e+69\n"
     ]
    }
   ],
   "source": [
    "# Try Stochastic Gradient Descent Regression\n",
    "\n",
    "stochastic_gradient_descent_regressor = linear_model.SGDRegressor(tol=1e-3)\n",
    "stochastic_gradient_descent_regressor.fit(trainAllFeaturesCombined, score_array)\n",
    "\n",
    "# Test Stochastic Gradient Descent Regression on Test Data\n",
    "\n",
    "print('Stochastic Gradient Descent Regressor Score: '\n",
    "      + str(stochastic_gradient_descent_regressor.score(testAllFeaturesCombined, testScorePruned)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Random Forests Regressor score: 0.0225786670209\n"
     ]
    }
   ],
   "source": [
    "# Try Random Forests Regression\n",
    "\n",
    "random_forests_regressor = ensemble.RandomForestRegressor(max_depth=10, min_samples_leaf=8)\n",
    "random_forests_regressor.fit(trainAllFeaturesCombined, score_array)\n",
    "\n",
    "# Test Random Forest Regression on Test Data\n",
    "\n",
    "print('Random Forests Regressor score: ' + str(random_forests_regressor.score(testAllFeaturesCombined,\n",
    "                                                                              testScorePruned)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Multi-layer Perceptron score: -0.0118450294104\n"
     ]
    }
   ],
   "source": [
    "# Try Multi-layer Perceptron Regression\n",
    "\n",
    "multi_layer_perceptron_regressor = neural_network.MLPRegressor(solver='sgd',hidden_layer_sizes=(100000,1))\n",
    "multi_layer_perceptron_regressor.fit(trainAllFeaturesCombined, score_array)\n",
    "\n",
    "# Test Multi-layer Perceptron on Test Data\n",
    "\n",
    "print('Multi-layer Perceptron score: ' + str(multi_layer_perceptron_regressor.score(testAllFeaturesCombined,\n",
    "                                                                                    testScorePruned)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ridge Regressor score: 0.231409345332\n",
      "Ridge Regressor prediction: [ -2.42420719e-01   3.52242512e-01   1.06678714e-02   2.56871959e-02\n",
      "  -3.03343202e-01  -3.31628729e-01  -4.60773307e-01  -1.74970400e-01\n",
      "   1.19400671e-01   2.75761079e-01  -1.68669255e-01  -6.48985401e-02\n",
      "  -1.63135767e-01  -1.27081305e-01  -5.63680686e-01  -1.33573550e-01\n",
      "  -4.40413132e-01   2.72971768e-02   2.60984523e-03  -2.16539267e-01\n",
      "  -8.22508793e-01  -1.77730376e-01  -7.03493262e-01  -6.73511321e-01\n",
      "  -1.47950421e-02  -8.40664909e-01  -2.70622648e-01  -2.05993086e-01\n",
      "  -4.50204024e-01  -5.21952630e-01  -5.94716148e-01   5.46971545e-01\n",
      "  -5.94041804e-01  -3.30822695e-01  -6.42548079e-01  -3.38678722e-01\n",
      "  -3.75990306e-01  -3.72729650e-01  -3.64115922e-01  -6.85511528e-01\n",
      "  -4.63777186e-02  -5.33515199e-01  -4.00683967e-01   2.02413369e-02\n",
      "  -1.68665454e-01  -3.25054460e-01  -8.80108584e-02  -3.66439378e-01\n",
      "  -3.92417207e-01  -3.79797239e-01  -5.11720615e-01  -5.75414863e-01\n",
      "   2.02702199e-01  -3.50832766e-01   2.56205132e-01   1.97577870e-01\n",
      "  -2.72191264e-01  -9.37209016e-02  -3.79683104e-01  -4.73920670e-01\n",
      "  -5.55633556e-01  -4.22781428e-01  -1.45688449e-01   7.04082330e-03\n",
      "  -4.36965179e-01  -4.29414488e-02  -7.24096958e-01  -5.20168743e-01\n",
      "  -6.07496658e-01  -1.72202029e-01  -3.16652759e-01  -3.24368488e-01\n",
      "  -2.21728573e-01  -1.02339983e+00  -2.65227295e-01  -1.00897356e-01\n",
      "  -4.25534914e-01  -4.67698096e-01  -7.10509192e-01  -2.78414330e-01\n",
      "  -7.69110581e-01  -1.29108536e+00  -5.95949260e-02  -1.26243476e+00\n",
      "  -3.11291171e-01  -7.14480864e-01   1.87577289e-01  -4.27881923e-01\n",
      "  -3.11293324e-01   1.27682069e-03  -2.07911954e-01  -7.39734001e-02\n",
      "  -4.80481344e-01  -5.71806626e-01  -5.49116474e-01   3.14385956e-02\n",
      "  -3.33732113e-01  -5.38448854e-01  -4.46354935e-01  -4.41542848e-01\n",
      "  -6.46387142e-02  -8.73092166e-02   5.66865205e-02  -6.73678999e-01\n",
      "  -1.95351486e-02  -2.35457755e-01  -3.84575882e-01  -1.16427340e-02\n",
      "  -4.23589700e-01  -2.28041808e-02  -4.22104958e-01  -6.38949057e-01\n",
      "  -3.98257597e-01  -1.29517168e-01  -6.55457481e-01  -4.21987551e-01\n",
      "  -8.09097835e-01  -2.96141297e-01  -5.09178578e-01  -3.83943450e-01\n",
      "  -5.77622136e-01  -1.67404123e-01  -4.69433444e-01  -2.95003106e-01\n",
      "  -5.35046867e-01  -1.11925152e-01  -3.08580797e-01  -5.76735972e-01\n",
      "   2.53770021e-02  -1.49675667e-02  -1.37347814e-01   8.40245418e-01\n",
      "  -5.15771903e-01   3.58211868e-02  -4.28722765e-01  -4.06442352e-01\n",
      "  -1.27420115e-01  -7.38150865e-01  -2.84751324e-02  -8.63509895e-01\n",
      "  -6.45501574e-01   2.28754934e-01  -1.58782187e-01  -5.74792876e-01\n",
      "  -7.64581772e-01  -3.49468592e-01  -7.95691617e-01   4.03335801e-01\n",
      "  -5.93088736e-01   3.64299427e-02  -4.17934855e-01  -5.94325236e-02\n",
      "  -5.47482961e-01   3.71662649e-01  -2.39608564e-02  -1.92768821e-01\n",
      "  -4.44951258e-01  -6.17814201e-01  -4.01221150e-01  -4.44475442e-01\n",
      "  -3.68411365e-01  -9.43188346e-02   9.26483724e-02  -3.73820267e-01\n",
      "  -6.07053405e-01   1.91020400e-01   1.46697036e-02  -3.17327951e-01\n",
      "  -4.58410086e-01  -3.83571177e-01  -3.24578075e-01  -4.42535385e-01\n",
      "  -2.41911483e-01  -2.05587054e-01   2.15893151e-01  -6.11939951e-01\n",
      "  -5.76180200e-01  -6.42689328e-01  -2.40587291e-01  -3.08289715e-02\n",
      "  -2.84816530e-01  -1.64368118e-01   1.97347580e-01  -5.32987894e-01\n",
      "  -4.08888785e-01  -3.53217955e-01  -4.90774169e-01  -5.06041455e-03\n",
      "   1.05980820e-01  -4.27208079e-01   4.85610863e-01  -2.42260657e-01\n",
      "  -8.11866625e-01   4.32973832e-01  -7.78936187e-01  -2.80919141e-01\n",
      "   8.82307116e-02  -3.88004830e-01   1.94894853e-01  -9.59241954e-02]\n"
     ]
    }
   ],
   "source": [
    "# Try Ridge Regression\n",
    "\n",
    "ridge_regressor = linear_model.Ridge(solver='auto', normalize=True)\n",
    "ridge_regressor.fit(trainAllFeaturesCombined, score_array)\n",
    "\n",
    "# Test Rigde Regression on Test Data\n",
    "\n",
    "print('Ridge Regressor score: ' + str(ridge_regressor.score(testAllFeaturesCombined, testScorePruned)))\n",
    "print('Ridge Regressor prediction: ' + str(ridge_regressor.predict(testAllFeaturesCombined)))\n",
    "predictedListTwo = ridge_regressor.predict(testAllFeaturesCombined)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ridge Regressor score: 0.11981181108\n",
      "Ridge Regressor prediction: [ -1.81221438e-01   4.42262150e-01   1.35298998e-01   7.78244404e-02\n",
      "  -3.01346970e-01  -3.39339573e-01  -6.41043423e-01  -1.16718757e-01\n",
      "   3.71180505e-01   3.55132877e-01  -2.17012966e-01  -5.13529418e-02\n",
      "  -1.50746344e-01  -1.74567138e-01  -6.21766170e-01  -7.39351696e-02\n",
      "  -4.18772204e-01   4.89991377e-02   4.54013283e-02  -9.20327326e-02\n",
      "  -1.07037159e+00  -1.44307536e-01  -7.53807453e-01  -7.11306734e-01\n",
      "  -1.31138375e-02  -8.90923518e-01  -2.43645178e-01  -1.95878910e-01\n",
      "  -4.04486410e-01  -6.23035607e-01  -6.32087946e-01   7.09232844e-01\n",
      "  -6.63171120e-01  -3.33530036e-01  -7.27456214e-01  -3.63878178e-01\n",
      "  -4.70257945e-01  -3.36976419e-01  -3.10720541e-01  -6.99478586e-01\n",
      "  -1.67415348e-02  -6.42114298e-01  -4.19971713e-01   9.40666885e-02\n",
      "  -1.64970900e-01  -2.59362291e-01  -9.75768836e-02  -3.72445475e-01\n",
      "  -4.39769287e-01  -3.37344995e-01  -5.70173682e-01  -6.45513314e-01\n",
      "   2.39570328e-01  -3.87401102e-01   3.07842790e-01   2.68432495e-01\n",
      "  -2.91298714e-01  -7.41535052e-02  -4.67969526e-01  -4.69606356e-01\n",
      "  -6.54677993e-01  -4.32366088e-01  -2.34197858e-01   4.95929324e-02\n",
      "  -4.19157493e-01  -4.97446622e-03  -7.53632260e-01  -5.62881930e-01\n",
      "  -7.02033604e-01  -1.49142201e-01  -3.16210280e-01  -3.42260254e-01\n",
      "  -2.86953683e-01  -1.36946386e+00  -2.71333493e-01  -8.41182483e-03\n",
      "  -3.98035503e-01  -5.82868830e-01  -8.99128188e-01  -2.11210479e-01\n",
      "  -9.72377554e-01  -1.60974696e+00  -9.31331411e-02  -1.54889730e+00\n",
      "  -3.76785503e-01  -7.62677219e-01   2.47153518e-01  -4.17165539e-01\n",
      "  -3.07383452e-01   7.81227940e-03  -2.00168320e-01  -5.48496647e-02\n",
      "  -4.65397110e-01  -6.02145389e-01  -6.18430428e-01   1.61946264e-01\n",
      "  -3.35694733e-01  -5.31421792e-01  -4.19649042e-01  -4.62137248e-01\n",
      "  -4.22129698e-02  -7.10161266e-02   4.75247012e-02  -6.79387301e-01\n",
      "   5.90958524e-02  -2.07750578e-01  -4.60012214e-01  -6.38959934e-02\n",
      "  -4.45423778e-01   4.34396456e-03  -4.49474874e-01  -7.24073624e-01\n",
      "  -2.85808292e-01  -1.16691757e-01  -6.42840380e-01  -5.12056575e-01\n",
      "  -9.67669549e-01  -3.53520791e-01  -5.91372605e-01  -3.19973052e-01\n",
      "  -5.99692170e-01  -8.48166470e-02  -4.95095435e-01  -2.71594270e-01\n",
      "  -5.13160820e-01  -5.66010178e-02  -3.96962458e-01  -8.29824985e-01\n",
      "   9.89053374e-02   1.68961658e-02  -2.25729416e-02   9.96083755e-01\n",
      "  -7.08690864e-01   9.94353126e-02  -4.10382179e-01  -4.41522922e-01\n",
      "  -5.63513750e-02  -7.98764988e-01   9.92912949e-02  -9.06570393e-01\n",
      "  -7.30813998e-01   3.55424994e-01  -2.17048490e-01  -6.57808096e-01\n",
      "  -8.54146396e-01  -3.38182257e-01  -8.98281268e-01   5.49050115e-01\n",
      "  -5.09076286e-01   1.05672405e-01  -3.90535058e-01  -1.84104860e-02\n",
      "  -5.48127470e-01   4.98535105e-01   1.76596277e-02  -3.20653513e-01\n",
      "  -5.16971649e-01  -6.78565635e-01  -4.41814389e-01  -5.07357114e-01\n",
      "  -4.19785692e-01  -6.85794616e-02   1.75287286e-01  -3.41950121e-01\n",
      "  -6.63653603e-01   2.85427905e-01   4.05728793e-02  -3.41133637e-01\n",
      "  -4.94563659e-01  -3.83239456e-01  -3.51461731e-01  -3.60172179e-01\n",
      "  -2.25548049e-01  -1.35517666e-01   3.04051275e-01  -6.20521172e-01\n",
      "  -5.34429873e-01  -6.06969817e-01  -2.64049672e-01   6.73255384e-03\n",
      "  -3.14808408e-01  -1.69265269e-01   1.57679574e-01  -5.69257420e-01\n",
      "  -3.49263939e-01  -3.13184383e-01  -4.65028082e-01   1.21444602e-03\n",
      "   1.13159869e-01  -3.70192012e-01   5.70390405e-01  -1.03362086e-01\n",
      "  -8.02469779e-01   5.70736072e-01  -9.03694482e-01  -3.40086169e-01\n",
      "   1.94975277e-01  -3.76277693e-01   2.61370739e-01  -1.35748554e-02]\n"
     ]
    }
   ],
   "source": [
    "# Try Bayesian Ridge Regression\n",
    "\n",
    "ridge_regressor = linear_model.BayesianRidge(normalize=True)\n",
    "ridge_regressor.fit(trainAllFeaturesCombined, score_array)\n",
    "\n",
    "# Test Rigde Regression on Test Data\n",
    "\n",
    "print('Ridge Regressor score: ' + str(ridge_regressor.score(testAllFeaturesCombined, testScorePruned)))\n",
    "print('Ridge Regressor prediction: ' + str(ridge_regressor.predict(testAllFeaturesCombined)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ensemble Regressor score: 0.0829749475567\n"
     ]
    }
   ],
   "source": [
    "# Try ensemble   Regression\n",
    "\n",
    "ensemble_regressor = ensemble.AdaBoostRegressor(base_estimator=ridge_regressor,loss='exponential',learning_rate=0.1)\n",
    "ensemble_regressor.fit(trainAllFeaturesCombined, score_array)\n",
    "\n",
    "# Test ensemble Regression on Test Data\n",
    "\n",
    "print('ensemble Regressor score: ' + str(ensemble_regressor.score(testAllFeaturesCombined, testScorePruned)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ensemble Regressor score: -0.212489547832\n"
     ]
    }
   ],
   "source": [
    "# Try ensemble   Regression\n",
    "\n",
    "ensemble_regressor = ensemble.BaggingRegressor(n_estimators=10, random_state=0)\n",
    "ensemble_regressor.fit(trainAllFeaturesCombined, score_array)\n",
    "\n",
    "# Test ensemble Regression on Test Data\n",
    "\n",
    "print('ensemble Regressor score: ' + str(ensemble_regressor.score(testAllFeaturesCombined, testScorePruned)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fileForReport= open(\"fileForReport.txt\",\"w+\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in range(len(predictedListOne)):\n",
    "     fileForReport.write(str(predictedListOne[i])+\"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fileForReport.close() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fileForReportTwo= open(\"fileForReportTwo.txt\",\"w+\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in range(len(predictedListTwo)):\n",
    "     fileForReportTwo.write(str(predictedListTwo[i])+\"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fileForReportTwo.close() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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