Document_classifciation_scikit.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Document Classification using Scikit"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pre-processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "import re\n",
    "from nltk.corpus import stopwords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#directory = \"/Users/ilabuser/TF/tensorflow_Data/Text_full\"\n",
    "directory = \"/home/praveen/Documents/Data/Text_full\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "f_names = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "filenames = os.listdir(directory)\n",
    "    \n",
    "for file in filenames:\n",
    "    f_name = os.path.join(directory, file)\n",
    "    f_names.append(f_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data_corpus = {}\n",
    "\n",
    "for f in filenames:\n",
    "    f_name = os.path.join(directory, f)\n",
    "    fi = open(f_name)\n",
    "    data = fi.read().lower()\n",
    "    data_corpus[f] = data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'united states of america\\nbefore the\\nsecurities and exchange commission\\nwashington, d.c. 20549\\nadministrative proceedings rulings\\nrelease no. 3815/april 29, 2016\\nadministrative proceeding\\nfile no. 3-17133\\n\\nin the matter of\\ntexstar oil corporation, and\\nbonamour, inc.\\n\\nstay order\\n\\ntoday, the parties filed a joint motion to stay this proceeding based upon their agreement\\nin principle to a settlement that will resolve the proceeding on all major terms.\\nfor good cause shown, it is ordered that the joint motion is granted, and the\\nproceeding is stayed, subject to compliance with rule of practice 161(c)(2), 17 c.f.r.\\n\\xc2\\xa7 201.161(c)(2), requiring that this office be notified promptly if any of the requirements of the\\nrule are not met.\\n_______________________________\\njason s. patil\\nadministrative law judge\\n\\n\\x0c'"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_corpus['ap-3815.pdf.txt']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data = pd.DataFrame.from_dict(data_corpus,orient='index')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data = data.reset_index()\n",
    "data.columns = ['file_name','text']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>file_name</th>\n",
       "      <th>text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ap-4081.pdf.txt</td>\n",
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       "      <th>1</th>\n",
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       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>id744cff.pdf.txt</td>\n",
       "      <td>initial decision release no. 744\\nadministrati...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ap-3748.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>33-10168.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>34-68988.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>33-10094.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>ap-3777.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>34-75165.pdf.txt</td>\n",
       "      <td>securities and exchange commission\\nrelease no...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>id302cff.pdf.txt</td>\n",
       "      <td>initial decision release no. 302\\nadministrati...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>ap-3776.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>34-53041.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>monyquiz.pdf.txt</td>\n",
       "      <td>test your\\n\\nmoney$ marts\\n\\nfacts on saving a...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>34-77739.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>33-10228.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>34-77423.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>34-77250.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>34-77013.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>34-70082.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>34-77288.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>ap-4044.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>sgtd.pdf.txt</td>\n",
       "      <td>2016 louisiana state government\\ntelephone di...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>id1047cff.pdf.txt</td>\n",
       "      <td>initial decision release no. 1047\\nadministrat...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>33-10225.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>ap-3492.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>34-72247.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>34-72505.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>ia-4455.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>ap-4000.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
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       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>34-69604-pdp.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
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       "      <th>3628</th>\n",
       "      <td>ap-4171.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
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       "    <tr>\n",
       "      <th>3629</th>\n",
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       "    <tr>\n",
       "      <th>3630</th>\n",
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       "    <tr>\n",
       "      <th>3631</th>\n",
       "      <td>34-79042-o.pdf.txt</td>\n",
       "      <td>united states of america\\nbefore the\\nsecuriti...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3632</th>\n",
       "      <td>comp23658.pdf.txt</td>\n",
       "      <td>case 1:16-cv-24106-jal document 1 entered on f...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3633</th>\n",
       "      <td>ap-4303.pdf.txt</td>\n",
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       "      <th>3634</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>3637</th>\n",
       "      <td>id328bpm.pdf.txt</td>\n",
       "      <td>initial decision release no. 328\\nadministrati...</td>\n",
       "    </tr>\n",
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       "      <th>3638</th>\n",
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       "      <th>3640</th>\n",
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       "      <th>3641</th>\n",
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       "      <td>securities and exchange commission\\n17 cfr par...</td>\n",
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       "      <th>3642</th>\n",
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       "      <th>3644</th>\n",
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       "      <td>united states of america \\n\\nbefore the \\n\\nse...</td>\n",
       "    </tr>\n",
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       "      <th>3646</th>\n",
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       "      <th>3647</th>\n",
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       "    <tr>\n",
       "      <th>3648</th>\n",
       "      <td>comp-pr2016-170.pdf.txt</td>\n",
       "      <td>case 2:16-cv-06427 document 1 filed 08/26/16 p...</td>\n",
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       "      <th>3649</th>\n",
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       "9     initial decision release no. 302\\nadministrati...  \n",
       "10    united states of america\\nbefore the\\nsecuriti...  \n",
       "11    united states of america\\nbefore the\\nsecuriti...  \n",
       "12    test your\\n\\nmoney$ marts\\n\\nfacts on saving a...  \n",
       "13    united states of america\\nbefore the\\nsecuriti...  \n",
       "14    united states of america\\nbefore the\\nsecuriti...  \n",
       "15    united states of america\\nbefore the\\nsecuriti...  \n",
       "16    united states of america\\nbefore the\\nsecuriti...  \n",
       "17    united states of america\\nbefore the\\nsecuriti...  \n",
       "18    united states of america\\nbefore the\\nsecuriti...  \n",
       "19    united states of america\\nbefore the\\nsecuriti...  \n",
       "20    united states of america\\nbefore the\\nsecuriti...  \n",
       "21    \f",
       "2016 louisiana state government\\ntelephone di...  \n",
       "22    initial decision release no. 1047\\nadministrat...  \n",
       "23    united states of america\\nbefore the\\nsecuriti...  \n",
       "24    united states of america\\nbefore the\\nsecuriti...  \n",
       "25    united states of america\\nbefore the\\nsecuriti...  \n",
       "26    united states of america\\nbefore the\\nsecuriti...  \n",
       "27    united states of america\\nbefore the\\nsecuriti...  \n",
       "28    united states of america\\nbefore the\\nsecuriti...  \n",
       "29    united states of america\\nbefore the\\nsecuriti...  \n",
       "...                                                 ...  \n",
       "3628  united states of america\\nbefore the\\nsecuriti...  \n",
       "3629  united states of america\\nbefore the\\nsecuriti...  \n",
       "3630  united states of america\\nbefore the\\nsecuriti...  \n",
       "3631  united states of america\\nbefore the\\nsecuriti...  \n",
       "3632  case 1:16-cv-24106-jal document 1 entered on f...  \n",
       "3633  united states of america\\nbefore the\\nsecuriti...  \n",
       "3634  united states of america\\nbefore the\\nsecuriti...  \n",
       "3635  united states of america\\nbefore the\\nsecuriti...  \n",
       "3636  united states of america\\nbefore the\\nsecuriti...  \n",
       "3637  initial decision release no. 328\\nadministrati...  \n",
       "3638  united states of america\\nbefore the\\nsecuriti...  \n",
       "3639  united states of america\\nbefore the\\nsecuriti...  \n",
       "3640  united states of america\\nbefore the\\nsecuriti...  \n",
       "3641  securities and exchange commission\\n17 cfr par...  \n",
       "3642  united states of america\\nbefore the\\nsecuriti...  \n",
       "3643  united states of america\\nbefore the\\nsecuriti...  \n",
       "3644  initial decision release no. 940\\nadministrati...  \n",
       "3645  united states of america \\n\\nbefore the \\n\\nse...  \n",
       "3646  u.s. securities and exchange commission\\nwashi...  \n",
       "3647  united states of america\\nbefore the\\nsecuriti...  \n",
       "3648  case 2:16-cv-06427 document 1 filed 08/26/16 p...  \n",
       "3649  united states of america \\n\\nbefore the\\n\\nsec...  \n",
       "3650  united states of america\\nbefore the\\nsecuriti...  \n",
       "3651  securities and exchange commission\\n17 cfr par...  \n",
       "3652  united states of america\\nbefore the\\nsecuriti...  \n",
       "3653  united states of america\\nbefore the\\nsecuriti...  \n",
       "3654  united states of america\\nbefore the\\nsecuriti...  \n",
       "3655  united states of america \\n\\nbefore the \\n\\nse...  \n",
       "3656  united states of america\\nbefore the\\nsecuriti...  \n",
       "3657  united states of america\\nbefore the\\nsecuriti...  \n",
       "\n",
       "[3658 rows x 2 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def clean_text(raw_text):\n",
    "    letters_only = re.sub(\"[^a-z]\", \" \", raw_text)\n",
    "    words = letters_only.split()\n",
    "    stops = set(stopwords.words(\"english\"))\n",
    "    meaningful_words = [w for w in words if not w in stops and len(w)>1]\n",
    "    return( \" \".join( meaningful_words ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[u'i', u'me', u'my', u'myself', u'we', u'our', u'ours', u'ourselves', u'you', u'your', u'yours', u'yourself', u'yourselves', u'he', u'him', u'his', u'himself', u'she', u'her', u'hers', u'herself', u'it', u'its', u'itself', u'they', u'them', u'their', u'theirs', u'themselves', u'what', u'which', u'who', u'whom', u'this', u'that', u'these', u'those', u'am', u'is', u'are', u'was', u'were', u'be', u'been', u'being', u'have', u'has', u'had', u'having', u'do', u'does', u'did', u'doing', u'a', u'an', u'the', u'and', u'but', u'if', u'or', u'because', u'as', u'until', u'while', u'of', u'at', u'by', u'for', u'with', u'about', u'against', u'between', u'into', u'through', u'during', u'before', u'after', u'above', u'below', u'to', u'from', u'up', u'down', u'in', u'out', u'on', u'off', u'over', u'under', u'again', u'further', u'then', u'once', u'here', u'there', u'when', u'where', u'why', u'how', u'all', u'any', u'both', u'each', u'few', u'more', u'most', u'other', u'some', u'such', u'no', u'nor', u'not', u'only', u'own', u'same', u'so', u'than', u'too', u'very', u's', u't', u'can', u'will', u'just', u'don', u'should', u'now', u'd', u'll', u'm', u'o', u're', u've', u'y', u'ain', u'aren', u'couldn', u'didn', u'doesn', u'hadn', u'hasn', u'haven', u'isn', u'ma', u'mightn', u'mustn', u'needn', u'shan', u'shouldn', u'wasn', u'weren', u'won', u'wouldn']\n"
     ]
    }
   ],
   "source": [
    "print stopwords.words(\"english\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data['text_clean'] = data['text'].apply(clean_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'united states of america\\nbefore the\\nsecurities and exchange commission\\nwashington, d.c. 20549\\nadministrative proceedings rulings\\nrelease no. 4081/august 22, 2016\\nadministrative proceeding\\nfile no. 3-17376\\n\\nin the matter of\\neastland financial corp.,\\ngranite cliffs, incorporated, and\\ngreater asia realty holdings, ltd.\\n\\norder postponing hearing and\\nscheduling prehearing\\nconference\\n\\non august 10, 2016, the securities and exchange commission issued an order instituting\\nproceedings (oip) against respondents pursuant to section 12(j) of the securities exchange act\\nof 1934. the hearing is scheduled to commence on august 29, 2016.\\non august 18, 2016, the division of enforcement filed a declaration of service\\nestablishing that respondents were served with the oip by u.s. postal service express mail on\\naugust 15, 2016, in accordance with rule of practice 141(a)(2)(ii), 17 c.f.r. \\xc2\\xa7 201.141(a)(ii).\\nrespondents\\xe2\\x80\\x99 answers are due by august 29, 2016. oip at 3; 17 c.f.r. \\xc2\\xa7\\xc2\\xa7 201.160(a)-(b),\\n.220(b).\\ni order that the hearing scheduled for august 29, 2016, is postponed and a\\ntelephonic prehearing conference shall be held at 3:30 p.m. edt on september 12, 2016. any\\nrespondent that fails to timely file an answer, appear at the prehearing conference, or otherwise\\ndefend the proceeding will be deemed in default and the registration of its securities will be\\nrevoked. oip at 3; 17 c.f.r. \\xc2\\xa7\\xc2\\xa7 201.155(a), .220(f), .221(f).\\n\\n_______________________________\\njames e. grimes\\nadministrative law judge\\n\\n\\x0c'"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['text'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'united states america securities exchange commission washington administrative proceedings rulings release august administrative proceeding file matter eastland financial corp granite cliffs incorporated greater asia realty holdings ltd order postponing hearing scheduling prehearing conference august securities exchange commission issued order instituting proceedings oip respondents pursuant section securities exchange act hearing scheduled commence august august division enforcement filed declaration service establishing respondents served oip postal service express mail august accordance rule practice ii ii respondents answers due august oip order hearing scheduled august postponed telephonic prehearing conference shall held edt september respondent fails timely file answer appear prehearing conference otherwise defend proceeding deemed default registration securities revoked oip james grimes administrative law judge'"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['text_clean'][0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Creating TF-IDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import sklearn as sk\n",
    "import scipy as sc\n",
    "import numpy as np\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "vectorizer = TfidfVectorizer(analyzer = \"word\",   \\\n",
    "                             tokenizer = None,    \\\n",
    "                             preprocessor = None, \\\n",
    "                             stop_words = None,   \\\n",
    "                             max_features = 5000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "train_data_features = vectorizer.fit_transform(data['text_clean'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<3658x5000 sparse matrix of type '<type 'numpy.float64'>'\n",
       "\twith 1602635 stored elements in Compressed Sparse Row format>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3658, 5000)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data_features.get_shape()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train_data_norm = sk.preprocessing.normalize(train_data_features,norm='l1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "train_data_np = train_data_norm.toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.99999999999999956"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(train_data_np[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[u'aa', u'aaer', u'aaron', u'ab', u'aba', u'abcp', u'abetted', u'abetting', u'ability', u'able', u'abroad', u'abs', u'absence', u'absent', u'absolute', u'abuse', u'abuses', u'abusive', u'abx', u'ac', u'academic', u'accelerated', u'accept', u'acceptable', u'acceptance', u'accepted', u'accepting', u'access', u'accessed', u'accessible', u'accho', u'accommodate', u'accommodation', u'accompanied', u'accompanying', u'accomplish', u'accomplished', u'accord', u'accordance', u'according', u'accordingly', u'account', u'accountability', u'accountant', u'accountants', u'accounted', u'accountholder', u'accountholders', u'accounting', u'accounts', u'accredited', u'accrual', u'accrue', u'accrued', u'accumulated', u'accuracy', u'accurate', u'accurately', u'ach', u'achieve', u'achieved', u'achievement', u'achieving', u'acknowledge', u'acknowledged', u'acknowledges', u'acknowledgment', u'acquire', u'acquired', u'acquiring', u'acquisition', u'acquisitions', u'across', u'act', u'acted', u'acting', u'action', u'actions', u'active', u'actively', u'activities', u'activity', u'actor', u'actors', u'acts', u'actual', u'actually', u'ad', u'adams', u'add', u'added', u'adding', u'addition', u'additional', u'additionally', u'additions', u'address', u'addressed', u'addresses', u'addressing', u'adequacy', u'adequate', u'adequately', u'adhere', u'adjust', u'adjusted', u'adjustment', u'adjustments', u'admin', u'administer', u'administered', u'administering', u'administration', u'administrative', u'administrator', u'administrators', u'admission', u'admissions', u'admitted', u'admitting', u'adopt', u'adopted', u'adopting', u'adoption', u'adv', u'advance', u'advanced', u'advances', u'advantage', u'advantages', u'adverse', u'adversely', u'advertisement', u'advertisements', u'advertising', u'advice', u'advise', u'advised', u'adviser', u'advisers', u'advising', u'advisor', u'advisors', u'advisory', u'advocate', u'afc', u'aff', u'affairs', u'affect', u'affected', u'affecting', u'affiliate', u'affiliated', u'affiliates', u'affirmative', u'affirmed', u'afford', u'afforded', u'afr', u'africa', u'african', u'ag', u'age', u'agencies', u'agency', u'agenda', u'agent', u'agents', u'aggregate', u'aggregated', u'aggregating', u'aggregation', u'aggressive', u'ago', u'agree', u'agreed', u'agreeing', u'agreement', u'agreements', u'agrees', u'ai', u'aicpa', u'aid', u'aided', u'aiding', u'aids', u'aim', u'aimed', u'aims', u'air', u'airport', u'al', u'alabama', u'aladdin', u'alaska', u'albert', u'alert', u'alger', u'algorithm', u'align', u'aligned', u'alignment', u'alj', u'allegation', u'allegations', u'alleged', u'allegedly', u'alleges', u'alleging', u'allen', u'alliance', u'allocate', u'allocated', u'allocation', u'allocations', u'allow', u'allowance', u'allowances', u'allowed', u'allowing', u'allows', u'almost', u'alone', u'along', u'alpha', u'alphasector', u'already', u'also', u'alter', u'alternate', u'alternative', u'alternatively', u'alternatives', u'although', u'always', u'amend', u'amended', u'amending', u'amendment', u'amendments', u'america', u'american', u'ameriprise', u'amex', u'amicus', u'among', u'amortization', u'amortized', u'amount', u'amounted', u'amounts', u'amz', u'analyses', u'analysis', u'analyst', u'analysts', u'analytical', u'analyze', u'analyzed', u'analyzing', u'anc', u'ancillary', u'anddesist', u'anderson', u'andrew', u'angel', u'angeles', u'announced', u'announcement', u'annual', u'annualized', u'annually', u'annuities', u'annuity', u'anonymous', u'another', u'answer', u'answered', u'answers', u'anthony', u'anti', u'anticipate', u'anticipated', u'anticipates', u'anticipation', u'antifraud', u'anyone', u'anything', u'ap', u'api', u'app', u'apparent', u'appeal', u'appealed', u'appeals', u'appear', u'appearance', u'appeared', u'appearing', u'appears', u'appellant', u'appellants', u'appellate', u'appendix', u'applicability', u'applicable', u'applicant', u'applicants', u'application', u'applications', u'applied', u'applies', u'apply', u'applying', u'appoint', u'appointed', u'appointing', u'appointment', u'appointments', u'appraisal', u'appreciation', u'approach', u'approaches', u'appropriate', u'appropriately', u'appropriation', u'appropriations', u'approval', u'approve', u'approved', u'approving', u'approximate', u'approximately', u'apr', u'april', u'aq', u'ar', u'arbitrage', u'arbitration', u'arca', u'area', u'areas', u'argue', u'argued', u'argues', u'arguing', u'argument', u'arguments', u'arise', u'arises', u'arising', u'arizona', u'arkansas', u'arm', u'armt', u'arose', u'around', u'arp', u'arrange', u'arranged', u'arrangement', u'arrangements', u'arthur', u'article', u'articles', u'artifice', u'asc', u'ascertain', u'asf', u'asia', u'aside', u'ask', u'asked', u'asking', u'aspect', u'aspects', u'ass', u'assert', u'asserted', u'asserting', u'assertion', u'assess', u'assessed', u'assessing', u'assessment', u'assessments', u'asset', u'assets', u'assign', u'assigned', u'assignment', u'assignments', u'assist', u'assistance', u'assistant', u'assisted', u'assisting', u'associate', u'associated', u'associates', u'associating', u'association', u'associations', u'asst', u'asstt', u'assume', u'assumed', u'assumes', u'assuming', u'assumption', u'assumptions', u'assurance', u'assurances', u'assure', u'atlanta', u'ats', u'atss', u'attach', u'attached', u'attachment', u'attachments', u'attempt', u'attempted', u'attempting', u'attempts', u'attend', u'attendance', u'attended', u'attention', u'attestation', u'attorney', u'attorneys', u'attract', u'attractive', u'attributable', u'attributed', u'au', u'auction', u'audit', u'audited', u'auditing', u'auditor', u'auditors', u'audits', u'aug', u'august', u'aurum', u'authorised', u'authorities', u'authority', u'authorization', u'authorizations', u'authorize', u'authorized', u'authorizes', u'authorizing', u'auto', u'automated', u'automatic', u'automatically', u'automobile', u'avail', u'availability', u'available', u'ave', u'avenue', u'average', u'avoid', u'avoidance', u'avoided', u'avoiding', u'award', u'awarded', u'awards', u'aware', u'awareness', u'away', u'ba', u'back', u'backed', u'background', u'backloading', u'backup', u'bad', u'balance', u'balanced', u'balances', u'baltimore', u'bank', u'bankers', u'banking', u'bankruptcy', u'banks', u'bar', u'barclays', u'bargaining', u'barred', u'barriers', u'barring', u'bars', u'base', u'based', u'basel', u'baseline', u'basic', u'basis', u'basket', u'bats', u'bay', u'bb', u'bd', u'bds', u'beach', u'bear', u'bearing', u'became', u'becc', u'become', u'becomes', u'becoming', u'began', u'begin', u'beginning', u'begins', u'behalf', u'behavior', u'behaviour', u'behind', u'belief', u'believe', u'believed', u'believes', u'benchmark', u'beneficial', u'beneficially', u'beneficiaries', u'beneficiary', u'benefit', u'benefits', u'bennett', u'best', u'beta', u'better', u'beyond', u'bhc', u'bid', u'bidding', u'bids', u'big', u'bilateral', u'bill', u'billion', u'bills', u'binding', u'bit', u'black', 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u'referenced', u'references', u'referencing', u'referral', u'referrals', u'referred', u'referring', u'refers', u'reflect', u'reflected', u'reflecting', u'reflects', u'reform', u'reforms', u'refund', u'refusal', u'refused', u'reg', u'regard', u'regarding', u'regardless', u'regime', u'regimes', u'region', u'regional', u'register', u'registered', u'registering', u'registrant', u'registrants', u'registration', u'registrations', u'regular', u'regularly', u'regulate', u'regulated', u'regulating', u'regulation', u'regulations', u'regulator', u'regulators', u'regulatory', u'rehearing', u'reimbursement', u'reinstatement', u'reject', u'rejected', u'rel', u'relate', u'related', u'relates', u'relating', u'relation', u'relations', u'relationship', u'relationships', u'relative', u'relatively', u'release', u'released', u'releases', u'relevant', u'reliability', u'reliable', u'reliance', u'relied', u'relief', u'relies', u'rely', u'relying', u'remain', u'remainder', u'remained', u'remaining', u'remains', u'remanded', u'remedial', u'remedies', u'remedy', u'remote', u'removal', u'remove', u'removed', u'removing', u'remuneration', u'render', u'rendered', u'renewal', u'reorganization', u'reorganizations', u'reorganized', u'rep', u'repay', u'repayment', u'repeated', u'repeatedly', u'replace', u'replaced', u'replacement', u'replacing', u'reply', u'report', u'reportable', u'reported', u'reporting', u'reports', u'repositories', u'repository', u'represent', u'representation', u'representations', u'representative', u'representatives', u'represented', u'representing', u'represents', u'reproposal', u'republic', u'repurchase', u'reputation', u'request', u'requested', u'requesting', u'requests', u'require', u'required', u'requirement', u'requirements', u'requires', u'requiring', u'requisite', u'resale', u'resales', u'rescission', u'research', u'reserve', u'reserved', u'reserves', u'residence', u'resident', u'residential', u'residents', u'resides', u'residual', u'resignation', u'resigned', u'resolution', u'resolve', u'resolved', u'resolving', u'resource', u'resources', u'resp', u'respect', u'respectfully', u'respective', u'respectively', u'respects', u'respond', u'responded', u'respondent', u'respondents', u'responding', u'response', u'responses', u'responsibilities', u'responsibility', u'responsible', u'responsive', u'rest', u'restated', u'restatement', u'restitution', u'restraining', u'restrict', u'restricted', u'restriction', u'restrictions', u'restructuring', u'result', u'resulted', u'resulting', u'results', u'retail', u'retain', u'retained', u'retaining', u'retains', u'retaliation', u'retention', u'retired', u'retirement', u'return', u'returned', u'returns', u'rev', u'reveal', u'revealed', u'revenue', u'revenues', u'reverse', u'reversed', u'review', u'reviewed', u'reviewing', u'reviews', u'revise', u'revised', u'revising', u'revision', u'revisions', u'revocation', u'revoke', u'revoked', u'revolving', u'reward', u'rewards', u'rfa', u'ri', u'riad', u'richard', u'right', u'rights', u'rise', u'risk', u'risks', u'risky', u'river', u'rmbs', u'rn', u'road', u'robert', u'roberts', u'robust', u'rogers', u'role', u'roles', u'room', u'rose', u'ross', u'round', u'rounding', u'roundtable', u'route', u'routed', u'routine', u'routinely', u'routing', u'rowe', u'royal', u'royalty', u'rpm', u'rs', u'ruby', u'rule', u'rulemaking', u'rules', u'ruling', u'rulings', u'run', u'running', u'rural', u'russell', u'rust', u'sa', u'sachs', u'safe', u'safeguards', u'safety', u'said', u'salaries', u'salary', u'sale', u'sales', u'salt', u'salutric', u'sample', u'sampling', u'san', u'sanction', u'sanctions', u'santa', u'sar', u'sarbanes', u'sasb', u'satisfaction', u'satisfactory', u'satisfied', u'satisfies', u'satisfy', u'satisfying', u'saving', u'savings', u'say', u'sb', u'sbs', u'sbsd', u'sbsds', u'sbse', u'sbsr', u'sc', u'scale', u'scaled', u'scenario', u'scenarios', u'schedule', u'scheduled', u'schedules', u'scheduling', u'scheme', u'schemes', u'school', u'schools', u'schwab', u'sci', u'science', u'sciences', u'scienter', u'scope', u'score', u'scott', u'scp', u'scrutiny', u'sd', u'sdr', u'sdrs', u'se', u'search', u'sears', u'sec', u'second', u'secondary', u'secretary', u'section', u'sections', u'sector', u'secunnes', u'secunties', u'secuntres', u'secure', u'secured', u'securing', u'securities', u'securitization', u'securitizations', u'securitized', u'security', u'securitybased', u'securityholders', u'see', u'seek', u'seeking', u'seeks', u'seems', u'seen', u'sef', u'sefs', u'segment', u'segments', u'segregated', u'segregation', u'select', u'selected', u'selecting', u'selection', u'self', u'sell', u'seller', u'sellers', u'selling', u'sells', u'semi', u'sen', u'senate', u'send', u'sending', u'senior', u'sense', u'sensitive', u'sensitivity', u'sent', u'sentence', u'sentenced', u'separate', u'separately', u'separation', u'sept', u'september', u'seq', u'sergeant', u'series', u'serious', u'serve', u'served', u'serves', u'service', u'servicer', u'services', u'servicing', u'serving', u'sess', u'session', u'sessions', u'set', u'sets', u'setting', u'settle', u'settled', u'settlement', u'settlements', u'seven', u'seventh', u'several', u'severe', u'sexual', u'sf', u'sfas', u'shall', u'share', u'shared', u'shareholder', u'shareholders', u'shares', u'sharing', u'sharma', u'sheet', u'sheets', u'shelf', u'shell', u'shift', u'shimla', u'shop', u'short', u'shorter', u'shortfall', u'shortly', u'show', u'showed', u'showing', u'shown', u'shows', u'shrm', u'shtml', u'sic', u'sick', u'side', u'sides', u'sifma', u'sign', u'signature', u'signatures', u'signed', u'significance', u'significant', u'significantly', u'signing', u'silver', u'similar', u'similarly', u'simple', u'simplification', u'simplify', u'simply', u'simultaneously', u'since', u'singh', u'single', u'sion', u'sipa', u'sipc', u'site', u'sites', u'situation', u'situations', u'six', u'sixth', u'sixty', u'size', u'sizes', u'skill', u'skills', u'slc', u'slightly', u'small', u'smaller', u'smith', u'sncoic', u'snrfor', u'socents', u'social', u'society', u'soft', u'software', u'sold', u'sole', u'solely', u'solicit', u'solicitation', u'solicitations', u'solicited', u'soliciting', u'solicitor', u'solution', u'solutions', u'someone', u'something', u'sometimes', u'somewhat', u'son', u'soon', u'sophisticated', u'sophistication', u'sort', u'sought', u'sound', u'soundness', u'source', u'sources', u'south', u'southern', u'sovereign', u'space', u'special', u'specialist', u'specialists', u'specialized', u'specific', u'specifically', u'specification', u'specifications', u'specified', u'specifies', u'specify', u'specifying', u'speculative', u'speech', u'speed', u'spend', u'spent', u'split', u'spokane', u'sponsor', u'sponsored', u'sponsors', u'sports', u'spouse', u'spread', u'spreads', u'springs', u'spruce', u'squared', u'sr', u'srcs', u'sro', u'sros', u'ss', u'ssion', u'st', u'sta', u'stability', u'stabilizing', u'stable', u'staff', u'staffing', u'stage', u'stages', u'stakeholders', u'stale', u'stand', u'standard', u'standardized', u'standards', u'standing', u'stanley', u'start', u'started', u'starting', u'startup', u'startups', u'stat', u'state', u'stated', u'statement', u'statements', u'states', u'static', u'stating', u'station', u'statistical', u'statistics', u'status', u'statute', u'statutes', u'statutory', u'stay', u'stayed', u'steadman', u'step', u'stephen', u'steps', u'steven', u'still', u'stock', u'stockholder', u'stockholders', u'stocks', u'stolen', u'stop', u'storage', u'stores', u'strategic', u'strategies', u'strategy', u'street', u'strength', u'strengthen', u'stress', u'stressed', u'strict', u'strike', u'striking', u'strong', u'strongly', u'structural', u'structure', u'structured', u'structures', u'student', u'students', u'studies', u'study', u'sub', u'subcommittee', u'subdivision', u'subject', u'subjects', u'submission', u'submissions', u'submit', u'submits', u'submitted', u'submitting', u'subordinated', u'subparagraph', u'subpart', u'subpoena', u'subpoenas', u'subscriber', u'subscribers', u'subscription', u'subsec', u'subsection', u'subsections', u'subsequent', u'subsequently', u'subsidiaries', u'subsidiary', u'substance', u'substantial', u'substantially', u'substantive', u'substitute', u'substituted', u'subtitle', u'success', u'successful', u'successfully', u'succession', u'successor', u'suffered', u'sufficient', u'sufficiently', u'suggest', u'suggested', u'suggesting', u'suggestion', u'suggestions', u'suggests', u'suisse', u'suit', u'suitability', u'suitable', u'suite', u'suits', u'sum', u'summarized', u'summary', u'summer', u'supervise', u'supervised', u'supervision', u'supervisor', u'supervisors', u'supervisory', u'supp', u'supplement', u'supplemental', u'supplementary', u'supplied', u'supply', u'support', u'supported', u'supporting', u'supports', u'supra', u'supreme', u'sure', u'surplus', u'surrounding', u'surveillance', u'survey', u'surveys', u'susan', u'suspend', u'suspended', u'suspending', u'suspension', u'sustainability', u'sustained', u'swap', u'swaps', u'swift', u'swing', u'swisher', u'swiss', u'sworn', u'symbol', u'syndicate', u'system', u'systemic', u'systemically', u'systems', u'ta', u'table', u'tables', u'tagliaferri', u'tailored', u'take', u'taken', u'taker', u'takers', u'takes', u'taking', u'talent', u'target', u'targeted', u'targets', u'task', u'tasks', u'tax', u'taxes', u'taylor', u'tbe', u'tchr', u'teacher', u'teachers', u'teaching', u'team', u'teams', u'tech', u'technical', u'technician', u'techniques', u'technological', u'technologies', u'technology', u'telecommunications', u'telefax', u'telephone', u'telephonic', u'tell', u'template', u'temporarily', u'temporary', u'ten', u'tend', u'tender', u'tennessee', u'tenth', u'tenure', u'teo', u'term', u'terminate', u'terminated', u'terminating', u'termination', u'terms', u'territory', u'test', u'tested', u'testified', u'testify', u'testimony', u'testing', u'tests', u'tex', u'texas', u'text', u'th', u'thakur', u'theft', u'theory', u'thereafter', u'thereby', u'therefor', u'therefore', u'therein', u'thereof', u'thereon', u'thereto', u'thereunder', u'therewith', u'thing', u'things', u'think', u'third', u'thirty', u'thomas', u'thompson', u'thorough', u'though', u'thought', u'thousand', u'thousands', u'threat', u'three', u'threshold', u'thresholds', u'thrift', u'throughout', u'thus', u'ti', u'ticker', u'tier', u'ties', u'time', u'timeframe', u'timeframes', u'timely', u'timer', u'timers', u'times', u'timing', u'timothy', u'tion', u'tions', u'title', u'tiw', u'tl', u'today', u'together', u'told', u'toll', u'took', u'tool', u'tools', u'top', u'topic', u'topics', u'tor', u'total', u'totaled', u'totaling', u'totals', u'toward', u'towards', u'town', u'tp', u'tr', u'track', u'tracking', u'trade', u'traded', u'trader', u'traders', u'trades', u'trading', u'traditional', u'training', u'tranche', u'tranches', u'transact', u'transacting', u'transaction', u'transactions', u'transcript', u'transfer', u'transferred', u'transferring', u'transfers', u'transition', u'transmission', u'transmit', u'transmitted', u'transparency', u'transparent', u'transport', u'transportation', u'travel', u'treasurer', u'treasury', u'treat', u'treated', u'treatment', u'trend', u'trends', u'trial', u'trigger', u'triggered', u'triggering', u'trillion', u'true', u'trust', u'trustee', u'trustees', u'trusts', u'truth', u'try', u'ts', u'tsai', u'turn', u'turnover', u'twelve', u'twenty', u'twice', u'two', u'tx', u'type', u'types', u'typical', u'typically', u'ubs', u'uic', u'uics', u'uit', u'uits', u'uk', u'ultimate', u'ultimately', u'un', u'unable', u'unacceptable', u'unaffiliated', u'unaudited', u'unauthorized', u'unavailable', u'uncertainty', u'unclear', u'unconsolidated', u'underlying', u'undermine', u'undersigned', u'understand', u'understanding', u'understands', u'understood', u'undertake', u'undertaken', u'undertakes', u'undertaking', u'undertakings', u'undertook', u'underwriter', u'underwriters', u'underwriting', u'undisclosed', u'undue', u'unduly', u'unesco', u'unfair', u'uniform', u'union', u'unions', u'unique', u'unit', u'united', u'units', u'universal', u'university', u'unknown', u'unlawful', u'unless', u'unlike', u'unlikely', u'unlisted', u'unnecessary', u'unpaid', u'unrealized', u'unreasonable', u'unregistered', u'unrelated', u'unsecured', u'untrue', u'unusual', u'update', u'updated', u'updates', u'updating', u'upheld', u'upon', u'upper', u'ups', u'uranium', u'urban', u'urged', u'urging', u'url', u'us', u'usa', u'usage', u'usc', u'usd', u'use', u'used', u'useful', u'usefulness', u'user', u'users', u'uses', u'using', u'usual', u'usually', u'ut', u'utah', u'util', u'utilities', u'utility', u'utilize', u'utilized', u'va', u'vacant', u'vacate', u'vacated', u'vacation', u'valid', u'validated', u'validation', u'validity', u'valley', u'valuable', u'valuation', u'valuations', u'value', u'valued', u'values', u'van', u'vanguard', u'var', u'variable', u'variables', u'variance', u'variation', u'variety', u'various', u'vary', u'varying', u'vast', u'vault', u'vehicle', u'vehicles', u'vendor', u'vendors', u'venture', u'ventures', u'venue', u'venues', u'verification', u'verified', u'verify', u'version', u'versus', u'vertical', u'vested', u'vesting', u'vi', u'via', u'vice', u'victims', u'view', u'viewed', u'views', u'vii', u'viii', u'violate', u'violated', u'violates', u'violating', u'violation', u'violations', u'virginia', u'virtually', u'virtue', u'vision', u'visited', u'voice', u'void', u'vol', u'volatility', u'volume', u'volumes', u'voluntarily', u'voluntary', u'vote', u'votes', u'voting', u'vwo', u'waddell', u'wage', u'waiting', u'waived', u'waiver', u'wall', u'wallace', u'want', u'wanted', u'war', u'warehouse', u'warning', u'warrant', u'warranted', u'warranties', u'warrants', u'wash', u'washington', u'waste', u'water', u'waterfall', u'way', u'ways', u'weakness', u'weaknesses', u'wealth', u'weatherford', u'web', u'website', u'websites', u'week', u'weekly', u'weeks', u'weight', u'weighted', u'welfare', u'well', u'wells', u'went', u'west', u'western', u'whatever', u'whenever', u'whereas', u'whereby', u'whether', u'whichever', u'whistleblower', u'white', u'whole', u'wholly', u'whose', u'wide', u'widely', u'widespread', u'wife', u'willful', u'willfully', u'william', u'williams', u'willing', u'willingness', u'wilson', u'wire', u'wisconsin', u'wish', u'wishes', u'withdraw', u'withdrawal', u'withdrawals', u'withdrawn', u'withdrew', u'within', u'without', u'witness', u'witnesses', u'wl', u'wmma', u'women', u'word', u'words', u'work', u'worked', u'worker', u'workers', u'workforce', u'working', u'workload', u'workplace', u'works', u'world', u'worldwide', u'worth', u'would', u'writ', u'write', u'writing', u'written', u'wrong', u'wrongdoing', u'wrongful', u'wrote', u'www', u'xbrl', u'xi', u'xii', u'xml', u'xr', u'xs', u'xv', u'xxxx', u'year', u'years', u'yes', u'yet', u'yield', u'york', u'young', u'yyyy', u'zero', u'ziff']\n"
     ]
    }
   ],
   "source": [
    "vocab = vectorizer.get_feature_names()\n",
    "print vocab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "tf_idf_sum = np.sum(train_data_np, axis=0)\n",
    "tf_idf_sum_vocab = pd.DataFrame(data=zip(vocab, tf_idf_sum),columns=['word','tf_idf_sum'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>word</th>\n",
       "      <th>tf_idf_sum</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>880</th>\n",
       "      <td>commission</td>\n",
       "      <td>44.259485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4115</th>\n",
       "      <td>securities</td>\n",
       "      <td>32.383551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1759</th>\n",
       "      <td>exchange</td>\n",
       "      <td>27.794489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>act</td>\n",
       "      <td>25.976008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3191</th>\n",
       "      <td>order</td>\n",
       "      <td>24.395054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>administrative</td>\n",
       "      <td>22.251917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3933</th>\n",
       "      <td>respondent</td>\n",
       "      <td>21.829830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2328</th>\n",
       "      <td>inc</td>\n",
       "      <td>19.825167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3641</th>\n",
       "      <td>pursuant</td>\n",
       "      <td>17.526223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2055</th>\n",
       "      <td>fund</td>\n",
       "      <td>16.596214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4106</th>\n",
       "      <td>section</td>\n",
       "      <td>16.528808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3934</th>\n",
       "      <td>respondents</td>\n",
       "      <td>15.968473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3140</th>\n",
       "      <td>oip</td>\n",
       "      <td>15.936158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2186</th>\n",
       "      <td>hearing</td>\n",
       "      <td>15.891593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3523</th>\n",
       "      <td>proceeding</td>\n",
       "      <td>15.566723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3524</th>\n",
       "      <td>proceedings</td>\n",
       "      <td>15.512453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4027</th>\n",
       "      <td>rule</td>\n",
       "      <td>14.842506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3377</th>\n",
       "      <td>plan</td>\n",
       "      <td>14.553958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2558</th>\n",
       "      <td>judge</td>\n",
       "      <td>13.790803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1924</th>\n",
       "      <td>file</td>\n",
       "      <td>13.741229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1469</th>\n",
       "      <td>distribution</td>\n",
       "      <td>13.287156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1247</th>\n",
       "      <td>decision</td>\n",
       "      <td>13.248583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3831</th>\n",
       "      <td>release</td>\n",
       "      <td>13.038717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3451</th>\n",
       "      <td>prehearing</td>\n",
       "      <td>12.821543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1483</th>\n",
       "      <td>division</td>\n",
       "      <td>12.224732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2619</th>\n",
       "      <td>law</td>\n",
       "      <td>12.148586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4102</th>\n",
       "      <td>sec</td>\n",
       "      <td>11.623358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>981</th>\n",
       "      <td>conference</td>\n",
       "      <td>11.566034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4031</th>\n",
       "      <td>rulings</td>\n",
       "      <td>11.416039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2826</th>\n",
       "      <td>may</td>\n",
       "      <td>11.174153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1912</th>\n",
       "      <td>fia</td>\n",
       "      <td>0.014496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3987</th>\n",
       "      <td>revolving</td>\n",
       "      <td>0.014417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1174</th>\n",
       "      <td>csd</td>\n",
       "      <td>0.014192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2804</th>\n",
       "      <td>markit</td>\n",
       "      <td>0.013736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2259</th>\n",
       "      <td>ias</td>\n",
       "      <td>0.013555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4129</th>\n",
       "      <td>sefs</td>\n",
       "      <td>0.013544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4987</th>\n",
       "      <td>xs</td>\n",
       "      <td>0.013515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4513</th>\n",
       "      <td>takers</td>\n",
       "      <td>0.013268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4069</th>\n",
       "      <td>sbsd</td>\n",
       "      <td>0.012801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2073</th>\n",
       "      <td>gamma</td>\n",
       "      <td>0.012607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>629</th>\n",
       "      <td>bunched</td>\n",
       "      <td>0.012525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3354</th>\n",
       "      <td>pf</td>\n",
       "      <td>0.012234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1491</th>\n",
       "      <td>docx</td>\n",
       "      <td>0.012130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368</th>\n",
       "      <td>asf</td>\n",
       "      <td>0.011767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447</th>\n",
       "      <td>authorised</td>\n",
       "      <td>0.011712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>abcp</td>\n",
       "      <td>0.011626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3105</th>\n",
       "      <td>occupy</td>\n",
       "      <td>0.011564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2100</th>\n",
       "      <td>giver</td>\n",
       "      <td>0.011128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>357</th>\n",
       "      <td>arp</td>\n",
       "      <td>0.011021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1334</th>\n",
       "      <td>depts</td>\n",
       "      <td>0.010912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3889</th>\n",
       "      <td>reproposal</td>\n",
       "      <td>0.010539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4288</th>\n",
       "      <td>soundness</td>\n",
       "      <td>0.010520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4436</th>\n",
       "      <td>subtitle</td>\n",
       "      <td>0.009947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2970</th>\n",
       "      <td>msbsp</td>\n",
       "      <td>0.009484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511</th>\n",
       "      <td>bds</td>\n",
       "      <td>0.008998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>544</th>\n",
       "      <td>bhc</td>\n",
       "      <td>0.008540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3071</th>\n",
       "      <td>novation</td>\n",
       "      <td>0.006325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>481</th>\n",
       "      <td>backloading</td>\n",
       "      <td>0.004382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>948</th>\n",
       "      <td>compression</td>\n",
       "      <td>0.004267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4986</th>\n",
       "      <td>xr</td>\n",
       "      <td>0.004101</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5000 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                word  tf_idf_sum\n",
       "880       commission   44.259485\n",
       "4115      securities   32.383551\n",
       "1759        exchange   27.794489\n",
       "73               act   25.976008\n",
       "3191           order   24.395054\n",
       "113   administrative   22.251917\n",
       "3933      respondent   21.829830\n",
       "2328             inc   19.825167\n",
       "3641        pursuant   17.526223\n",
       "2055            fund   16.596214\n",
       "4106         section   16.528808\n",
       "3934     respondents   15.968473\n",
       "3140             oip   15.936158\n",
       "2186         hearing   15.891593\n",
       "3523      proceeding   15.566723\n",
       "3524     proceedings   15.512453\n",
       "4027            rule   14.842506\n",
       "3377            plan   14.553958\n",
       "2558           judge   13.790803\n",
       "1924            file   13.741229\n",
       "1469    distribution   13.287156\n",
       "1247        decision   13.248583\n",
       "3831         release   13.038717\n",
       "3451      prehearing   12.821543\n",
       "1483        division   12.224732\n",
       "2619             law   12.148586\n",
       "4102             sec   11.623358\n",
       "981       conference   11.566034\n",
       "4031         rulings   11.416039\n",
       "2826             may   11.174153\n",
       "...              ...         ...\n",
       "1912             fia    0.014496\n",
       "3987       revolving    0.014417\n",
       "1174             csd    0.014192\n",
       "2804          markit    0.013736\n",
       "2259             ias    0.013555\n",
       "4129            sefs    0.013544\n",
       "4987              xs    0.013515\n",
       "4513          takers    0.013268\n",
       "4069            sbsd    0.012801\n",
       "2073           gamma    0.012607\n",
       "629          bunched    0.012525\n",
       "3354              pf    0.012234\n",
       "1491            docx    0.012130\n",
       "368              asf    0.011767\n",
       "447       authorised    0.011712\n",
       "5               abcp    0.011626\n",
       "3105          occupy    0.011564\n",
       "2100           giver    0.011128\n",
       "357              arp    0.011021\n",
       "1334           depts    0.010912\n",
       "3889      reproposal    0.010539\n",
       "4288       soundness    0.010520\n",
       "4436        subtitle    0.009947\n",
       "2970           msbsp    0.009484\n",
       "511              bds    0.008998\n",
       "544              bhc    0.008540\n",
       "3071        novation    0.006325\n",
       "481      backloading    0.004382\n",
       "948      compression    0.004267\n",
       "4986              xr    0.004101\n",
       "\n",
       "[5000 rows x 2 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf_idf_sum_vocab.sort_values(by=['tf_idf_sum'],ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn.decomposition import PCA \n",
    "pca = PCA(n_components=2)\n",
    "pca_comp = pca.fit_transform(train_data_np)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.06598829,  0.02226494, -0.0043227 , ..., -0.03556187,\n",
       "       -0.01686188,  0.00571915])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pca_comp[:,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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CiG4jwUw3MRgMzJo1kpKSMmw2LYjQknljCAk5wKBBTaiq7xe85yyO74yOs/UZ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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb54e093ad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(num=None, figsize=(8, 8), dpi=80, facecolor='w', edgecolor='k')\n",
    "plt.plot(pca_comp[:,0],pca_comp[:,1],'bo')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# K-means"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.cluster import KMeans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "KMeans_euc_model = KMeans(n_clusters=4).fit(train_data_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'algorithm': 'auto',\n",
       " 'copy_x': True,\n",
       " 'init': 'k-means++',\n",
       " 'max_iter': 300,\n",
       " 'n_clusters': 4,\n",
       " 'n_init': 10,\n",
       " 'n_jobs': 1,\n",
       " 'precompute_distances': 'auto',\n",
       " 'random_state': None,\n",
       " 'tol': 0.0001,\n",
       " 'verbose': 0}"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "KMeans_euc_model.get_params()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 657,  531,  429, 2041])"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.bincount(KMeans_euc_model.labels_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  0.00000000e+00,   0.00000000e+00,   8.06339343e-05, ...,\n",
       "          0.00000000e+00,   0.00000000e+00,   5.79570898e-05],\n",
       "       [  0.00000000e+00,   0.00000000e+00,   0.00000000e+00, ...,\n",
       "          0.00000000e+00,   0.00000000e+00,   0.00000000e+00],\n",
       "       [  1.06892185e-06,   0.00000000e+00,   1.42633011e-05, ...,\n",
       "          0.00000000e+00,   1.47504253e-05,   0.00000000e+00],\n",
       "       [  8.66880611e-05,   6.54592829e-05,   1.12181494e-04, ...,\n",
       "          1.41472024e-05,   3.60279396e-05,   6.09102878e-05]])"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "KMeans_euc_model.cluster_centers_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "43.47195213720293"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "KMeans_euc_model.inertia_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running Kmeans with  2  clusters\n",
      "Running Kmeans with  3  clusters\n",
      "Running Kmeans with  4  clusters\n",
      "Running Kmeans with  5  clusters\n"
     ]
    }
   ],
   "source": [
    "KMeans_model = []\n",
    "\n",
    "for i in xrange(2,6):\n",
    "    print \"Running Kmeans with \",i,\" clusters\"\n",
    "    KMeans_model.append(KMeans(n_clusters=i).fit(train_data_norm))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "with open(\"KMeans_models\", \"wb\") as fp: \n",
    "    pickle.dump(KMeans_model, fp)\n",
    "    \n",
    "#with open(\"KMeans_models\", \"rb\") as fp: \n",
    "    #KMeans_model = pickle.load(fp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Zq0dUHjbTkrF2rWwBULeubJJ4f0Tx89M9HoOIqEKqVk3GXuzYAZw+Dbz9trR4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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb54c98b990>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "inertia = [i.inertia_ for i in KMeans_model]\n",
    "\n",
    "plt.figure(num=None, figsize=(7, 4), dpi=80, facecolor='w', edgecolor='k')\n",
    "plt.plot(np.array(xrange(len(KMeans_model))),np.array(inertia),linestyle='solid',linewidth=4, color='red')\n",
    "plt.xlabel('Number of clusters',fontsize=14, color='blue')\n",
    "plt.ylabel('Inertia',fontsize=14, color='blue')\n",
    "plt.rcParams.update({'font.size': 16})\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Num of clusters:  2\n",
      "Num of docs in each cluster:  [2979  679]\n",
      "----------------------------------------------------------------------------------------------------------------\n",
      "Num of clusters:  3\n",
      "Num of docs in each cluster:  [ 139 2851  668]\n",
      "----------------------------------------------------------------------------------------------------------------\n",
      "Num of clusters:  4\n",
      "Num of docs in each cluster:  [2399  530  158  571]\n",
      "----------------------------------------------------------------------------------------------------------------\n",
      "Num of clusters:  5\n",
      "Num of docs in each cluster:  [ 158  431  521  139 2409]\n",
      "----------------------------------------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "for i in xrange(len(KMeans_model)):\n",
    "    print \"Num of clusters: \",KMeans_model[i].n_clusters\n",
    "    print \"Num of docs in each cluster: \",np.bincount(KMeans_model[i].labels_)\n",
    "    print \"----------------------------------------------------------------------------------------------------------------\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3676, 5000)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "KMeans_model[13].cluster_centers_[KMeans_model[13].labels_].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3658, 5000)"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data_np.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "IndexError",
     "evalue": "list index out of range",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-50-52dc785d513b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mxrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrain_data_np\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m     \u001b[0mcluster_id\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKMeans_model\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m13\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlabels_\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m     dist_doc_centroid[i] = sc.spatial.distance.euclidean(train_data_np[i], \n\u001b[1;32m      6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mIndexError\u001b[0m: list index out of range"
     ]
    }
   ],
   "source": [
    "dist_doc_centroid = np.zeros(shape=(3676))\n",
    "\n",
    "for i in xrange(train_data_np.shape[0]): \n",
    "    cluster_id = KMeans_model[13].labels_[i]\n",
    "    dist_doc_centroid[i] = sc.spatial.distance.euclidean(train_data_np[i], \n",
    "\n",
    "                                                         \n",
    "                                                         KMeans_model[13].cluster_centers_[cluster_id])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.09876156,  0.05046611,  0.17908945, ...,  0.09979327,\n",
       "        0.07940338,  0.06976781])"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dist_doc_centroid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pprint\n",
    "\n",
    "def print_file_with_clusters(num_clusters):\n",
    "    file_with_clusters = {}\n",
    "    data['cluster'] = KMeans_model[num_clusters - 1].labels_\n",
    "    \n",
    "    for i in xrange(num_clusters):\n",
    "        file_with_clusters[i] = list(data[data['cluster']==i]['file_name'].values[0:20])\n",
    "    \n",
    "    pprint.pprint(file_with_clusters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0: ['ap-3651.pdf.txt',\n",
      "     'ap-3839.pdf.txt',\n",
      "     'ap-3620.pdf.txt',\n",
      "     'ap-3647.pdf.txt',\n",
      "     'ap-3856.pdf.txt',\n",
      "     'ap-4193.pdf.txt',\n",
      "     'ap-3848.pdf.txt',\n",
      "     'ap-3859.pdf.txt',\n",
      "     'ap-3718.pdf.txt',\n",
      "     'ap-3928.pdf.txt',\n",
      "     'ap-3648.pdf.txt',\n",
      "     'ap-4195.pdf.txt',\n",
      "     'ap-3938.pdf.txt',\n",
      "     'ap-4285.pdf.txt',\n",
      "     'ap-3757.pdf.txt',\n",
      "     'ap-4075.pdf.txt',\n",
      "     'ap-4076.pdf.txt',\n",
      "     'ap-3933.pdf.txt',\n",
      "     'ap-4170.pdf.txt',\n",
      "     'ap-3958.pdf.txt'],\n",
      " 1: ['34-68988.pdf.txt',\n",
      "     '34-53041.pdf.txt',\n",
      "     '34-70082.pdf.txt',\n",
      "     '34-72247.pdf.txt',\n",
      "     '34-72505.pdf.txt',\n",
      "     '34-69604-pdp.pdf.txt',\n",
      "     '34-60056a.pdf.txt',\n",
      "     '34-74231.pdf.txt',\n",
      "     '34-53453.pdf.txt',\n",
      "     '34-77497-pdp.pdf.txt',\n",
      "     '34-63143.pdf.txt',\n",
      "     '34-60310.pdf.txt',\n",
      "     '34-62936.pdf.txt',\n",
      "     '34-74993.pdf.txt',\n",
      "     '34-77131.pdf.txt',\n",
      "     '34-70151.pdf.txt',\n",
      "     '34-55598-pdp.pdf.txt',\n",
      "     '34-71825.pdf.txt',\n",
      "     '34-53432.pdf.txt',\n",
      "     '34-54838.pdf.txt'],\n",
      " 2: ['ap-4081.pdf.txt',\n",
      "     'ap-3948.pdf.txt',\n",
      "     'ap-3748.pdf.txt',\n",
      "     'ap-3777.pdf.txt',\n",
      "     'ap-3492.pdf.txt',\n",
      "     'ap-4000.pdf.txt',\n",
      "     'ap-4135.pdf.txt',\n",
      "     'ap-3455.pdf.txt',\n",
      "     'ap-3474.pdf.txt',\n",
      "     'ap-3871.pdf.txt',\n",
      "     'ap-3844.pdf.txt',\n",
      "     'ap-3985.pdf.txt',\n",
      "     'ap-3899.pdf.txt',\n",
      "     'ap-4092.pdf.txt',\n",
      "     'ap-3878.pdf.txt',\n",
      "     'ap-4266.pdf.txt',\n",
      "     'ap-3795.pdf.txt',\n",
      "     'ap-3633.pdf.txt',\n",
      "     'ap-4215.pdf.txt',\n",
      "     'ap-3491.pdf.txt'],\n",
      " 3: ['34-77423.pdf.txt',\n",
      "     '34-77250.pdf.txt',\n",
      "     '34-77013.pdf.txt',\n",
      "     '34-77514.pdf.txt',\n",
      "     '34-78072.pdf.txt',\n",
      "     '34-77667.pdf.txt',\n",
      "     '34-77377.pdf.txt',\n",
      "     '34-78493.pdf.txt',\n",
      "     '34-78336.pdf.txt',\n",
      "     '34-77515.pdf.txt',\n",
      "     '34-78257.pdf.txt',\n",
      "     '34-77655.pdf.txt',\n",
      "     '33-9695.pdf.txt',\n",
      "     '34-77987.pdf.txt',\n",
      "     '33-10045.pdf.txt',\n",
      "     '34-79104.pdf.txt',\n",
      "     '34-79033.pdf.txt',\n",
      "     '34-77616.pdf.txt',\n",
      "     '33-10047.pdf.txt',\n",
      "     '34-78399.pdf.txt']}\n"
     ]
    }
   ],
   "source": [
    "print_file_with_clusters(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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TToD5d8K8W4l77BiqfD2F9995+4ABBcCUKVPIKHtk/oACgn8+8XI4qjMEcmHo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JYqo3Vy5dpGDBglnHX0NISAg9eg/g/NlTmCysMaUnglKN3KilfYdO/D3+T9zdzTfoFARBEIS3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BQvr6pF31evXuHt542FvzmT702kgbsl5W/LebDrEToPdTg/5yJDjwyu1U/eszzSrqUzcF9/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\nakHzkc15sPMRtzdEM2BPPyzczLkw9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gmCiQnrNm1iyJAh/41bEYnqEQQBX29vXFJT6dLA\n+TMSCeXt2nEjIeF3+fzMzEza+/nRvawMvwbOFwOrDQzIzM7+ny1Qv2HDBt6e/zajT0bStE2T2uPq\nSjXrgjZSmVdJ4FR/FMUKtGodcjcrKjIrST+agZmpGfk5+rRKbQLa8P7b7zN+/Pg6/QuCQNvAthgG\nGFCYVEjujTxAH2jo+EYwbUb71pnovb7qBikHUxlzZBQAmecz2dVvL7eu3yIhIYGV61aSmpqKlZUV\n6Y/TiTw0HLce9ROKXVl8lZPvn0YqlWJqZ4pECtXFCloPa8WQLYPrrM5XV6rZHrGTZkHN8B7ckr0j\n9iF3lzNk8yA2ddlCi3APOrzWHksnC3Lic7nyw1XMmpjR6d1QDkQeRK1U0ePL7kikUpq0scezbwuk\nBlLSz2QQM+4Ab2TNaTSt0IpWq3n6UJ/Sz97XDs++LXhyJYfJlyY1+p0tdV+OtYc1wa93wHtwSy4v\nukr6qXTGHx9bp93BSYcZ5DaYzz//HIAxE8ZwNe8KWRezcfB3wMbTmoyzmSifKqmprkEqk+IztBWd\n5oXi1EG/s0HQCSzzXIlbdxfST2Uw7faUejtLyp9UsNZvPUO3D2b/hIN0mhfKlS+uotVpmPNkdr3d\nLAAJUXeIm3sMO09bLFVWXL14FblcXnveyNgI5+7NyTibia5Gh4N/Uzq81p6AKf7cj37ApQWXmXZz\nSu0YT80/w5UfruLQrinWLazJu5FHTXUN/VZF4PNLHZM9I6IxsjQiYmkfVrRcTYfZ7en2UZc6719q\n7CN2D92LVCYlMno4MSN/5sTRE3Tq1Km2TVZWFh27dMQ2xIbQ9zvSLNCBssxybqy8wfVVNxl9KBL3\nMP07WZ5dzkrPNTxMfoi7u3uj36lIJBKJRCLRH+mPnisXa1KIRCKRSPQnN2nSJPbExJDh7c33hob8\naGrKMqkU25de4sq1a/UCFADz3nqLqJUrCdJoMK2uRqJUEqZQ0KWkhNEjR3Ly5Mn/wp2IRPVJJBI2\nRkVx0diY4xIJz5I6lQJxUinXTUxYv3nzf/xza2pqmDltGp4eHpSVleHbSDs7wM3YmAMHDjTS4q9N\np9Px5bdf0vOHsNoAxdPUp1z54SoXvrpISVoJZk3MeBCdjGVzKxwCHMi9kcf9mAdYt5ITERFBdnY2\n+fn53Ll5p16A4hkvDy8eHkwhYIo/b+bO5Y2cufhNaMuxN09w8v3TddqmHn6EU8jz1D8uXV2oqanB\nP9AfIyMjzp44S1pyGr6tfVFWKnHp6lLv8zLOZXL20/O8cm4CbxX8jZe3DqLjGyEgQMSyvvUCBkYW\nRvRZ3JuETYk07+hEvxV9KU4uZu+IaLq835lR+0fi2acFTds2JeBVf6bET6amWsO+Efvx8/NDECDl\nYCo513I4PD2WFV6ryDiXiXOn5qgr1KQdb7j2Q97tfMozy3m7+A3eKX6TgFcDuLnmNjnXcynNKGv4\nmoR8qgsVRMaMoPVwHypzK4n/8RodZrev11Yqk6LVamt/dnRwxMbFhjeezCHgVT/sWtkR9ll33syd\ni1c/T7yHtGToT0NqAxQAGpUGSzsL7kcn02F2+wZTX1k1tyRgij9HZsVh08Ka0LdDsHS0wKtlSw6/\nEotGqanTvvB+EcfeOE6zgKaUPC5lYP+BdQIU27ZtQyfR4djekem3pzA383WC53Tg0sIr7Buzn6bt\nmlCQVEhVQRUAJ98/zb3d95l67VWmXn+VEbuHMTtlFr2/783+cT/X1t5IP5mO/yQ/7mxNwsrFql6A\nAsCrnycBr/pj7WHNjeW38PP3IzQ0tE4bFxcXrl+5TpemXfmpxw6+MlzAiparKEkrZdL5CbUBCgAr\nZyta9PDg8OHDDX6fIpFIJBKJRP8LxHRPIpFIJBL9HzBo0CAGDhxIcnIyJSUluLu74+jo2GDb3Nxc\nli5bhkQQyAdaACogDpAB7Wtq+HDePK7evIkgCGRlZaFWq3F1da1NBaVQKFizZg0rf/yR9OxsrMzN\nGTNuHG/Pmyeu9BT9x3Xq1Inzly7x4bx5LDlzBiMDA2q0Wvr16cPl776jbdu2/7iTf9HsmTM5vH07\nL+t0HOO3/1FsLghUVlb+x8fwZ6FUKtm1axcbojaQl5+Hi7ML0ydPZ9iwYaSmppKTncOY4ZGoq9Qc\nnHKY5JiHtAj3QGYhw9DEELfurgxc1782nVKX9zqRdvwxu1/ey/ab21m5bCVmZo3XbDh9+jSnzp5i\n6o1XsfGwrj0e/HoHPCNasL7DJrwHeuHazZVHx9J4fDKd/mv61bbTKDTotDoilvVh7Pix3L55m8+/\n/pwrD64AUF1UjYVD3XRKV5fEE/x6B5p3bI5OoyPlUCrxS6/j2t2lXh2NZ5yCnTCWG5N/O5+2Y9tw\nZGYsqnI1Xd7vVK+tzExG74U92dFvN08U2bz2cEZtfQJtjZYbq2+yvZ8+hRMSODT1MOOOj8He53nq\nnrKscmLG7if49faY2eqfX6e39avydw7azeFpR4g8MAKZ6fN6KapyFYemHcF7SEuqi6q5vSmRS99e\npvUIH1oNeWHHXY2WtCOP6bK+C3l5eTx58oTwl8JZOWIlYQu6EzQtsE77wZsHsqbdOtb5byT4jfbY\ntrSl4E4BCSsScbN3R2mlwqWLc6Pfs3Pn5tzemMCrVyYhlUqRu8iZNngaazauYUnzZQRO9ceyuSVP\nruZwP/oBnhEtSD+VQef3OrHsy2V069KNnJwcysrK+OTvnzD6YCQtwp/XLQmcEkCrl73Z2HELaXGP\nMTQx5PTHZ+k2vwtXF8cz7faUOjuBJFIJ7ca2oTKngjMfn6MwqRCNUoPMTEbqkUe0G9emwTohAP6T\n2pGwOZHyx+WcPbGlwXZOTk6sWbmG0SNHM3TMUGakTMXY0rjB/ozlxiiVykafnUgkEolEItFfnRik\nEIlEIpHo/wiJRIKPT0OVKepauHAhCAKjAa9fHe8JHAEeAE9v3WLRokWsXbGC1PR0/YSRpSWzZs/m\njTffZEDfvuTcu0ewUklfoKKsjHPr1xO1ZQunz50jKCjod7lH0f+uoKAgjp48SUFBAYWFhTg4OPxu\nudYzMzPZuGkTvQSBB0AlUALUL3ELWiBLEGjduuEaCf/XPX36lF59epFflY/fzLa0bxlI0d0i5nzw\nOivWrGDBlwswMpFhYGTA3uH7UJWrmJM+G0tHCx7sTyb70pM6AYpnWoR7EPK3YK4uvkpBQUG94GZa\nWhqr1qzi9PnTZGRmYONrjYGs/iZvWy9bAl7158LXl7DzfsCt9QkM3DAAq+aWtW3u7ryHfWt7AqcF\n8OR8Dl9+/SV7du7mtbRZbOy4mdsbEuj6Yd1kYuknM+j2cVcAYl+PI/NcJp3eDSX/Vn6jz0oQBDRK\nDRKpBIlEgqWzFc0CHTCQGTTY3rW7Kzqdjp6Lw+oUUDaQGRAyJ5inKSXc3/aAoGkBSGUGrPFbj1d/\nL5q2tafofjEph1Lxm9iOXt/ULWzu0cudZv4OlDwuZaW3PiWRbUtbCpIKubbsOhbGFqQkpvJgTzLN\n3ZpjZGxE2Jfd602kX/zqEqaGpnz+9edcj7+OmZUpinIltg62bO26nRE/D60NmtRU13Bj1S2kagNe\ni3yNnzf+TEL+HZxdnFnwwbeMHj0avw5+VOZVNfr8qvKr0Kq1XPjqIp0/6EzenTz8PvLD0dERjbuG\nitxKih4UY9vSlukJU7FvZUfK4VT2jz+AsZ0xIyKH49XTi6K0Yhw7NqsNUCieKkiMukN+QgGGJga0\nHOjF2b+fQ6PWcH/PAx5EJ+PYvlmdAMWvBU4N4OT7pym8W4jM3IiUw6lo1Vp9fYpGyMxlSA2kBE4J\n4NUZr5J0K6nRgIafnx+KUgXl2RU0aV0/SKFRacg4l4H/DP9GP08kEolEIpHor04MUohEIpFI9Bdz\n9OBBQqkboAAwAAYAPwKGEglfzJ9PT7WaSMBAp+NxWRlbf/iBqI0bkT19yiS1mmdTNPaAh1rN+Zoa\nhg0eTFpmZm2RUJHotwiCwK5du1i8cCE3ExMxkErp07s37374IV27dq3XvmnTpjRt2vR3HdP333+P\nVBC4DfigT+l0ChgGvDjNeBMwlcvp27fvv/QZd+7c4fjx42i1Wjp16kSXLvXTxjyj0+mQSCSNnv89\nTZ72CmonFZP3TMTQWP9fg5b9vWg/K4g9/aNZu2EtWrWOxKg7ZJ7PYm7G7NqdBg9/TqHtuDb1AhTP\n+E1qx8UFl/jggw+YP39+7Y6YnTt38sqrr+A9oCWes1vQXOvEvd33WOmzhhF7hmHhZEHm2UwEQcCt\nhxsevd25te42xfeLGXdsNC5dnqdvyr9TwMn3ThG+OByJREKrUd4cnXEU7wHeVDwppzK3ggtfX6JZ\nYDO8+nnWXicIAlJDKU9Tn5KwKZHXHs6kpkrN1R/iqS6ubjBlUfalbNQVKuS/7PbQqjRo1dp67Z7R\naXQg0GhR7OA5Hbi56ha3Vycy4udhtJ8ZRGLUHYofFvNgXzLTE6fg0M6hwWvdwtwoSMwn7UQ6KYcf\noVEmY+VsibmVGYv+voiJEyciCAI1NTUMGT6ELUFbCfxbAM6hzanMqyJx7R0yzmeiVqlxGdqc13e9\nhlVzSxRPFdxYfYvzn19gnd9GnIOcMbU1IfNyFq6urpw7fY6AgAA+/fTTemMaFzmOn9Zto/UIn3rv\nsqATuLX+NkHTAym4U8DGjpuRW8jx9PTk7MmzvJ4+C0sny3p9evX3xNTWFLOm5kxP0Ne62DMiGpfO\n+h0bd3ff4+DkwzQLcsDjJXdUZSqStt9Fq9KhU+mQWEpQFCuw9fas1/czJtYmmMiNGRM7GkWxgpjx\nB2gzypfUo48Imh7Y4DWpsWk4BTsS9k13ljuv4uzZs4SFhTXY1s7OjpGjRnLuw/MM3TukToFvgPgl\n17CztqdXr16NjlEkEolEIpHor04MUohEIpFI9Bei0+l4mJbGrEbOS9Gnf0oQBCaq1fx6nbon4KJU\nsiovDx+goTWknQWBG0VFxMXF0a9fv3rndTodJ0+e5PChQ6hVKoI7dmTUqFG/mepF9OeVl5dHUVER\njo6O2NnZ/cvXC4LAjGnT2PvTT3RUKpkFaLRakuLi6HPiBEtXrmTq1Kn/+YH/huzsbNauWkUvIBR9\nUKI9sBHYA3QFmgHlwFUgHpg3eTIGBg2vln9RYWEho4YN4+Lly3gbGSEVBD7T6fDw8CD6559ra8jU\n1NSwZs0alq1exsO7DzE2NWbwy4P5YN4HBAY2PDH6W2pqati5cyer1q8iPT0dOztbXhk3mSlTpmBt\nbd3gNenp6Rw5GMvstJm1AYpnjCyM6L3iJbZ03ErkqEgOfXYI38jWdVIhaZQajK0aTl8DYGJtDAIc\nOH6A6JhoBgwawPz35jN5ymSG7XsZr4jnE8f+E9txbeV19o7ch6AT8OitXyV/+sOzWHvIsbOzw8nR\niV2D9hAwxR8LRwuyrzzh4YEUun3SFb/x+gCIgZEBWq0WMyczYmcfwy3MjYBX/dk7ch9N2zbBtbsr\nVQVVCDqBB/uSkUig5UAvrN309Q5cu7sQOzuOl7cOrrNDQlGiIPb1Y0hlBiRsSqTlAC/KsyqoLqxG\nVa5q8Dkk73+IsdwYu5a2DT4fuasVWo2W7xd9z7v938W9mxvNezXXp3aSgIm1aaPPtiKngtS4NAat\nH4D/pOcl3/eP+JmioiJAv/vOyMiIgzEH2blzJyvXreTnBYextLLE2dGZx6TT8c0QXlrwfKeGqa0p\nXT/sjFkTU259mcCnMz9FpVLR7qN2dOrUqdFAWlFREf5+/vyw5AdOvX+asC971D4/jVLDiXknURQr\n6f5pV2SmMraEbSPUOZSUlBRkJoZsC99BRXYF5k3NaDexHR1eC8LMzgyJREKzoGY4BDjUBo4MjQ1R\nlavIupTNwcmHGbbrZbwHtqwdy0vf9mL/xIMUJhXgP9mfMx+fJedaLoIgNDj+0owyVBVqrN3lOAU7\nEjglgJvrblFTVUP66XTce7rXaV+WVc7VH64SsbwvMlMZXv08OX/+fKNBCoDFixbTuXtndvXZQ8i7\nwTQLcqA8s5ybK2/zMDqF0ydOi4F/kUgkEolE/9MkgiAI/+1B/Bn80RXLRSKRSCT6PajVaoyNjXkL\naOxvs42AHBjeyPlbwBVgKnAd/UryEsAEaAtUyGREfvQRn3zySZ3rsrOz6R8eTsbjx/jU1GCo05Fh\nakqlgQF7Y2Lo3bv3//8Niv4QV69e5f133uHcxYsYGxqi1moZ2K8fCxYt+qdSjj0THR3N1HHjmKxS\nIX/hXAbwk6EhDx4+xMPDo6HLfxcffvABMYsWMVpTt1BvEXAIyAR06IMX3oAbcMHIiI1RUYwYMYK4\nuDiSkpIwNzdn0KBBuLq61vahUqnoEBCAJC2Nfmo1z0JzauCMgQGPbGxIvHsXa2trBgwZQFJGEiHv\nB+Me5oriqZI7m5O4vS6B3Tt3M2jQoH/6nhQKBf0G9eN+xn0C5/jTLNCB0vQyElbdQSgQOHfqXJ1x\nPhMVFcXnaz9j7IXRjfa91HU5k4e/ypp1a3Dt68qAVRGYNzUH4OK3l3l09BETTzdcDDtxWxIXvrxA\nRW4lw7YP4eo316BAgm13G/qvj6jTVl2pZn3wJhyDHOi3IqI2GKIsVRL7ehzJMQ9pYt8ETw9P7uff\nx76NHbYtbQmcGoCtpw35dwpI3JxIamwasgoZOnMdhY8K8R3ZmqHbh6AsU3JnWxJF94sxsjDCwtGc\nc59dwKufJxaOFoQvegmAyvxKtnTbik4r0PGNYKzdrcm7lce15TdQV6mxbWmLqY0JT1NKCJwWQMbp\nDMybmdcLapSml7Kl81ZMrU0ZeXgEqUdS0aq0NAt0wC3MDYlEQvblbPZERFNc+JSSkhI2btrI7Tu3\nMTM1I+FOApYRFvT4rFu956oqV7HYaSkvbxuMz8utao8LgsD61pv46t2vGDt2LCYmDdfWePLkCW7u\nbmAAb2TPwcy+fhBZW6Nllftadm7aSZ8+fRp9PwoLC5n71lz27dmHVTMrlBUK1MoakELrka2QSKQ8\n/PkhFk6WRMYMr017lX46negh+2nStAkKcwVdPuhEkzZNKEktIX7pNQrvFeHZtwUWjhakHEqh4xsh\ntTUyknbc5ewn52jSpgn2vvb0+jqswfEvc1/BgLX9sXCyYGPoZiL3jaDlgBf3GMLhmbEUJxfXvseC\nIPDw5xRixh1AV6Ojw+vtaTe+rb5WxeFULi+6is9QbyKW90UikXBgzEEi245i/vz5jT4ngJKSEr77\n/jvWrl9LcX4xJmYmjBk7hvfnvV8bvBSJRCKRSCT6s/ij58rFIMUvxCCFSCQSif4qWrq70y4jg8ay\nWy9CX5+ifSPni4DV6FeTa4BOQHP0K8uvAynArLlz+fHHH2uvUavVtGvdGsvMTPppNLVbNQXgNnDc\n2Jj4Gzdo06bN/+fdiX5vp0+fZkBEBCFqNcGABfog1RWplPumply6evWf/h67hYZievUqXRo5H21s\nTMScOSz87rv/rzGnpaWRnJyMhYUFoaGhyGSN55L3dncnKCODX1eYeAAcACwBZ/Tv+mP0KdOG/XL+\nop0dRjIZVaWluAJKqZRHSiWjR41i3caNmJiYsH37dt6aOpXpCgUv7rsQgB0mJox57z1MzUxZum0p\n4y+MqbcC/+7ue8RNPU7uk1wsLeunv2nI3DfncjD+IKPiRmBkYfT8M3UCsTPiMHwg48r5K/Wui4qK\n4ov1nzPm3KgG+81PLNBP2Gt0OHVwRFGqpPhBMb6jWzNo3QCUZUp+dFnOqAMj8ezbos61yjIlmzpt\nof3MIBK23KHVy960nxHIshYrGblvOJ596ra/vvIGtzYkMCX+lXrpcHRaHRs7bsbIypj86/molWom\nnhmPS2dndBodh2fEkrTjLr4jfLD3tafo7lOSdiUhMZBgZGHE6EORNA9xqreK/vCsWG6vT8Clq3Pt\nBLW6Us1S9+W0CPegKr+a6mIFcjc5gVP9sXK1Iqr7NjRKDS8t6EnHN0OoKqhie8QuVGVKAqYEYOlk\nQdaFbO5sS0JuI6estAx+SVtlZGlE5rlMzJqY8fK2wVz6/AphLj1ZsWxFvWd/4cIFwvuGM3Brf3yG\ntqodu6JEwd7h+zAwMmBM7Kg69/TwYArRkTFolBqkUil9B/Th4w8+oVOnuoW9FyxYwIroFSgqFbx2\nf0aD3z3A3v77mDNoLrNmNbw3r7S0lI5dOmLobUCPb7ph72OPTqvjUVwaR6bFIkj0Kb88ernh3su9\nzlg1Kg0Lrb7Ho7c7ow6MrJMyTNAJ/PzqIbIuZOHS1YW7O+/h2t2VkdHDMLY0RqvWssp3DaWPy5h5\nbzr2rRre5XVi3kmUpSoGruvPtvDtZF3Kpu/i8NqAQ/mTCi4tuMTNtbcZf2osrr9KIwawO3wvgwOH\nsHzNcjQafXH25iFOdHi9Pb4jWyORSFBXqVnmtJLjscfp3Llzo8/y1wRBQKlUYmxsLO6eEIlEIpFI\n9Kf1R8+Vi+meRCKRSCT6i/nbO+/w1bx5eCuVvJgs5BGgAip+4/pK9KvIDYHxwEP0K8xLADPABYje\ntYvFixfXTrDExMRQkpvLaI2GX0+5SIBAIEerZdG337IpKuo/cIei34tOp2PyhAn0VKsJ+dVxG6Cf\nToehQsGsadM4d+nSP9XfrYQEJvzGeXeViqsXLvzb401JSWHmlCmcv3SJpiYmVGo0GJub8/FnnzF7\n9uwGU7solEp+vb48E4gGhgBteF6TohrYDewFwoCi4mL6Ah2gNgBRAuyPiWFsVRX7Dhxg9fLltGsg\nQMEv/QYqlURt2ECNIXReFNpgiqA2kb7cWHSTbdu2NTo5/GuVlZVs3LCRUSdG1glQAEikEnotCuOH\npj/i5ebG6PHjmTlrFs7O+nz+ISEhPJ6Szt7Iffq0OoEOBLzqj3lTc54+KiGqx1Y6zA6i6/wuGJnr\n+y56UMSeYdEsb7mKiWfGE/p2R3YN3kPo2x3xm9gWE2sT0o4/5uI3l7DxtCFoZiAXF1zm6pJ4Ms9l\ngkCDNSyStt+l/YzAegEKAKmBlPYzg7i14TZmzcxQpir5qc8OAqcGoChWkHMth9kps2qLaedcz6Uo\npYi8m3nITA35KXwHlk4W9PwqjNbD9TuBBJ1AeVY5MgsZmeezyL2Zh2NQM+78lITczZqh219u8P3p\n/F4n7u+5T+hbHQGwcLBg9KGRrGq9lusrb2DlbImDvwNjjkYSN/c4zdwdGBE9vHZsGpWGSwuvsKXb\nVizMLLkXcI+g0CDcXd2ZMWUG4eHhSKVSunbtytYtWxkzdgzWnta06O1OdbFCn6JKKiHkb8GoylWY\nyE3QqrXc3XWPIzNjaT8riB5/70ZVYTUJGxPp1bsX27dtZ+jQobX3kJmViaHckIrkCrRqLQZGDacy\nK88ux8amoXLyeouXLEbbRMPIvcNqvzepgZSW/b2YeGECq3zW0HaML03b1q8xk59YgE6rI2JZn3rv\ng0S6o9vPAAAgAElEQVQqIXzRSyxxXkbnd0PpuyScPcOj2T0smgGr+yF3sSLywEjWtF2HqW3Du0UA\nTGxNqcipBCBkbjBPHz7l2vLrHHvrBKa2plTlV2HR3AK3MNd6AQqtWkteYh79PuyH3FrO8q3LGHt2\ndO0uItC/QyfeOEUrn1b1AkG/RSKRYGraeCovkUgkEolEov9FYpBCJBKJRKK/mBkzZnDk4EG2nDtH\nJ6WSFugDE4kSCfGGhsyYMYNdGzbQrZHJ1JsG+pzuYegnaUuAEMARKEO/m6IgP5/t27czfrx+9fHu\n7dtpo1DQ2JpQP42G3dHRYpDiT+706dOUFhUR1Mj5zjodS+LjSU1NxcvredoUtVrNvn37uHjhAgaG\nhoSHhxMREYHM0JCa3/i8GsC4kZQ0/8jjx4/pFBxMy8pK5mq1WFZVoQMeqlR8/M47FBcV8enf/17v\nOj8/P9JPnMDjl83E59HvFmr7QjszYBSwGH1R7Q5Axxfa2ACRSiVLjxxh/LhxxF++zMDfGLMVUFJa\nSmllJS36NLx7AcClrwvRMdG4uLjQrVs35PIXk2U9l5iYiJGFDKdgxwbPm8hN8OjmgvnJdGJ++IEf\nFy/m4JEjuLm5MfDlgZg7mGPb0hYTuTFpxx9z7rMLDNwwgMcnHuPZz5NeX/es05+9jz0Tz4znR7fl\nbAzZxOCowVxdHE/G2QwuLbyMoBWw87Gjw6wg2s8KIuNsJjXVNei0OiybW+Ley42HBx7i0cu9Tr/P\ndiw0Ru4uR1GsoNXQViRG3SFy33CuLI4nef9DJl+cWBsEyL2Ry9ZeP9HxzRDGHhmFqa0pGpWGpO13\n+fmVQ5SklaAqU5G8/yFPU0p45eJEkmOS+anPDgas7cfjk+kNFn5+xjeyNWc+PsvRuXE4d3amIltf\nmLtpu6ZMOju+dsI942wGlTlVzHk8qU4wytDYkO4fd6UwqZDU2EdIe4FHCzcKEwsYNTGSbp27E70r\nGiMjI0xNTbGwsSDkbx0ofvAUaw9rXrk4EZ1aS9wbJ7j6Qzzy5lZUF1UjAP3X9MN3RGsK7+trUnT7\npAvN2jsw8ZWJ5PTOqd2Zk5uTS9aFLIzlxtzb+4B2Y+vvjMq+nM3TxyUMGDCg0e9kzfo1hK3u3mBg\nycbDGp9hrbi+6ib9V0TUO39l0RXkbvLa9E8vMrM3wzm0OTnxuUhl+VTmVVF0v4hVPmswsTEhcJo/\ncjcr0k9l0GaUb4N9pJ9Kx+MldwCUZSoAIn8eSU2FmifXcrm36x4513IZsLZ+faVbG25jbWVDjx49\n6N69O4l3E9nQbhN+0/1wCnGk4kkFd9YmYVBhyNmTZ/8rRe9FIpFIJBKJ/krEIIVIJBKJRH8xMpmM\nA4cOsXr1apZ+/z0xGRlIJRIiwsM59tFHhIaGcvr4cQ6mpdG/poZna6916AsFpxoaYqjTkSwIqICZ\nwK/Xe7cDDgIfvvtubZCioryc3yqNbQZUK5Votdp/ugCx6I+XkpJCcwODRv+BaA40MTGpE6S4du0a\ng/r3h6oqPBQKBImEqDVrsGvWjO49epAUF4fLC/UfQJ/+6L6ZGe9FRv5bY/1k/nxcq6qI0Gprj0kB\nH0CuUvHVl18yfcYMHB3rTt7PeestRp07R5BKhQn69GWNTcOaAq2BRKD+NKaeOeCj07Fv1y7cgVz0\nvyMNyQXcXFwovX8fdYUaY8uGi06rylQkJCQy7Z1plGWXMX3GdBZ+sxAjI6MG22s02gaPP2+gwwno\nqFRyAxjUvz9NnJvRJNyO0UtH1k4yd363E4/i0tg1ZA+CVmDy5UkN33NTc9qOaUPW+Sz2DN2LY7Aj\nRUmFjD85FpdOzrUr85/E53Bg4kFMbIxpO6Ytvb4OI/vKE34K34HfxHY4tn/+3Vi7y8m9mVcvbVTt\ns7uRh6JYweWF+rRVe4bvo0VEC2w8bXAKdqptd2LeKUL+FkzYZ91rjxkaG+I7sjV3fkri1AdnsPex\nw8DYEEEQOD3/DAM3DMDK1YrDM2LRKjV1xvUiqYEEiURCzvVc7my7i4GJARqVhrAvutfZEZC0/S7t\nJrRttLB4xzeCeXT0EZ3f/6UY9Sjo+HYIO3vv4YOPPuD7hd+z/+B+fMa2ov30+mHDVy9P4tGxNLb3\n3YmF3IKB2/uRfekJS5yXIWj1ATipTEr7WUFYe1qzY8cOpk+fTnFxMbFxRxh9MJKqgiqOzo7DvKkZ\nHi89T8eUtOMuh2fEYmJiQkBwABHhEcyZPadOPRqtVkv+k3yaBTZr9Fk17+jEle/jqf68urbotSAI\n3Nt9n+QDKVg6WTR6LegLbj88lELmuSx6fRNG2zFtMDQx5PGpdE7MO0lFTiVnPz1PywFe9XYRpZ9O\nJ/N8FkN/GgLA3c13cTBvxgrPVQg6AamhFENTQ9QVala2WoPP0FZ0+7gLFs0suLHmFuf+fp7YQ7G1\nuwV3bttJXFwcK9etJOHnO1hbW/PBtA+ZMGECFha/fR8ikUgkEolEon9MDFKIRCKRSPQXJJPJmDNn\nDnPmzEGlUmFoaFgnOHDizBmG9O/PkqQkWgGGWi2PjYwwtLBgzeLFTH3lFW5qtYynboAC9BPBfYEf\n8vO5fv06HTp0wC8oiBOXL4NK1eB4MgBDQWDksGHsjo7G0FD8J8ifkVwup+I3VgRrgQqNpnZlf1ZW\nFr179iS0uppQQdDvpBEE+iiVnMjK4nJ5ORUSCS2AVr/qRwDOSSRUGxszbty4f3mcVVVV7N6zhykN\nBD9Av+unhUzGtm3bmDdvXp1zffv2ZfSECWzZto0OSiWgr7vRGJNfxtv4Gn+Q63Q4A6Hodx91Ql/f\n4tfUwA1TUz578022bN/CnW136fxuaL2+tGot93bfZ0jUIDz7tiD3Zh7RU6NJH5tOzJ6Yunn9NRqW\nfP891WXVZF3IwrVb/eLY1cXVpF/KJvyXn9sDV7VaSpUljF06qt4qeM++LWg/M4j4H69h08K60Xu2\n9bKhKq+KitxKOr8byt7h+/ipzw7sWtri4O9ASVoJ+QkFBEzx5/bGBDq/p79X59Dm9Pi8O1FhPxE4\nLQCfod7otAI6jcDVxfF0eC0IE3nd3TWqchVXF8fTbkJbXvq2FxKJhAf7k4l97ShWzs/z45Y8LiXr\nYjbDdr1c53qdVseuwXsQBIHXkmdi66lfvV9VUMWJeafY1vMnXo1/Bd9RrVnusZK7O+/R5b2G0/c8\niHmISxdnJp2bQGVeJWsDN6Cp1uDS2fmF567ApXPDtRIA5G5yVOVqBK2AxFD/nZramhK+ohdrItbw\n+aef6+sWODUcmAJqd89UllVyfeVNKnOrGLF3GG49XEGAx6fSOf72SbQ1WhLvJAL6OiTOwc60CNcX\nq1dXqtkzLBpbLxuatmtK5vlMKp5U4DfJD59hrdBpdFzafZGN7TcStTmKkSNHIggCN27cwNjMmLL0\n0tpdLC8qSytHLpOzzGUlHhHuWDpakHEui4onFQzePJDD02LJuZZTJ8j0zNNHJeTdyif3Vh7Tbrxa\nJ2VUi94e2PvYY+VihaZaw+auUXT9qAstenugLFORsDmRi19fou+P4Zg1MePyoqsU3ioi+V4yM1+b\nybELxzCzNaX7Z91w6exMZW4l11fdZG3ABgSdgFOIE+jA09Oz9jMlEgkRERFERNTfFSISiUQikUgk\n+v8nVuoSiUQikegvztjYuN7uhWbNmnHlxg2OnznDgPfeo+c777Bq61Yyc3IYM2YMlpaWGKAvItwQ\nE6ClTMb58+cBmDlrFvc0GnIbaKsELgLdBYHLx47VKbgt+nPp378/RRoN2Y2cvw9YyeWEhOgrVixb\nuhRXjYbOzwIUvzAA+mi1mCoUjJ80iX0yGTtMTLgCXAA2mJpy18aG46dP/1tF2IqKiqjRaKif6f45\nW6WSzMzMesclEgmr165l0cqVZHl5YQBk/UY/T365n4be7Wey0P+uuAPewBYgFf3uJOGX8z/JZHi0\na8fEiROZ/+58Ln15mezLdZ/0syLQFs3MayeRHYOaMer4CE6eOlH7+/bMpx9/zIUjR+ig0RE3PRbF\nU0W9/mKnHcHVQIrDr47L0NBmom+DaXoAAqf6Y2BkQEFSYaP3XHCnkCZt7KmpqmHv0GikGh1yNysK\n7xYhIGDpZEn3j7ti7W6NY2CzOoGH0DdDGBs3moqcCvaNOcDOQbspvFeAjac1W3v+ROaFLARBQBAE\nsi5msblrFE187Qlf1BtDY0MMjAxoE+nLyH0jKLxXRHVxNQDlWeVYOFpg3sS8zlhTDqdS/PApow9F\n1gYoQL8jZPCmgZg1MWNFy9UssllMjUpD4d1Cbm9KqHfPT1Ofcunby4T8LRgAi2YWhMwJBglU5lfV\naWvtbk3erfw6xwRBoKqgiqrCKnJu5GLZ3LJePYbmoc0xkRsTHx9P+4D2ZB1v7LcR0o49prl789rv\nY8LJsbiHuSGRSJBIJbTo7cGEU2NRFFaTm5OLUqlk155dFD4uZKH8e5Z5rKAss5xpN18lZG4wBiYG\nVOZVMfHsBAau7Y9XhCfeA1syKGoAL+8ezIRJE0hISCC8Xzg9evfA0t2S+KXXGxybqlxFYtQdtm7a\nyhtz3iDlUCpVBdV0eqcjb2TPoe3oNgTNCOTwzKP13lt1pZpDUw9j52OL74jW9WpaVBdX8yAmmd4L\nezH6cCRtx7bh5Lun+c7mB5Z5rCD7cjYGJgZc+PoiK7xXc+WrqxyLPYaDgwNpj9Owdpcz7dYU2kT6\nYuVshVOwE4M3DtQHNezNmHRmPHZudqSnpzf67EUikUgkEolE/1likEIkEolEov9REomEzp0788UX\nX/Dtt98yYsQIZDIZBgYGjH/lFf5BAhmQSmtXdXt5efHlV18RZWjIFfRFh2vQT2pvQp+7PxToqlSy\n9Pvv0el0v9+Nif5tcrmct99+mwMmJhS8cC4DOGpkxBcLFtQGvXZv3067RnbPSIC2CgXJd+6QkZXF\nhI8+QtK7N2b9+/Pp0qWkZWbi7+//b43TxsYGqVRKyS8/FwMPgDTg2d6KCmNjHBwcGrxeIpEwefJk\n7qWk8Nrrr3PJyKjB9z0dyAEGDhrEZSMjGnprc39pF/jLPQ8B/IAYYCHwHfqgRasePTh++jTGxsb0\n69ePhd8sZFvYDqKHxHB1STynPz7LMo8V5FzLYfShSCTS5zsmzOzMaPdKW9ZtWld7rLq6mmVLlxKh\nVBKuE7BOK2W11yrOfnqO5J8fEr/sGmtbraYo9hHDlHV3nOikUozlv1Fw2MYUnUbHxW8uIfxSu+PX\nnj4q4UFMMm49XZEYSHCWwlgBSh+XYWhiSNrRNCRSCZkXsjj94RmKHhSjKK07Ee3S2ZmWA7yQmRmi\n0+ioqaoh92YeJY9L2fbST3xn8wPfN13Ctt47kFkYMSZ2VL0Jfbfursjd5Jz+6CyCIGDWxIyqgipU\nFXXfycSoOwRO9a8t/v1rEqmEjm+GoFNraeJmhXdfTxyDm3F4Riy7h+0l+eeHpJ9O5+QHp9kQspmA\nV/3xGfZ8X1DLgV7IzGTcWnerTr8BU/y5t+c+Tx+VIOgErq+6wSrftfzg8CM/NP2RnycdolmgQ73n\nK5FIwECCVqtl0qRJ5NzM5eHBlHrjVpWruPLlVd58/U1smtnQ4bX2mFjX/07N7MzoMLs92fnZhPUO\nI60kjbDPezDp/AQilvelIKGALd224tTRCU21hsCpATiHNq/XT8sBXrj0ciY4NJg0VRpzs2cz5nAk\nj0+mc+bTc9QonlefKcssY1v4DjRqDXZ2duzZvweXLs7UKGrwn+SHzEwGQK+vw7B2l7Oy1WqOv32C\nhKg7nJp/hpWtViORSrB0ssS5c/2xPE0pwdTWFHsfewyNDen8bidefzSLd8ve5oPqdxl3dAxeEZ5U\n5VdTnl5O8t1kQkJCUKlUpKWl8dK3vTA0qb+br/2MIIwsjLi7+x4VBRXY2trWayMSiUQikUgk+n1I\nhIb+5/E/qLy8HLlcTllZ2b+1ok8kEolEoj8TrVaL9FdBhH9VdXU1dnI5ozQaPBo4rwCWGBoSf+MG\nfn5+tccjIiK4EhdH2S8/y9EXHO6EPsdkDfAVkJeX1+gEsui/S6fT8f6777JkyRI8jIyQ19RQZGRE\nrkbDN99+yxtvvFHbtqmtLYNLSnBppK8kINXXl1t37/7Hx/nywIFkHDlCmSCQCdijfy816FMaXZZK\neZiaiodHQ2/wc6WlpXQKDkbIzKSrWo0z+kLzt4EzhoYsWb6coUOHEhwYiHVhId1rarD/5XPuA8dk\nMqo1Gt4SBH69fl8DFPzS1y5DQy5evUpQUN3aAllZWaxdv5aEpNscPRJHr+/CaD8jCANZ/botN9fd\nonJPNWeOnQFgw4YNzJk9i6aGYKQT8FFoMAESTQzJMpBgKgh0qdbQDpC90NdSmSHWXV0Yd2pMg8/k\n9qYE4uYeR6vR0nqYD72+CUPuKkfQCaSdeMyRGbG0etkbjVJD9VMFlY9KMU8sIEUiIfTtELp/0q12\nErgyv5J9Yw6gKlUy5drk2t0bFxdc4vwXF2nq14TqwmrKsytoN6EtzUOcKLxbxO3NCQg1OnSCQOS+\nEXhFeDY41oTNiRyZGUvLvi0IeTeUo7PjCHjVn5C5wbVtNneLov3MINqNe7E8ul7urTyiQrcwVK3l\ngUzKXaBFvxakn87AwMgQqaEUl67OdHitfb2C3xnnMtn98l60Ki2DNg7AN7J17Z+7sa/HcW/PfZoF\nOlCc/JSwz7vrAxwC3I9+wJmPz+I9qCURy/vWXlOQVMCG9pvJy8nDzs6OvXv3MmHSBIJmB9JuUltM\nbU15fDKd+G/iaevWjsMHDuPSwpnwLb3rje2ZlCOpHJt6Ahtva0bGDkdm+vyNEASBk++f5tHRNJQl\nCoZEDcY9zA1BEKjMq0Kr1mLpZIGBzIA72+9yZGYsczNmY2pjCkB+YgEx4w5Q8aQC507NUTxVkHsj\nD0snC4wtTRjUeRAb1m5geuJUNnXaQud5oXT5sHPtO64sV7J78F6exOdg52NHRXYFlk4W9P7+JW6v\nT8DGywb/V/y4tf42xcnFGFsZ49jBkdMfnuGdojdr65+86Kc+O9AoNThqnbhyUV/HJCUlBd+2vryv\nnNfo341HZsVSmlGGNMOA5KRksSC2SCQSiUSi/1l/9Fy5mBBaJBKJRKK/CJ1Ox6ZNm1jy3XckJSdj\naGBARHg4782fT9euXf+lvszMzHjznXfY8sMPjFer6xTF1gJxMhkh7dvXCVAAeHt7U3LsGGGCgA59\nwWzpC9cCYvHsPzGpVMrCRYt465132LVrFwUFBbi6ujJq1CisrevWKGjt40Pm5cuNBimyDQ1pFxDw\nu4xzxuzZDDp8mA7ACPQFrHXod1PEAO3atfuHAQoAa2trLsXH8/H8+WzZvBmlSoVWpyPIz49dX3zB\n4MGDAbhy/Tpvzp3L2v37MZfJUGo0NG3ShCVffMHm9es5Hx9fp4i3IeAEnJJI8PHxqRegAHBxceGL\nz74AwNm9Odbu1g0GKABKHpbi4agvKv3FV1/wxRdf0Gq4Ny36eFBVUMXFpTeoya9kglJDGRCNPgXV\niwGKBKBCECg5l07aice06F33GSlKFFz68jJapZaWg1qSeS6TZZ4rsfW0+aWGgo7guR0AuLzwKpOv\nTMLQ2ICVrVbj1bcFvb7uWac/CwcLxhyK5EeX5SRsTiRwSgCpRx9x9tPz2Pva02qINxIDKckxydzf\n/YC2o30JmhZIzy97sL3/LvIT8qkqqG70+5PKpNhKJVgeTmVn7CNUNTpOzDuJiY0Jbce2QWogxbK5\nJYV3ixrto+heEdaGUlqrtbSu0REAbDuYioGVEa49XCh7XMaIPcManLC+szUJ35E+ePbzJGbsAc59\nfB6PPh6oilTcjbmHxEDCk8s5zLo/HUun57Ub/Cf54d7TjbUBG/AZ7oNHL3c0Kg1HXz9GWM8w7Oz0\n9SxGjBiBi4sLCxYtYEPgJjQ1Gjx9PHl/1gfMmjULAwMDdIJAeVZ5o/dXnlVOZUUlQ78bXCdAAfqd\nGz3+3o1b624jkQCCQNLOu1xeeEWfrkqiT4sVND0Aaw9rjK2MawMUAA5+TZmROJWsC1lkXczm1Adn\nkBpL9TuBDARu3r4JgIm1CRNPj2N7/11c/fEaLQd6UVNdQ+rhVCSGUlw6N2f8iXEoS5Vc+Ooi+yL3\no3iqQGYh4/LCK3gPaYlbd1cq86q48NVFJBK4v+8BbUe3qXe/ZZllpJ/JoMv7nZAnPU/vZWxsjE6j\nQ6PQ1O7meJGyTEXGyUx279wtBihEIpFIJBKJ/kDiTopfiDspRCKRSPR/mVarZfTIkZyNjSVUqcQT\nfaHeOxIJ1wwNWbN+PRMnTvyX+qypqWH4yy9z4dQp/JVKmgFlQKKpKRZOTpw+fx5HR8c61xw+fJjx\nw4czR6WioanW60CGjw8J9+6JE0D/x6WlpfHRRx8Rs3s33bRa2qOvVfJMMbBeJuP0+fN07NjxP/KZ\narUanU6HiYkJk8aPJ3HnTl7W1k/UVAiskUpJS0/HxaWxEEp9CoWC7OxszM3NcXKqX8wX9PUwUlJS\nMDc3p23btkilUlJSUugcEkLzyko6ajQ0QX//1wwMSDEx4fylS/UCev+PvfMMq+Lc/va9O00poiAo\n0sSKvaLYW4y9xN5bNIkaWxI1RmMSNbH3XsCuib1F7AWxFwRUFBRQlCoCu+95P0xEkU3KOUnOP3nn\nvi4/+PR59p5hz/o9a613mfbVNLZf3EaPn7sXuDd0mTpWll3D3h17SU9PZ/CHg+l9ugeuFVy5OCec\nK3MvocsyIBNAsAjUQxRsLgO15XL8LRYMQLRGwz2zGZmNktrjanFpXgR1RtemSv/KaIpqePRzHGem\nn0OboqXtmjYE9q6M2Whma9sdPD75GJeyzjiWcSQp4il2rra8v6otPs29AZht/wM99nfDp7l1YejE\nF6eIWHAZn2bexJ9+TLPvmlBnTO1813pr022OfvIzw28NxdnHiczHL1nquxwHDwe67e5Cqbr5Q/8I\ngsDmoE34XXpK8C/XbAIOAXdtldg4aihZsyQvIlPQvdQxOu6jAiGRLCYLG6qvIzAyhbdTZe+Twx25\nDItMhlwlp87HtWg2q2m+MFyR2+9ycOhhWvzQjPs7HiB7Lmfsx2N5/Pgx9vb27D20l2RLMmXb+tHk\n68ZW9yVs4kmSbyVTqUdFLs2/zKsnr0iKT8oTKfKt1WLBbDajUr0xsC9avIgpM6bgFODIoAsD8q0P\nxKTha2uuJ+1eOl9oJ1ldA8COjruIPfyQkrXcSX+QQdNvGxPYpzIqOxWPjsdx+sszvEzIoqhnEYZe\nHWx1DEEQ+FY1myFXBxG1LYqIRVcIrBJI0aJFUbZQ0ODz+ggWgTvb7nJ3610sZgu+LX24NP8ybVe0\noVyHgLyxki4/ZUODTajt1Aw41w+3Km/yUpj0JtbX3Uhm/EsGnM1fl5uWy/Z2uygW4IJSrqShUzCL\nFizKW1/FqhXxH+NL9SEFxVN9lp75bgv58otpTJs2rdC9kpCQkJCQkJD4/wHJk0JCQkJCQkLiD7Np\n0ybOHDnCQJ0uX8iZ5oKAj9HIsCFDaNGiRaGGV2uoVCr2HjjA4cOHWblkCTdjY3F1dWXG8OH06tUL\nOzu7An3atGlDcQ8Pjj95QiuzOZ8XRSpwTqNh2dSpkkDxD0Kr1bJlyxY2rFrF8xcvKF26NDKFgvMX\nLhCgUhFoNnMbOAW0Aqoihnk6p9EwcuTIP0WgOHDgAHO++YYLly8DUMHfn9i4OIZYESgAigMBajWh\noaFMnjz5d89ja2tL2bJlf7WNq6srrq6u+crKli3L1Zs3mTljBiFbtqAzGNCoVHzQvTvbpk//zTEB\nRn8ymg0hGzg89ChNZjXCvoR4J6dEp3Jk0FGC6gbRtGlTagfVJuirejj5OLGuxnrSHqRj1JpQyGWU\nU8rxMZi5ihhmys/fn9JVq3IuPBy1Wk2Hrl3RhJ+laAcHgj6rLxqI50WwsvIaBLOAayVXdGk6nMs4\nEdhbDI2kUClQ2SpxKGlPuc7luLf3PoZsAwiwre0OynUOoN74uph0Jop6ORZ6fU7ejti42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u1+clxQbwAzxMJpYhigCdgE2IuR9qI4YOS0f8bG45OHA6OxulQoFcLueD7t35dvZsSpcu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\ntZqa/F8cAAAA0CX5vlfe69+kAAAGtmeffjrOi/YBRUREJiLOj4j/t3t3f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uiKfN+f7qke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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb5321d3850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(num=None, figsize=(20, 10), dpi=80, facecolor='w', edgecolor='k')\n",
    "plt.scatter(pca_comp[:,0],pca_comp[:,1],c=np.array(KMeans_model[3].labels_),s=60)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Mixture Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn import mixture\n",
    "EM_model = mixture.GaussianMixture(n_components=5).fit(train_data_np)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method GaussianMixture.get_params of GaussianMixture(covariance_type='full', init_params='kmeans', max_iter=100,\n",
       "        means_init=None, n_components=5, n_init=1, precisions_init=None,\n",
       "        random_state=None, reg_covar=1e-06, tol=0.001, verbose=0,\n",
       "        verbose_interval=10, warm_start=False, weights_init=None)>"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "EM_model.get_params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5, 5000, 5000)"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "EM_model.covariances_.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.03799891,  0.15172225,  0.043193  ,  0.68644068,  0.08064516])"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "EM_model.weights_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'numpy.ndarray' object is not callable",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-98-2ab1fed60e82>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mprint\u001b[0m \u001b[0mEM_model\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mweights_\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrain_data_np\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;32mprint\u001b[0m \u001b[0mEM_model\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict_proba\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrain_data_np\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;32mprint\u001b[0m \u001b[0mEM_model\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict_proba\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrain_data_np\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m200\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;32mprint\u001b[0m \u001b[0mEM_model\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict_proba\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrain_data_np\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m300\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;32mprint\u001b[0m \u001b[0mEM_model\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict_proba\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrain_data_np\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m700\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: 'numpy.ndarray' object is not callable"
     ]
    }
   ],
   "source": [
    "print EM_model.weights_(train_data_np[0])\n",
    "print EM_model.predict_proba(train_data_np[100])\n",
    "print EM_model.predict_proba(train_data_np[200])\n",
    "print EM_model.predict_proba(train_data_np[300])\n",
    "print EM_model.predict_proba(train_data_np[700])\n",
    "print EM_model.predict_proba(train_data_np[2000])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import itertools\n",
    "\n",
    "import numpy as np\n",
    "from scipy import linalg\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "\n",
    "from sklearn import mixture\n",
    "\n",
    "color_iter = itertools.cycle(['navy', 'c', 'cornflowerblue', 'gold',\n",
    "                              'darkorange'])\n",
    "\n",
    "\n",
    "def plot_results(X, Y_, means, covariances, index, title):\n",
    "    splot = plt.subplot(2, 1, 1 + index)\n",
    "    for i, (mean, covar, color) in enumerate(zip(\n",
    "            means, covariances, color_iter)):\n",
    "        v, w = linalg.eigh(covar)\n",
    "        v = 2. * np.sqrt(2.) * np.sqrt(v)\n",
    "        u = w[0] / linalg.norm(w[0])\n",
    "        # as the DP will not use every component it has access to\n",
    "        # unless it needs it, we shouldn't plot the redundant\n",
    "        # components.\n",
    "        if not np.any(Y_ == i):\n",
    "            continue\n",
    "        plt.scatter(X[Y_ == i, 0], X[Y_ == i, 1], .8, color=color)\n",
    "\n",
    "        # Plot an ellipse to show the Gaussian component\n",
    "        angle = np.arctan(u[1] / u[0])\n",
    "        angle = 180. * angle / np.pi  # convert to degrees\n",
    "        ell = mpl.patches.Ellipse(mean, v[0], v[1], 180. + angle, color=color)\n",
    "        ell.set_clip_box(splot.bbox)\n",
    "        ell.set_alpha(0.5)\n",
    "        splot.add_artist(ell)\n",
    "\n",
    "    plt.xlim(-9., 5.)\n",
    "    plt.ylim(-3., 6.)\n",
    "    plt.xticks(())\n",
    "    plt.yticks(())\n",
    "    plt.title(title)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/praveen/anaconda/lib/python2.7/site-packages/ipykernel/__main__.py:29: RuntimeWarning: invalid value encountered in double_scalars\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb5881e9890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_results(train_data_np, EM_model.predict(train_data_np), EM_model.means_, EM_model.covariances_, 0,\n",
    "             'Gaussian Mixture')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# Creating test and train dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data_full = pd.DataFrame(train_data_np)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data_full.columns = vocab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data_full['_class_label_'] = np.array(KMeans_model[3].labels_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "train_data = data_full.sample(frac=0.8,random_state=200)\n",
    "test_data = data_full.drop(train_data.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train_data.to_csv('train_data.csv', sep='\\t', encoding='utf-8',index=False)\n",
    "test_data.to_csv('test_data.csv', sep='\\t', encoding='utf-8',index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Random Forest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "train_rf = RandomForestClassifier(n_estimators=100).fit(train_data.drop('_class_label_', 1),train_data['_class_label_'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "output = train_rf.predict(test_data.drop('_class_label_', 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "sk.metrics.accuracy_score(test_data['_class_label_'],output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "sk.metrics.confusion_matrix(test_data['_class_label_'],output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "np.bincount(test_data['_class_label_'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}