From 3651471f17ab66fa06adb8026fe5cd6e8d8c24d7 Mon Sep 17 00:00:00 2001
From: Zack Cooper <zackjcooper@gmail.com>
Date: Fri, 13 Feb 2015 10:59:58 -0500
Subject: [PATCH 1/6] built frame of solution. Broke out data ingestion to its
 own file

---
 corpus_build.py            |  86 +++++++++
 lang classifier live.ipynb | 361 +++++++++++++++++++++++++++++++++++++
 2 files changed, 447 insertions(+)
 create mode 100644 corpus_build.py
 create mode 100644 lang classifier live.ipynb

diff --git a/corpus_build.py b/corpus_build.py
new file mode 100644
index 0000000..d0d74d5
--- /dev/null
+++ b/corpus_build.py
@@ -0,0 +1,86 @@
+import glob
+import os
+import pandas as pd
+import re
+
+
+file_types = {'.clj': 'clojure',
+'.cljs': 'clojure',
+'.clojure': 'clojure',
+'.edn': 'clojure',
+'.hs': 'haskell',
+'.lhs': 'haskell',
+'.ghc': 'haskell',
+'.java': 'java',
+'.class': 'java',
+'.js': 'javascript',
+'.javascript': 'javascript',
+'.ml': 'ocaml',
+'.mli': 'ocaml',
+'.ocaml': 'ocaml',
+'.perl': 'perl',
+'.php': 'php',
+'.phtml': 'php',
+'.php3': 'php',
+'.php4': 'php',
+'.php5': 'php',
+'.phps': 'php',
+'.python3': 'python',
+'.python2': 'python',
+'.py': 'python',
+'.jruby': 'ruby',
+'.scala': 'scala',
+'.racket': 'scheme',
+'.scm': 'scheme',
+'.ss': 'scheme',
+'.clojure': 'clojure'}
+
+hit_num = {"clojure": "1",
+"haskell": "2",
+"java": "3",
+"javascript": "4",
+"ocaml": "5",
+"perl": "6",
+"php": "7",
+"python": "8",
+"ruby": "9",
+"scala": "10",
+"scheme": "11"}
+
+raw_file_list = [filename
+                 for filename in glob.iglob(os.path.join('corpus/bench',
+                                                         '*', '*'))
+                 if os.path.splitext(filename)[1] in file_types.keys()]
+
+
+class Corpus():
+
+
+    def read_process_file(self, file_name):
+        with open(file_name) as f:
+            return f.read()
+
+    def parenthesis_count(self, a_string):
+        return len(re.findall(r'[()]', a_string)) / len(a_string)
+
+    def build_dataframe(self):
+        a_dataframe = pd.DataFrame([file_types[os.path.splitext(file)[1]]
+                                    for file
+                                    in raw_file_list], columns=['file_type'])
+        a_dataframe['hit_num'] = a_dataframe['file_type'].map(hit_num)
+        raw_text = [self.read_process_file(file) for file in raw_file_list]
+        a_dataframe['raw_text'] = raw_text
+
+        return a_dataframe
+
+    def feature_breakout(self, a_dataframe):
+
+        a_dataframe['paren_count'] = [self.parenthesis_count(row)
+                                      for row in a_dataframe['raw_text']]
+        return a_dataframe
+
+
+    def compl_df_build(self):
+        corpus = self.build_dataframe()
+        corpus = self.feature_breakout(corpus)
+        return corpus
diff --git a/lang classifier live.ipynb b/lang classifier live.ipynb
new file mode 100644
index 0000000..32aa0d0
--- /dev/null
+++ b/lang classifier live.ipynb	
@@ -0,0 +1,361 @@
+{
+ "metadata": {
+  "name": "",
+  "signature": "sha256:517c0af79cf5d3b4fc45e900b47c2c280b55540e2ca9ee92e073faaa3e7a2a55"
+ },
+ "nbformat": 3,
+ "nbformat_minor": 0,
+ "worksheets": [
+  {
+   "cells": [
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "from corpus_build import Corpus, hit_num\n",
+      "corpus = Corpus()\n",
+      "corpus_df = corpus.compl_df_build()\n",
+      "corpus_df.head()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "html": [
+        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+        "<table border=\"1\" class=\"dataframe\">\n",
+        "  <thead>\n",
+        "    <tr style=\"text-align: right;\">\n",
+        "      <th></th>\n",
+        "      <th>file_type</th>\n",
+        "      <th>hit_num</th>\n",
+        "      <th>raw_text</th>\n",
+        "      <th>paren_count</th>\n",
+        "    </tr>\n",
+        "  </thead>\n",
+        "  <tbody>\n",
+        "    <tr>\n",
+        "      <th>0</th>\n",
+        "      <td> clojure</td>\n",
+        "      <td> 1</td>\n",
+        "      <td> ;; The Computer Language Benchmarks Game\\n;; h...</td>\n",
+        "      <td> 0.071901</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>1</th>\n",
+        "      <td> clojure</td>\n",
+        "      <td> 1</td>\n",
+        "      <td> ;; The Computer Language Benchmarks Game\\n;; h...</td>\n",
+        "      <td> 0.071704</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>2</th>\n",
+        "      <td> clojure</td>\n",
+        "      <td> 1</td>\n",
+        "      <td> ;; The Computer Language Benchmarks Game\\n;; h...</td>\n",
+        "      <td> 0.063995</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>3</th>\n",
+        "      <td> haskell</td>\n",
+        "      <td> 2</td>\n",
+        "      <td> --\\n-- The Computer Language Benchmarks Game\\n...</td>\n",
+        "      <td> 0.024707</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>4</th>\n",
+        "      <td> haskell</td>\n",
+        "      <td> 2</td>\n",
+        "      <td> --\\n-- The Computer Language Benchmarks Game\\n...</td>\n",
+        "      <td> 0.024352</td>\n",
+        "    </tr>\n",
+        "  </tbody>\n",
+        "</table>\n",
+        "</div>"
+       ],
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 2,
+       "text": [
+        "  file_type hit_num                                           raw_text  \\\n",
+        "0   clojure       1  ;; The Computer Language Benchmarks Game\\n;; h...   \n",
+        "1   clojure       1  ;; The Computer Language Benchmarks Game\\n;; h...   \n",
+        "2   clojure       1  ;; The Computer Language Benchmarks Game\\n;; h...   \n",
+        "3   haskell       2  --\\n-- The Computer Language Benchmarks Game\\n...   \n",
+        "4   haskell       2  --\\n-- The Computer Language Benchmarks Game\\n...   \n",
+        "\n",
+        "   paren_count  \n",
+        "0     0.071901  \n",
+        "1     0.071704  \n",
+        "2     0.063995  \n",
+        "3     0.024707  \n",
+        "4     0.024352  "
+       ]
+      }
+     ],
+     "prompt_number": 2
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "corpus[''] = []\n",
+      "corpus.head()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 5
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 67
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 67
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 67
+    },
+    {
+     "cell_type": "heading",
+     "level": 1,
+     "metadata": {},
+     "source": [
+      "Choosing the Best Model"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "from sklearn.naive_bayes import GaussianNB, MultinomialNB, BernoulliNB\n",
+      "from sklearn.neighbors import KNeighborsClassifier\n",
+      "from sklearn.tree import DecisionTreeClassifier\n",
+      "from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier\n",
+      "from sklearn.cross_validation import train_test_split\n",
+      "from sklearn.cluster import KMeans\n",
+      "from sklearn import metrics\n",
+      "from sklearn.cross_validation import cross_val_score\n",
+      "import numpy as np\n",
+      "import seaborn as sbn\n",
+      "import matplotlib.pyplot as plt\n",
+      "%matplotlib inline\n",
+      "\n",
+      "corpus_features = corpus.drop(['raw_text','file_type'], axis=1)\n",
+      "\n",
+      "corp_train = corpus_features.values[0::,1::]\n",
+      "corp_answer = corpus_features.values[0::,0]\n",
+      "\n",
+      "x_train, x_test, y_train, y_test = train_test_split(corp_train, corp_answer, test_size=.4, random_state=0)\n",
+      "\n",
+      "model_list = [KNeighborsClassifier(), RandomForestClassifier(), DecisionTreeClassifier()]\n",
+      "# BernoulliNB(), MultinomialNB(), AdaBoostClassifier(), GaussianNB(), \n",
+      "\n",
+      "def run_test_model(classifier, x_train, y_train, x_test, y_test, orig_train, orig_answ):\n",
+      "\n",
+      "    classifier.fit(x_train, y_train)\n",
+      "    predicted = classifier.predict(x_test)\n",
+      "    return metrics.f1_score(y_test, predicted)\n",
+      "\n",
+      "def run_rank_multiple_models(list_of_models):\n",
+      "    return [(model, run_test_model(model, x_train, y_train, x_test, y_test, corp_train, corp_answer)) \n",
+      "            for model \n",
+      "            in list_of_models]"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 175
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "model_results = run_rank_multiple_models(model_list)\n",
+      "model_results.sort(key=lambda x: x[1])\n",
+      "x_labels = [group[0] for group in model_results]\n",
+      "x_values = [group[1] for group in model_results]  \n",
+      "width = .75\n",
+      "height = np.arange(len(model_results))\n",
+      "mean = np.array(x_values).mean()\n",
+      "\n",
+      "plt.yticks(height+width/2., x_labels)\n",
+      "plt.barh(height, x_values, width, color = sbn.color_palette())\n",
+      "plt.axvline(mean, c='r')\n",
+      "plt.rc('figure', figsize=(10, 5))\n",
+      "plt.show()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "png": 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diTu3n0gab2aXACPwaOh5lFMkTQuesmkqMCVFGmvJ7mIlUsCSHkoqUiOAn0ga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\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x10ebb2828>"
+       ]
+      }
+     ],
+     "prompt_number": 176
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "run_test_model(DecisionTreeClassifier(), x_train, y_train, x_test, y_test, corp_train, corp_answer)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 177,
+       "text": [
+        "0.18077668222273341"
+       ]
+      }
+     ],
+     "prompt_number": 177
+    },
+    {
+     "cell_type": "heading",
+     "level": 1,
+     "metadata": {},
+     "source": [
+      "Pass in live code file for response"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "def reverse_dict_match(a_dictionary, a_list):\n",
+      "    \"\"\"Pass this function a dictionary and a list. it will reverse the order of the dict\n",
+      "    and match the first values of the list with the dict.\"\"\"\n",
+      "    reversed_dict = dict((v,k) for k,v in a_dictionary.items())\n",
+      "    return [(reversed_dict.get(x),y) for x,y in a_list]\n",
+      "\n",
+      "def check_code_snippet(a_file, corp_train, corp_answer):\n",
+      "    \n",
+      "    # Ingest file\n",
+      "    a_file_df = pd.DataFrame([read_process_file(a_file)], columns=['raw_text'])\n",
+      " \n",
+      "    # Turn file into features\n",
+      "    a_file_df['paren_count'] = parenthesis_count(a_file_df['raw_text'][0])\n",
+      "    a_cleaned_df = a_file_df.drop(['raw_text'], axis=1)\n",
+      "\n",
+      "    # Run model\n",
+      "    model_created = GaussianNB()\n",
+      "    model_created.fit(corp_train, corp_answer)\n",
+      "    predicted = model_created.predict(a_cleaned_df.values)\n",
+      "    predict_prob = model_created.predict_proba(a_cleaned_df.values)\n",
+      "    \n",
+      "    #Pretty response\n",
+      "    answer_list = list(zip(model_created.classes_, predict_prob[0]))\n",
+      "    answer_list.sort(key=lambda x: x[1], reverse=True)\n",
+      "    return reverse_dict_match(hit_num, answer_list)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 348
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "check_code_snippet('test/1', corp_train, corp_answer)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 350,
+       "text": [
+        "[('java', 0.23709565168200461),\n",
+        " ('perl', 0.15122183416794088),\n",
+        " ('ruby', 0.13694881776324136),\n",
+        " ('ocaml', 0.12725804928624451),\n",
+        " ('python', 0.08496717978985284),\n",
+        " ('haskell', 0.081919233740987057),\n",
+        " ('php', 0.064364558495229707),\n",
+        " ('scala', 0.063449250754175929),\n",
+        " ('javascript', 0.049179273881515481),\n",
+        " ('clojure', 0.0035955804751662455),\n",
+        " ('scheme', 5.6996364138916492e-07)]"
+       ]
+      }
+     ],
+     "prompt_number": 350
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 350
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 329
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 336
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 327
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [],
+     "language": "python",
+     "metadata": {},
+     "outputs": []
+    }
+   ],
+   "metadata": {}
+  }
+ ]
+}
\ No newline at end of file

From 18b19c8683141c82d346aa61c2978df0ea6efe0f Mon Sep 17 00:00:00 2001
From: Zack Cooper <zackjcooper@gmail.com>
Date: Fri, 13 Feb 2015 16:35:33 -0500
Subject: [PATCH 2/6] testing against proper test data. All bare bones still in
 tact. Just adding features at this point. Rest is complete!!!

---
 corpus_build.py            | 144 ++++++++------
 lang classifier live.ipynb | 375 ++++++++++++++++++++++++++-----------
 test/26                    |  35 ----
 test/27                    |  20 --
 test_fixed.csv             |   1 +
 5 files changed, 348 insertions(+), 227 deletions(-)
 delete mode 100644 test/26
 delete mode 100644 test/27
 create mode 100644 test_fixed.csv

diff --git a/corpus_build.py b/corpus_build.py
index d0d74d5..1b54621 100644
--- a/corpus_build.py
+++ b/corpus_build.py
@@ -5,82 +5,106 @@
 
 
 file_types = {'.clj': 'clojure',
-'.cljs': 'clojure',
-'.clojure': 'clojure',
-'.edn': 'clojure',
-'.hs': 'haskell',
-'.lhs': 'haskell',
-'.ghc': 'haskell',
-'.java': 'java',
-'.class': 'java',
-'.js': 'javascript',
-'.javascript': 'javascript',
-'.ml': 'ocaml',
-'.mli': 'ocaml',
-'.ocaml': 'ocaml',
-'.perl': 'perl',
-'.php': 'php',
-'.phtml': 'php',
-'.php3': 'php',
-'.php4': 'php',
-'.php5': 'php',
-'.phps': 'php',
-'.python3': 'python',
-'.python2': 'python',
-'.py': 'python',
-'.jruby': 'ruby',
-'.scala': 'scala',
-'.racket': 'scheme',
-'.scm': 'scheme',
-'.ss': 'scheme',
-'.clojure': 'clojure'}
+              '.cljs': 'clojure',
+              '.clojure': 'clojure',
+              '.edn': 'clojure',
+              '.hs': 'haskell',
+              '.lhs': 'haskell',
+              '.ghc': 'haskell',
+              '.java': 'java',
+              '.class': 'java',
+              '.js': 'javascript',
+              '.javascript': 'javascript',
+              '.ml': 'ocaml',
+              '.mli': 'ocaml',
+              '.ocaml': 'ocaml',
+              '.perl': 'perl',
+              '.php': 'php',
+              '.phtml': 'php',
+              '.php3': 'php',
+              '.php4': 'php',
+              '.php5': 'php',
+              '.phps': 'php',
+              '.python3': 'python',
+              '.python2': 'python',
+              '.py': 'python',
+              '.jruby': 'ruby',
+              '.scala': 'scala',
+              '.racket': 'scheme',
+              '.scm': 'scheme',
+              '.ss': 'scheme',
+              '.clojure': 'clojure'}
 
 hit_num = {"clojure": "1",
-"haskell": "2",
-"java": "3",
-"javascript": "4",
-"ocaml": "5",
-"perl": "6",
-"php": "7",
-"python": "8",
-"ruby": "9",
-"scala": "10",
-"scheme": "11"}
-
-raw_file_list = [filename
-                 for filename in glob.iglob(os.path.join('corpus/bench',
-                                                         '*', '*'))
+           "haskell": "2",
+           "java": "3",
+           "javascript": "4",
+           "ocaml": "5",
+           "perl": "6",
+           "php": "7",
+           "python": "8",
+           "ruby": "9",
+           "scala": "10",
+           "scheme": "11"}
+
+raw_file_list = [filename for filename in
+                 glob.iglob(os.path.join('corpus/bench', '*', '*'))
                  if os.path.splitext(filename)[1] in file_types.keys()]
 
+feature_list = [('parent_count', "[()]"),
+                ('double_colon', "::"),
+                ('let_exists', r"\blet\b"),
+                ('less_minus', "((\<\-))"),
+                ('paren_star', "(\(\*|\*\))"),
+                ('def_exists', r"\bdef\b"),
+                ]
+
 
 class Corpus():
 
+    def __init__(self, file_list=[]):
+        self.file_list = file_list
 
     def read_process_file(self, file_name):
         with open(file_name) as f:
             return f.read()
 
-    def parenthesis_count(self, a_string):
-        return len(re.findall(r'[()]', a_string)) / len(a_string)
+    def build_dataframe(self, snippet=True):
+        raw_text = [self.read_process_file(file) for file in self.file_list]
 
-    def build_dataframe(self):
-        a_dataframe = pd.DataFrame([file_types[os.path.splitext(file)[1]]
-                                    for file
-                                    in raw_file_list], columns=['file_type'])
-        a_dataframe['hit_num'] = a_dataframe['file_type'].map(hit_num)
-        raw_text = [self.read_process_file(file) for file in raw_file_list]
-        a_dataframe['raw_text'] = raw_text
+        if snippet:
+            a_dataframe = pd.DataFrame(raw_text, columns=['raw_text'])
+        else:
+            a_dataframe = pd.DataFrame([file_types[os.path.splitext(file)[1]]
+                                        for file in self.file_list],
+                                       columns=['file_type'])
+
+            a_dataframe['hit_num'] = a_dataframe['file_type'].map(hit_num)
+            a_dataframe['raw_text'] = raw_text
 
         return a_dataframe
 
-    def feature_breakout(self, a_dataframe):
+    def feat_lookup(self, regex, a_dataframe):
+        return [(len(re.findall(regex, a_row))/len(a_row))
+                for a_row in a_dataframe['raw_text']]
 
-        a_dataframe['paren_count'] = [self.parenthesis_count(row)
-                                      for row in a_dataframe['raw_text']]
-        return a_dataframe
+    def feature_breakout(self, a_df):
+
+        for name, regex in feature_list:
+            a_df[name] = self.feat_lookup(regex, a_df)
+
+        return a_df
+
+    def compl_df_build(self, snippet=True):
+        a_df = self.build_dataframe(snippet)
+        a_df = self.feature_breakout(a_df)
+        cleaned_df = self.clean_df(a_df, snippet)
+        return cleaned_df
+
+    def clean_df(self, a_df, snippet):
+        cleaned_df = a_df.drop(['raw_text'], axis=1)
 
+        if not snippet:
+            cleaned_df = cleaned_df.drop(['file_type'], axis=1)
 
-    def compl_df_build(self):
-        corpus = self.build_dataframe()
-        corpus = self.feature_breakout(corpus)
-        return corpus
+        return cleaned_df
diff --git a/lang classifier live.ipynb b/lang classifier live.ipynb
index 32aa0d0..5f96e25 100644
--- a/lang classifier live.ipynb	
+++ b/lang classifier live.ipynb	
@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:517c0af79cf5d3b4fc45e900b47c2c280b55540e2ca9ee92e073faaa3e7a2a55"
+  "signature": "sha256:0f9223d2ddd3e37046d43bb1578139df3c7fa29d3b2f15da299cf9a0a8978d11"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -12,9 +12,11 @@
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "from corpus_build import Corpus, hit_num\n",
-      "corpus = Corpus()\n",
-      "corpus_df = corpus.compl_df_build()\n",
+      "from corpus_build import Corpus, hit_num, raw_file_list\n",
+      "import pandas as pd\n",
+      "\n",
+      "corpus = Corpus(raw_file_list)\n",
+      "corpus_df = corpus.compl_df_build(False)\n",
       "corpus_df.head()"
      ],
      "language": "python",
@@ -27,47 +29,65 @@
         "  <thead>\n",
         "    <tr style=\"text-align: right;\">\n",
         "      <th></th>\n",
-        "      <th>file_type</th>\n",
         "      <th>hit_num</th>\n",
-        "      <th>raw_text</th>\n",
-        "      <th>paren_count</th>\n",
+        "      <th>parent_count</th>\n",
+        "      <th>double_colon</th>\n",
+        "      <th>let_exists</th>\n",
+        "      <th>less_minus</th>\n",
+        "      <th>paren_star</th>\n",
+        "      <th>def_exists</th>\n",
         "    </tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
         "      <th>0</th>\n",
-        "      <td> clojure</td>\n",
         "      <td> 1</td>\n",
-        "      <td> ;; The Computer Language Benchmarks Game\\n;; h...</td>\n",
         "      <td> 0.071901</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002066</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001240</td>\n",
+        "      <td> 0.000413</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>1</th>\n",
-        "      <td> clojure</td>\n",
         "      <td> 1</td>\n",
-        "      <td> ;; The Computer Language Benchmarks Game\\n;; h...</td>\n",
         "      <td> 0.071704</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002699</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000771</td>\n",
+        "      <td> 0.000386</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>2</th>\n",
-        "      <td> clojure</td>\n",
         "      <td> 1</td>\n",
-        "      <td> ;; The Computer Language Benchmarks Game\\n;; h...</td>\n",
         "      <td> 0.063995</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002695</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000337</td>\n",
+        "      <td> 0.000337</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>3</th>\n",
-        "      <td> haskell</td>\n",
         "      <td> 2</td>\n",
-        "      <td> --\\n-- The Computer Language Benchmarks Game\\n...</td>\n",
         "      <td> 0.024707</td>\n",
+        "      <td> 0.002471</td>\n",
+        "      <td> 0.002471</td>\n",
+        "      <td> 0.000618</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>4</th>\n",
-        "      <td> haskell</td>\n",
         "      <td> 2</td>\n",
-        "      <td> --\\n-- The Computer Language Benchmarks Game\\n...</td>\n",
         "      <td> 0.024352</td>\n",
+        "      <td> 0.002118</td>\n",
+        "      <td> 0.002647</td>\n",
+        "      <td> 0.000529</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
@@ -75,37 +95,134 @@
        ],
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 2,
+       "prompt_number": 47,
        "text": [
-        "  file_type hit_num                                           raw_text  \\\n",
-        "0   clojure       1  ;; The Computer Language Benchmarks Game\\n;; h...   \n",
-        "1   clojure       1  ;; The Computer Language Benchmarks Game\\n;; h...   \n",
-        "2   clojure       1  ;; The Computer Language Benchmarks Game\\n;; h...   \n",
-        "3   haskell       2  --\\n-- The Computer Language Benchmarks Game\\n...   \n",
-        "4   haskell       2  --\\n-- The Computer Language Benchmarks Game\\n...   \n",
+        "  hit_num  parent_count  double_colon  let_exists  less_minus  paren_star  \\\n",
+        "0       1      0.071901      0.000000    0.002066    0.000000    0.001240   \n",
+        "1       1      0.071704      0.000000    0.002699    0.000000    0.000771   \n",
+        "2       1      0.063995      0.000000    0.002695    0.000000    0.000337   \n",
+        "3       2      0.024707      0.002471    0.002471    0.000618    0.000000   \n",
+        "4       2      0.024352      0.002118    0.002647    0.000529    0.000000   \n",
         "\n",
-        "   paren_count  \n",
-        "0     0.071901  \n",
-        "1     0.071704  \n",
-        "2     0.063995  \n",
-        "3     0.024707  \n",
-        "4     0.024352  "
+        "   def_exists  \n",
+        "0    0.000413  \n",
+        "1    0.000386  \n",
+        "2    0.000337  \n",
+        "3    0.000000  \n",
+        "4    0.000000  "
        ]
       }
      ],
-     "prompt_number": 2
+     "prompt_number": 47
     },
     {
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "corpus[''] = []\n",
-      "corpus.head()"
+      "import glob\n",
+      "import os\n",
+      "test_file_list = [filename for filename in\n",
+      "                 glob.iglob(os.path.join('test/', '*'))]\n",
+      "test_info = Corpus(test_file_list)\n",
+      "test_info_df = test_info.compl_df_build(True)\n",
+      "test_info_df['answers'] = pd.read_csv('test_fixed.csv', dtype='object')\n",
+      "test_info_df.head()"
      ],
      "language": "python",
      "metadata": {},
-     "outputs": [],
-     "prompt_number": 5
+     "outputs": [
+      {
+       "html": [
+        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+        "<table border=\"1\" class=\"dataframe\">\n",
+        "  <thead>\n",
+        "    <tr style=\"text-align: right;\">\n",
+        "      <th></th>\n",
+        "      <th>parent_count</th>\n",
+        "      <th>double_colon</th>\n",
+        "      <th>let_exists</th>\n",
+        "      <th>less_minus</th>\n",
+        "      <th>paren_star</th>\n",
+        "      <th>def_exists</th>\n",
+        "      <th>answers</th>\n",
+        "    </tr>\n",
+        "  </thead>\n",
+        "  <tbody>\n",
+        "    <tr>\n",
+        "      <th>0</th>\n",
+        "      <td> 0.045734</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001759</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 1</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>1</th>\n",
+        "      <td> 0.063037</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 4</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>2</th>\n",
+        "      <td> 0.042795</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000058</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000058</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 4</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>3</th>\n",
+        "      <td> 0.047059</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 4</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>4</th>\n",
+        "      <td> 0.015708</td>\n",
+        "      <td> 0.000561</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000281</td>\n",
+        "      <td> 0.002805</td>\n",
+        "      <td> 9</td>\n",
+        "    </tr>\n",
+        "  </tbody>\n",
+        "</table>\n",
+        "</div>"
+       ],
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 105,
+       "text": [
+        "   parent_count  double_colon  let_exists  less_minus  paren_star  def_exists  \\\n",
+        "0      0.045734      0.000000    0.001759           0    0.000000    0.000000   \n",
+        "1      0.063037      0.000000    0.000000           0    0.000000    0.000000   \n",
+        "2      0.042795      0.000000    0.000058           0    0.000058    0.000000   \n",
+        "3      0.047059      0.000000    0.000000           0    0.000000    0.000000   \n",
+        "4      0.015708      0.000561    0.000000           0    0.000281    0.002805   \n",
+        "\n",
+        "  answers  \n",
+        "0       1  \n",
+        "1       4  \n",
+        "2       4  \n",
+        "3       4  \n",
+        "4       9  "
+       ]
+      }
+     ],
+     "prompt_number": 105
     },
     {
      "cell_type": "code",
@@ -114,7 +231,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 67
+     "prompt_number": 101
     },
     {
      "cell_type": "code",
@@ -123,7 +240,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 67
+     "prompt_number": 38
     },
     {
      "cell_type": "code",
@@ -132,7 +249,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 67
+     "prompt_number": 38
     },
     {
      "cell_type": "heading",
@@ -159,90 +276,152 @@
       "import matplotlib.pyplot as plt\n",
       "%matplotlib inline\n",
       "\n",
-      "corpus_features = corpus.drop(['raw_text','file_type'], axis=1)\n",
-      "\n",
-      "corp_train = corpus_features.values[0::,1::]\n",
-      "corp_answer = corpus_features.values[0::,0]\n",
-      "\n",
-      "x_train, x_test, y_train, y_test = train_test_split(corp_train, corp_answer, test_size=.4, random_state=0)\n",
+      "corp_train = corpus_df.values[0::,1::]\n",
+      "corp_answer = corpus_df.values[0::,0]\n",
+      "test_train = test_info_df.values[0::,:-1:]\n",
+      "test_answer = test_info_df.values[0::1,-1]\n",
       "\n",
       "model_list = [KNeighborsClassifier(), RandomForestClassifier(), DecisionTreeClassifier()]\n",
       "# BernoulliNB(), MultinomialNB(), AdaBoostClassifier(), GaussianNB(), \n",
       "\n",
-      "def run_test_model(classifier, x_train, y_train, x_test, y_test, orig_train, orig_answ):\n",
+      "def run_test_model(classifier, x_train, y_train, x_test, y_test):\n",
       "\n",
       "    classifier.fit(x_train, y_train)\n",
       "    predicted = classifier.predict(x_test)\n",
       "    return metrics.f1_score(y_test, predicted)\n",
       "\n",
       "def run_rank_multiple_models(list_of_models):\n",
-      "    return [(model, run_test_model(model, x_train, y_train, x_test, y_test, corp_train, corp_answer)) \n",
+      "    return [(model, run_test_model(model, corp_train, corp_answer, test_train, test_answer)) \n",
       "            for model \n",
       "            in list_of_models]"
      ],
      "language": "python",
      "metadata": {},
-     "outputs": [],
-     "prompt_number": 175
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 106,
+       "text": [
+        "array([[0.04573438874230431, 0.0, 0.001759014951627089, 0.0, 0.0, 0.0],\n",
+        "       [0.06303724928366762, 0.0, 0.0, 0.0, 0.0, 0.0],\n",
+        "       [0.0427946089160235, 0.0, 5.7597051030987213e-05, 0.0,\n",
+        "        5.7597051030987213e-05, 0.0],\n",
+        "       [0.047058823529411764, 0.0, 0.0, 0.0, 0.0, 0.0],\n",
+        "       [0.01570827489481066, 0.0005610098176718093, 0.0, 0.0,\n",
+        "        0.00028050490883590464, 0.002805049088359046],\n",
+        "       [0.0, 0.0, 0.0, 0.0, 0.0, 0.002036659877800407],\n",
+        "       [0.00816326530612245, 0.0, 0.0, 0.0, 0.0, 0.00816326530612245],\n",
+        "       [0.013328977458346946, 0.000914733747141457, 6.533812479581836e-05,\n",
+        "        0.0004573668735707285, 0.0, 0.00013067624959163673],\n",
+        "       [0.05806451612903226, 0.0064516129032258064, 0.0,\n",
+        "        0.0064516129032258064, 0.0, 0.0],\n",
+        "       [0.0137524557956778, 0.003929273084479371, 0.0004911591355599214,\n",
+        "        0.0029469548133595285, 0.0, 0.0],\n",
+        "       [0.12435233160621761, 0.0, 0.0, 0.0, 0.0, 0.0],\n",
+        "       [0.08866995073891626, 0.0, 0.0, 0.0, 0.0, 0.0],\n",
+        "       [0.2222222222222222, 0.0, 0.0, 0.0, 0.0, 0.0],\n",
+        "       [0.11084624553039332, 0.0, 0.0008939213349225268, 0.0, 0.0, 0.0],\n",
+        "       [0.006644518272425249, 0.0, 0.0, 0.0, 0.0, 0.0],\n",
+        "       [0.0065717415115005475, 0.0, 0.0, 0.0, 0.0, 0.0],\n",
+        "       [0.027181688125894134, 0.001072961373390558, 0.0, 0.0,\n",
+        "        0.000715307582260372, 0.00178826895565093],\n",
+        "       [0.014606155451225874, 0.0, 0.0, 0.0, 0.0, 0.004173187271778821],\n",
+        "       [0.019253910950661854, 0.00030084235860409147, 0.0, 0.0, 0.0, 0.0],\n",
+        "       [0.058997050147492625, 0.0, 0.0, 0.0, 0.0029498525073746312, 0.0],\n",
+        "       [0.0979020979020979, 0.0, 0.0, 0.0, 0.0, 0.0],\n",
+        "       [0.05322415557830092, 0.0015353121801432957, 0.0, 0.0, 0.0, 0.0],\n",
+        "       [0.026448029621793177, 0.0001322401481089659, 0.004892885480031738,\n",
+        "        0.0, 0.005554086220576567, 0.0],\n",
+        "       [0.017391304347826087, 0.0, 0.0052173913043478265, 0.0, 0.0, 0.0],\n",
+        "       [0.02680067001675042, 0.0, 0.0016750418760469012, 0.0, 0.0,\n",
+        "        0.0016750418760469012],\n",
+        "       [0.03986710963455149, 0.0, 0.0, 0.0, 0.0, 0.0],\n",
+        "       [0.028050490883590462, 0.0, 0.0, 0.0, 0.0, 0.001402524544179523],\n",
+        "       [0.03680981595092025, 0.0, 0.0, 0.0, 0.0, 0.012269938650306749],\n",
+        "       [0.029607698001480384, 0.0, 0.0, 0.0, 0.0, 0.0030594621268196396],\n",
+        "       [0.05389221556886228, 0.0, 0.0, 0.0, 0.0, 0.0]], dtype=object)"
+       ]
+      }
+     ],
+     "prompt_number": 106
     },
     {
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "model_results = run_rank_multiple_models(model_list)\n",
-      "model_results.sort(key=lambda x: x[1])\n",
-      "x_labels = [group[0] for group in model_results]\n",
-      "x_values = [group[1] for group in model_results]  \n",
-      "width = .75\n",
-      "height = np.arange(len(model_results))\n",
-      "mean = np.array(x_values).mean()\n",
-      "\n",
-      "plt.yticks(height+width/2., x_labels)\n",
-      "plt.barh(height, x_values, width, color = sbn.color_palette())\n",
-      "plt.axvline(mean, c='r')\n",
-      "plt.rc('figure', figsize=(10, 5))\n",
-      "plt.show()"
+      "run_test_model(DecisionTreeClassifier(), corp_train, corp_answer, test_train, test_answer)"
      ],
      "language": "python",
      "metadata": {},
      "outputs": [
+      {
+       "output_type": "stream",
+       "stream": "stderr",
+       "text": [
+        "/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py:1773: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true samples.\n",
+        "  'recall', 'true', average, warn_for)\n"
+       ]
+      },
       {
        "metadata": {},
-       "output_type": "display_data",
-       "png": 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diTu3n0gab2aXACPwaOh5lFMkTQuesmkqMCVFGmvJ7mIlUsCSHkoqUiOAn0ga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\n",
+       "output_type": "pyout",
+       "prompt_number": 107,
        "text": [
-        "<matplotlib.figure.Figure at 0x10ebb2828>"
+        "0.4173737373737374"
        ]
       }
      ],
-     "prompt_number": 176
+     "prompt_number": 107
     },
     {
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "run_test_model(DecisionTreeClassifier(), x_train, y_train, x_test, y_test, corp_train, corp_answer)"
+      "model_results = run_rank_multiple_models(model_list)\n",
+      "model_results.sort(key=lambda x: x[1])\n",
+      "x_labels = [group[0] for group in model_results]\n",
+      "x_values = [group[1] for group in model_results]  \n",
+      "width = .75\n",
+      "height = np.arange(len(model_results))\n",
+      "mean = np.array(x_values).mean()\n",
+      "\n",
+      "plt.yticks(height+width/2., x_labels)\n",
+      "plt.barh(height, x_values, width, color = sbn.color_palette())\n",
+      "plt.axvline(mean, c='r')\n",
+      "plt.rc('figure', figsize=(10, 5))\n",
+      "plt.show()"
      ],
      "language": "python",
      "metadata": {},
      "outputs": [
       {
-       "metadata": {},
-       "output_type": "pyout",
-       "prompt_number": 177,
-       "text": [
-        "0.18077668222273341"
+       "ename": "ValueError",
+       "evalue": "Found array with dim 30. Expected 1",
+       "output_type": "pyerr",
+       "traceback": [
+        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+        "\u001b[0;32m<ipython-input-62-03797cfd7aba>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmodel_results\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrun_rank_multiple_models\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel_list\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mmodel_results\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msort\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\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[0mx_labels\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mgroup\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mgroup\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmodel_results\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mx_values\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mgroup\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mgroup\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmodel_results\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mwidth\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m.75\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+        "\u001b[0;32m<ipython-input-61-c19c6a31408c>\u001b[0m in \u001b[0;36mrun_rank_multiple_models\u001b[0;34m(list_of_models)\u001b[0m\n\u001b[1;32m     29\u001b[0m     return [(model, run_test_model(model, corp_train, corp_answer, test_train, test_answer)) \n\u001b[1;32m     30\u001b[0m             \u001b[0;32mfor\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 31\u001b[0;31m             in list_of_models]\n\u001b[0m\u001b[1;32m     32\u001b[0m \u001b[0mtest_answer\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+        "\u001b[0;32m<ipython-input-61-c19c6a31408c>\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m     28\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mrun_rank_multiple_models\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlist_of_models\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     29\u001b[0m     return [(model, run_test_model(model, corp_train, corp_answer, test_train, test_answer)) \n\u001b[0;32m---> 30\u001b[0;31m             \u001b[0;32mfor\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     31\u001b[0m             in list_of_models]\n\u001b[1;32m     32\u001b[0m \u001b[0mtest_answer\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+        "\u001b[0;32m<ipython-input-61-c19c6a31408c>\u001b[0m in \u001b[0;36mrun_test_model\u001b[0;34m(classifier, x_train, y_train, x_test, y_test)\u001b[0m\n\u001b[1;32m     24\u001b[0m     \u001b[0mclassifier\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     25\u001b[0m     \u001b[0mpredicted\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mclassifier\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx_test\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 26\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mmetrics\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf1_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_test\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpredicted\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     27\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     28\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mrun_rank_multiple_models\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlist_of_models\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+        "\u001b[0;32m/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py\u001b[0m in \u001b[0;36mf1_score\u001b[0;34m(y_true, y_pred, labels, pos_label, average, sample_weight)\u001b[0m\n\u001b[1;32m   1396\u001b[0m     return fbeta_score(y_true, y_pred, 1, labels=labels,\n\u001b[1;32m   1397\u001b[0m                        \u001b[0mpos_label\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpos_label\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maverage\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maverage\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1398\u001b[0;31m                        sample_weight=sample_weight)\n\u001b[0m\u001b[1;32m   1399\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1400\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+        "\u001b[0;32m/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py\u001b[0m in \u001b[0;36mfbeta_score\u001b[0;34m(y_true, y_pred, beta, labels, pos_label, average, sample_weight)\u001b[0m\n\u001b[1;32m   1493\u001b[0m                                                  \u001b[0maverage\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maverage\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1494\u001b[0m                                                  \u001b[0mwarn_for\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'f-score'\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-> 1495\u001b[0;31m                                                  sample_weight=sample_weight)\n\u001b[0m\u001b[1;32m   1496\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1497\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+        "\u001b[0;32m/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py\u001b[0m in \u001b[0;36mprecision_recall_fscore_support\u001b[0;34m(y_true, y_pred, beta, labels, pos_label, average, warn_for, sample_weight)\u001b[0m\n\u001b[1;32m   1667\u001b[0m         \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"beta should be >0 in the F-beta score\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1668\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1669\u001b[0;31m     \u001b[0my_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_pred\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_check_clf_targets\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_pred\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1670\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1671\u001b[0m     \u001b[0mlabel_order\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlabels\u001b[0m  \u001b[0;31m# save this for later\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+        "\u001b[0;32m/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py\u001b[0m in \u001b[0;36m_check_clf_targets\u001b[0;34m(y_true, y_pred)\u001b[0m\n\u001b[1;32m    107\u001b[0m     \u001b[0my_pred\u001b[0m \u001b[0;34m:\u001b[0m \u001b[0marray\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mindicator\u001b[0m \u001b[0mmatrix\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    108\u001b[0m     \"\"\"\n\u001b[0;32m--> 109\u001b[0;31m     \u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_pred\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_arrays\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_pred\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mallow_lists\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    110\u001b[0m     \u001b[0mtype_true\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtype_of_target\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_true\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    111\u001b[0m     \u001b[0mtype_pred\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtype_of_target\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_pred\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+        "\u001b[0;32m/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36mcheck_arrays\u001b[0;34m(*arrays, **options)\u001b[0m\n\u001b[1;32m    252\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0msize\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mn_samples\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    253\u001b[0m             raise ValueError(\"Found array with dim %d. Expected %d\"\n\u001b[0;32m--> 254\u001b[0;31m                              % (size, n_samples))\n\u001b[0m\u001b[1;32m    255\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    256\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mallow_lists\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"shape\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+        "\u001b[0;31mValueError\u001b[0m: Found array with dim 30. Expected 1"
        ]
       }
      ],
-     "prompt_number": 177
+     "prompt_number": 62
     },
     {
      "cell_type": "heading",
      "level": 1,
      "metadata": {},
      "source": [
-      "Pass in live code file for response"
+      "Pass in code file for response"
      ]
     },
     {
@@ -257,18 +436,15 @@
       "\n",
       "def check_code_snippet(a_file, corp_train, corp_answer):\n",
       "    \n",
-      "    # Ingest file\n",
-      "    a_file_df = pd.DataFrame([read_process_file(a_file)], columns=['raw_text'])\n",
-      " \n",
-      "    # Turn file into features\n",
-      "    a_file_df['paren_count'] = parenthesis_count(a_file_df['raw_text'][0])\n",
-      "    a_cleaned_df = a_file_df.drop(['raw_text'], axis=1)\n",
+      "    # Ingest and featurizes file\n",
+      "    request = Corpus([a_file])\n",
+      "    request_df = request.compl_df_build()\n",
       "\n",
       "    # Run model\n",
       "    model_created = GaussianNB()\n",
       "    model_created.fit(corp_train, corp_answer)\n",
-      "    predicted = model_created.predict(a_cleaned_df.values)\n",
-      "    predict_prob = model_created.predict_proba(a_cleaned_df.values)\n",
+      "    predicted = model_created.predict(request_df.values)\n",
+      "    predict_prob = model_created.predict_proba(request_df.values)\n",
       "    \n",
       "    #Pretty response\n",
       "    answer_list = list(zip(model_created.classes_, predict_prob[0]))\n",
@@ -277,8 +453,7 @@
      ],
      "language": "python",
      "metadata": {},
-     "outputs": [],
-     "prompt_number": 348
+     "outputs": []
     },
     {
      "cell_type": "code",
@@ -288,27 +463,7 @@
      ],
      "language": "python",
      "metadata": {},
-     "outputs": [
-      {
-       "metadata": {},
-       "output_type": "pyout",
-       "prompt_number": 350,
-       "text": [
-        "[('java', 0.23709565168200461),\n",
-        " ('perl', 0.15122183416794088),\n",
-        " ('ruby', 0.13694881776324136),\n",
-        " ('ocaml', 0.12725804928624451),\n",
-        " ('python', 0.08496717978985284),\n",
-        " ('haskell', 0.081919233740987057),\n",
-        " ('php', 0.064364558495229707),\n",
-        " ('scala', 0.063449250754175929),\n",
-        " ('javascript', 0.049179273881515481),\n",
-        " ('clojure', 0.0035955804751662455),\n",
-        " ('scheme', 5.6996364138916492e-07)]"
-       ]
-      }
-     ],
-     "prompt_number": 350
+     "outputs": []
     },
     {
      "cell_type": "code",
@@ -316,8 +471,7 @@
      "input": [],
      "language": "python",
      "metadata": {},
-     "outputs": [],
-     "prompt_number": 350
+     "outputs": []
     },
     {
      "cell_type": "code",
@@ -325,8 +479,7 @@
      "input": [],
      "language": "python",
      "metadata": {},
-     "outputs": [],
-     "prompt_number": 329
+     "outputs": []
     },
     {
      "cell_type": "code",
@@ -334,8 +487,7 @@
      "input": [],
      "language": "python",
      "metadata": {},
-     "outputs": [],
-     "prompt_number": 336
+     "outputs": []
     },
     {
      "cell_type": "code",
@@ -343,8 +495,7 @@
      "input": [],
      "language": "python",
      "metadata": {},
-     "outputs": [],
-     "prompt_number": 327
+     "outputs": []
     },
     {
      "cell_type": "code",
diff --git a/test/26 b/test/26
deleted file mode 100644
index 182f919..0000000
--- a/test/26
+++ /dev/null
@@ -1,35 +0,0 @@
-proc isaac::mix {a b c d e f g h} {
-    set a [expr {($a ^ ($b << 11)) & 0xffffffff}]
-    set d [expr {($d + $a) & 0xffffffff}]
-    set b [expr {($b + $c) & 0xffffffff}]
-
-    set b [expr {($b ^ ($c >> 2)) & 0xffffffff}]
-    set e [expr {($e + $b) & 0xffffffff}]
-    set c [expr {($c + $d) & 0xffffffff}]
-
-    set c [expr {($c ^ ($d << 8)) & 0xffffffff}]
-    set f [expr {($f + $c) & 0xffffffff}]
-    set d [expr {($d + $e) & 0xffffffff}]
-
-    set d [expr {($d ^ ($e >> 16)) & 0xffffffff}]
-    set g [expr {($g + $d) & 0xffffffff}]
-    set e [expr {($e + $f) & 0xffffffff}]
-
-    set e [expr {($e ^ ($f << 10)) & 0xffffffff}]
-    set h [expr {($h + $e) & 0xffffffff}]
-    set f [expr {($f + $g) & 0xffffffff}]
-
-    set f [expr {($f ^ ($g >> 4)) & 0xffffffff}]
-    set a [expr {($a + $f) & 0xffffffff}]
-    set g [expr {($g + $h) & 0xffffffff}]
-
-    set g [expr {($g ^ ($h << 8)) & 0xffffffff}]
-    set b [expr {($b + $g) & 0xffffffff}]
-    set h [expr {($h + $a) & 0xffffffff}]
-
-    set h [expr {($h ^ ($a >> 9)) & 0xffffffff}]
-    set c [expr {($c + $h) & 0xffffffff}]
-    set a [expr {($a + $b) & 0xffffffff}]
-
-    return [list $a $b $c $d $e $f $g $h]
-}
diff --git a/test/27 b/test/27
deleted file mode 100644
index 902ec5c..0000000
--- a/test/27
+++ /dev/null
@@ -1,20 +0,0 @@
-proc twitter::follow {nick uhost hand chan argv} {
-	if {![channel get $chan twitter]} { return }
-
-	if {[string length $argv] < 1} {
-		$twitter::output_cmd "PRIVMSG $chan :Usage: !follow <screen name>"
-		return
-	}
-
-	if {[catch {::twitlib::query $::twitlib::follow_url [list screen_name $argv]} result]} {
-		$twitter::output_cmd "PRIVMSG $chan :Twitter failed or already friends with $argv!"
-		return
-	}
-
-	if {[dict exists $result error]} {
-		twitter::output $chan "Follow failed ($argv): [dict get $result error]"
-		return
-	}
-
-	twitter::output $chan "Now following [dict get $result screen_name]!"
-}
\ No newline at end of file
diff --git a/test_fixed.csv b/test_fixed.csv
new file mode 100644
index 0000000..63c3d03
--- /dev/null
+++ b/test_fixed.csv
@@ -0,0 +1 @@
+answers
1
4
4
4
9
9
9
2
2
2
11
1
11
11
3
3
10
10
7
7
1
7
5
5
1
8
8
8
8
4
\ No newline at end of file

From 26432f45763f6b59262f2082f3af5b0c923b675b Mon Sep 17 00:00:00 2001
From: Zack Cooper <zackjcooper@gmail.com>
Date: Fri, 13 Feb 2015 17:31:06 -0500
Subject: [PATCH 3/6] producing roughly 75 percent when running the model
 compared to the given tests. Working away to find better features.

---
 corpus_build.py            |    9 +-
 lang classifier live.ipynb | 5626 ++++++++++++++++++++++++++++++++++--
 test/33                    |   56 +
 test_fixed.csv             |    2 +-
 4 files changed, 5374 insertions(+), 319 deletions(-)
 create mode 100644 test/33

diff --git a/corpus_build.py b/corpus_build.py
index 1b54621..2bf6982 100644
--- a/corpus_build.py
+++ b/corpus_build.py
@@ -57,7 +57,14 @@
                 ('less_minus', "((\<\-))"),
                 ('paren_star', "(\(\*|\*\))"),
                 ('def_exists', r"\bdef\b"),
-                ]
+                ('end_exists', r"\bend\b"),
+                ('curly_bracket', "[\{\}]"),
+                ('slash_star_star', "\/\*\*"),
+                ('forward_slash', "//"),
+                ('var_exists', r"\bvar\b"),
+                ('star_count', r"\b\*\b"),
+                ('dollar_sign', r"\$"),
+                ('val_exists', r"\bval\b")]
 
 
 class Corpus():
diff --git a/lang classifier live.ipynb b/lang classifier live.ipynb
index 5f96e25..9d0abb2 100644
--- a/lang classifier live.ipynb	
+++ b/lang classifier live.ipynb	
@@ -1,23 +1,33 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:0f9223d2ddd3e37046d43bb1578139df3c7fa29d3b2f15da299cf9a0a8978d11"
+  "signature": "sha256:d283fdea1a61866f7cbeaeeaafff75fcae1237f43b5990f43814c78cd7baa485"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
  "worksheets": [
   {
    "cells": [
+    {
+     "cell_type": "heading",
+     "level": 1,
+     "metadata": {},
+     "source": [
+      "Brings in corpus and test data"
+     ]
+    },
     {
      "cell_type": "code",
      "collapsed": false,
      "input": [
       "from corpus_build import Corpus, hit_num, raw_file_list\n",
       "import pandas as pd\n",
+      "import glob\n",
+      "import os\n",
       "\n",
       "corpus = Corpus(raw_file_list)\n",
       "corpus_df = corpus.compl_df_build(False)\n",
-      "corpus_df.head()"
+      "corpus_df"
      ],
      "language": "python",
      "metadata": {},
@@ -36,386 +46,5347 @@
         "      <th>less_minus</th>\n",
         "      <th>paren_star</th>\n",
         "      <th>def_exists</th>\n",
+        "      <th>end_exists</th>\n",
+        "      <th>curly_bracket</th>\n",
+        "      <th>slash_star_star</th>\n",
+        "      <th>forward_slash</th>\n",
+        "      <th>var_exists</th>\n",
+        "      <th>star_count</th>\n",
+        "      <th>dollar_sign</th>\n",
+        "      <th>val_exists</th>\n",
         "    </tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
-        "      <th>0</th>\n",
-        "      <td> 1</td>\n",
+        "      <th>0  </th>\n",
+        "      <td>  1</td>\n",
         "      <td> 0.071901</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.002066</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.001240</td>\n",
         "      <td> 0.000413</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000413</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-        "      <th>1</th>\n",
-        "      <td> 1</td>\n",
+        "      <th>1  </th>\n",
+        "      <td>  1</td>\n",
         "      <td> 0.071704</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.002699</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000771</td>\n",
         "      <td> 0.000386</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000386</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-        "      <th>2</th>\n",
-        "      <td> 1</td>\n",
+        "      <th>2  </th>\n",
+        "      <td>  1</td>\n",
         "      <td> 0.063995</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.002695</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000337</td>\n",
         "      <td> 0.000337</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000337</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-        "      <th>3</th>\n",
-        "      <td> 2</td>\n",
+        "      <th>3  </th>\n",
+        "      <td>  2</td>\n",
         "      <td> 0.024707</td>\n",
         "      <td> 0.002471</td>\n",
         "      <td> 0.002471</td>\n",
         "      <td> 0.000618</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000618</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001235</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-        "      <th>4</th>\n",
-        "      <td> 2</td>\n",
+        "      <th>4  </th>\n",
+        "      <td>  2</td>\n",
         "      <td> 0.024352</td>\n",
         "      <td> 0.002118</td>\n",
         "      <td> 0.002647</td>\n",
         "      <td> 0.000529</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001059</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000529</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001059</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
-        "  </tbody>\n",
-        "</table>\n",
-        "</div>"
-       ],
-       "metadata": {},
-       "output_type": "pyout",
-       "prompt_number": 47,
-       "text": [
-        "  hit_num  parent_count  double_colon  let_exists  less_minus  paren_star  \\\n",
-        "0       1      0.071901      0.000000    0.002066    0.000000    0.001240   \n",
-        "1       1      0.071704      0.000000    0.002699    0.000000    0.000771   \n",
-        "2       1      0.063995      0.000000    0.002695    0.000000    0.000337   \n",
-        "3       2      0.024707      0.002471    0.002471    0.000618    0.000000   \n",
-        "4       2      0.024352      0.002118    0.002647    0.000529    0.000000   \n",
-        "\n",
-        "   def_exists  \n",
-        "0    0.000413  \n",
-        "1    0.000386  \n",
-        "2    0.000337  \n",
-        "3    0.000000  \n",
-        "4    0.000000  "
-       ]
-      }
-     ],
-     "prompt_number": 47
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "import glob\n",
-      "import os\n",
-      "test_file_list = [filename for filename in\n",
-      "                 glob.iglob(os.path.join('test/', '*'))]\n",
-      "test_info = Corpus(test_file_list)\n",
-      "test_info_df = test_info.compl_df_build(True)\n",
-      "test_info_df['answers'] = pd.read_csv('test_fixed.csv', dtype='object')\n",
-      "test_info_df.head()"
-     ],
-     "language": "python",
-     "metadata": {},
-     "outputs": [
-      {
-       "html": [
-        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
-        "<table border=\"1\" class=\"dataframe\">\n",
-        "  <thead>\n",
-        "    <tr style=\"text-align: right;\">\n",
-        "      <th></th>\n",
-        "      <th>parent_count</th>\n",
-        "      <th>double_colon</th>\n",
-        "      <th>let_exists</th>\n",
-        "      <th>less_minus</th>\n",
-        "      <th>paren_star</th>\n",
-        "      <th>def_exists</th>\n",
-        "      <th>answers</th>\n",
+        "    <tr>\n",
+        "      <th>5  </th>\n",
+        "      <td>  2</td>\n",
+        "      <td> 0.026361</td>\n",
+        "      <td> 0.002292</td>\n",
+        "      <td> 0.002865</td>\n",
+        "      <td> 0.000573</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001146</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000573</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001146</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
-        "  </thead>\n",
-        "  <tbody>\n",
         "    <tr>\n",
-        "      <th>0</th>\n",
-        "      <td> 0.045734</td>\n",
+        "      <th>6  </th>\n",
+        "      <td>  3</td>\n",
+        "      <td> 0.028487</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000982</td>\n",
+        "      <td> 0.015226</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000246</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.001759</td>\n",
-        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 1</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-        "      <th>1</th>\n",
-        "      <td> 0.063037</td>\n",
+        "      <th>7  </th>\n",
+        "      <td>  3</td>\n",
+        "      <td> 0.032197</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 4</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.010417</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000947</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001420</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-        "      <th>2</th>\n",
-        "      <td> 0.042795</td>\n",
+        "      <th>8  </th>\n",
+        "      <td>  3</td>\n",
+        "      <td> 0.029671</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.012981</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000464</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.000058</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.000058</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-        "      <th>3</th>\n",
-        "      <td> 0.047059</td>\n",
+        "      <th>9  </th>\n",
+        "      <td>  4</td>\n",
+        "      <td> 0.038012</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.010234</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000731</td>\n",
+        "      <td> 0.006579</td>\n",
+        "      <td> 0.002193</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-        "      <th>4</th>\n",
-        "      <td> 0.015708</td>\n",
-        "      <td> 0.000561</td>\n",
+        "      <th>10 </th>\n",
+        "      <td>  9</td>\n",
+        "      <td> 0.025682</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004815</td>\n",
+        "      <td> 0.001605</td>\n",
+        "      <td> 0.003210</td>\n",
+        "      <td> 0.011236</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000803</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.000281</td>\n",
-        "      <td> 0.002805</td>\n",
-        "      <td> 9</td>\n",
         "    </tr>\n",
-        "  </tbody>\n",
-        "</table>\n",
-        "</div>"
-       ],
-       "metadata": {},
-       "output_type": "pyout",
-       "prompt_number": 105,
-       "text": [
-        "   parent_count  double_colon  let_exists  less_minus  paren_star  def_exists  \\\n",
-        "0      0.045734      0.000000    0.001759           0    0.000000    0.000000   \n",
-        "1      0.063037      0.000000    0.000000           0    0.000000    0.000000   \n",
-        "2      0.042795      0.000000    0.000058           0    0.000058    0.000000   \n",
-        "3      0.047059      0.000000    0.000000           0    0.000000    0.000000   \n",
-        "4      0.015708      0.000561    0.000000           0    0.000281    0.002805   \n",
-        "\n",
-        "  answers  \n",
-        "0       1  \n",
-        "1       4  \n",
-        "2       4  \n",
-        "3       4  \n",
-        "4       9  "
-       ]
-      }
-     ],
-     "prompt_number": 105
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [],
-     "language": "python",
-     "metadata": {},
-     "outputs": [],
-     "prompt_number": 101
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [],
-     "language": "python",
-     "metadata": {},
-     "outputs": [],
-     "prompt_number": 38
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [],
-     "language": "python",
-     "metadata": {},
-     "outputs": [],
-     "prompt_number": 38
-    },
-    {
-     "cell_type": "heading",
-     "level": 1,
-     "metadata": {},
-     "source": [
-      "Choosing the Best Model"
-     ]
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "from sklearn.naive_bayes import GaussianNB, MultinomialNB, BernoulliNB\n",
-      "from sklearn.neighbors import KNeighborsClassifier\n",
-      "from sklearn.tree import DecisionTreeClassifier\n",
-      "from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier\n",
-      "from sklearn.cross_validation import train_test_split\n",
-      "from sklearn.cluster import KMeans\n",
-      "from sklearn import metrics\n",
-      "from sklearn.cross_validation import cross_val_score\n",
-      "import numpy as np\n",
-      "import seaborn as sbn\n",
-      "import matplotlib.pyplot as plt\n",
-      "%matplotlib inline\n",
-      "\n",
-      "corp_train = corpus_df.values[0::,1::]\n",
-      "corp_answer = corpus_df.values[0::,0]\n",
-      "test_train = test_info_df.values[0::,:-1:]\n",
-      "test_answer = test_info_df.values[0::1,-1]\n",
-      "\n",
-      "model_list = [KNeighborsClassifier(), RandomForestClassifier(), DecisionTreeClassifier()]\n",
-      "# BernoulliNB(), MultinomialNB(), AdaBoostClassifier(), GaussianNB(), \n",
-      "\n",
-      "def run_test_model(classifier, x_train, y_train, x_test, y_test):\n",
-      "\n",
-      "    classifier.fit(x_train, y_train)\n",
-      "    predicted = classifier.predict(x_test)\n",
-      "    return metrics.f1_score(y_test, predicted)\n",
-      "\n",
-      "def run_rank_multiple_models(list_of_models):\n",
-      "    return [(model, run_test_model(model, corp_train, corp_answer, test_train, test_answer)) \n",
-      "            for model \n",
-      "            in list_of_models]"
-     ],
-     "language": "python",
-     "metadata": {},
-     "outputs": [
-      {
-       "metadata": {},
-       "output_type": "pyout",
-       "prompt_number": 106,
-       "text": [
-        "array([[0.04573438874230431, 0.0, 0.001759014951627089, 0.0, 0.0, 0.0],\n",
-        "       [0.06303724928366762, 0.0, 0.0, 0.0, 0.0, 0.0],\n",
-        "       [0.0427946089160235, 0.0, 5.7597051030987213e-05, 0.0,\n",
-        "        5.7597051030987213e-05, 0.0],\n",
-        "       [0.047058823529411764, 0.0, 0.0, 0.0, 0.0, 0.0],\n",
-        "       [0.01570827489481066, 0.0005610098176718093, 0.0, 0.0,\n",
-        "        0.00028050490883590464, 0.002805049088359046],\n",
-        "       [0.0, 0.0, 0.0, 0.0, 0.0, 0.002036659877800407],\n",
-        "       [0.00816326530612245, 0.0, 0.0, 0.0, 0.0, 0.00816326530612245],\n",
-        "       [0.013328977458346946, 0.000914733747141457, 6.533812479581836e-05,\n",
-        "        0.0004573668735707285, 0.0, 0.00013067624959163673],\n",
-        "       [0.05806451612903226, 0.0064516129032258064, 0.0,\n",
-        "        0.0064516129032258064, 0.0, 0.0],\n",
-        "       [0.0137524557956778, 0.003929273084479371, 0.0004911591355599214,\n",
-        "        0.0029469548133595285, 0.0, 0.0],\n",
-        "       [0.12435233160621761, 0.0, 0.0, 0.0, 0.0, 0.0],\n",
-        "       [0.08866995073891626, 0.0, 0.0, 0.0, 0.0, 0.0],\n",
-        "       [0.2222222222222222, 0.0, 0.0, 0.0, 0.0, 0.0],\n",
-        "       [0.11084624553039332, 0.0, 0.0008939213349225268, 0.0, 0.0, 0.0],\n",
-        "       [0.006644518272425249, 0.0, 0.0, 0.0, 0.0, 0.0],\n",
-        "       [0.0065717415115005475, 0.0, 0.0, 0.0, 0.0, 0.0],\n",
-        "       [0.027181688125894134, 0.001072961373390558, 0.0, 0.0,\n",
-        "        0.000715307582260372, 0.00178826895565093],\n",
-        "       [0.014606155451225874, 0.0, 0.0, 0.0, 0.0, 0.004173187271778821],\n",
-        "       [0.019253910950661854, 0.00030084235860409147, 0.0, 0.0, 0.0, 0.0],\n",
-        "       [0.058997050147492625, 0.0, 0.0, 0.0, 0.0029498525073746312, 0.0],\n",
-        "       [0.0979020979020979, 0.0, 0.0, 0.0, 0.0, 0.0],\n",
-        "       [0.05322415557830092, 0.0015353121801432957, 0.0, 0.0, 0.0, 0.0],\n",
-        "       [0.026448029621793177, 0.0001322401481089659, 0.004892885480031738,\n",
-        "        0.0, 0.005554086220576567, 0.0],\n",
-        "       [0.017391304347826087, 0.0, 0.0052173913043478265, 0.0, 0.0, 0.0],\n",
-        "       [0.02680067001675042, 0.0, 0.0016750418760469012, 0.0, 0.0,\n",
-        "        0.0016750418760469012],\n",
-        "       [0.03986710963455149, 0.0, 0.0, 0.0, 0.0, 0.0],\n",
-        "       [0.028050490883590462, 0.0, 0.0, 0.0, 0.0, 0.001402524544179523],\n",
-        "       [0.03680981595092025, 0.0, 0.0, 0.0, 0.0, 0.012269938650306749],\n",
-        "       [0.029607698001480384, 0.0, 0.0, 0.0, 0.0, 0.0030594621268196396],\n",
-        "       [0.05389221556886228, 0.0, 0.0, 0.0, 0.0, 0.0]], dtype=object)"
-       ]
-      }
-     ],
-     "prompt_number": 106
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "run_test_model(DecisionTreeClassifier(), corp_train, corp_answer, test_train, test_answer)"
-     ],
-     "language": "python",
-     "metadata": {},
-     "outputs": [
-      {
-       "output_type": "stream",
-       "stream": "stderr",
-       "text": [
-        "/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py:1773: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true samples.\n",
-        "  'recall', 'true', average, warn_for)\n"
-       ]
-      },
-      {
-       "metadata": {},
-       "output_type": "pyout",
-       "prompt_number": 107,
-       "text": [
-        "0.4173737373737374"
-       ]
-      }
-     ],
-     "prompt_number": 107
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "model_results = run_rank_multiple_models(model_list)\n",
-      "model_results.sort(key=lambda x: x[1])\n",
-      "x_labels = [group[0] for group in model_results]\n",
-      "x_values = [group[1] for group in model_results]  \n",
-      "width = .75\n",
-      "height = np.arange(len(model_results))\n",
-      "mean = np.array(x_values).mean()\n",
-      "\n",
-      "plt.yticks(height+width/2., x_labels)\n",
-      "plt.barh(height, x_values, width, color = sbn.color_palette())\n",
-      "plt.axvline(mean, c='r')\n",
-      "plt.rc('figure', figsize=(10, 5))\n",
-      "plt.show()"
-     ],
-     "language": "python",
-     "metadata": {},
-     "outputs": [
-      {
-       "ename": "ValueError",
-       "evalue": "Found array with dim 30. Expected 1",
-       "output_type": "pyerr",
-       "traceback": [
-        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
-        "\u001b[0;32m<ipython-input-62-03797cfd7aba>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmodel_results\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrun_rank_multiple_models\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel_list\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mmodel_results\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msort\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\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[0mx_labels\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mgroup\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mgroup\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmodel_results\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mx_values\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mgroup\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mgroup\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmodel_results\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mwidth\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m.75\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-        "\u001b[0;32m<ipython-input-61-c19c6a31408c>\u001b[0m in \u001b[0;36mrun_rank_multiple_models\u001b[0;34m(list_of_models)\u001b[0m\n\u001b[1;32m     29\u001b[0m     return [(model, run_test_model(model, corp_train, corp_answer, test_train, test_answer)) \n\u001b[1;32m     30\u001b[0m             \u001b[0;32mfor\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 31\u001b[0;31m             in list_of_models]\n\u001b[0m\u001b[1;32m     32\u001b[0m \u001b[0mtest_answer\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-        "\u001b[0;32m<ipython-input-61-c19c6a31408c>\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m     28\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mrun_rank_multiple_models\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlist_of_models\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     29\u001b[0m     return [(model, run_test_model(model, corp_train, corp_answer, test_train, test_answer)) \n\u001b[0;32m---> 30\u001b[0;31m             \u001b[0;32mfor\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     31\u001b[0m             in list_of_models]\n\u001b[1;32m     32\u001b[0m \u001b[0mtest_answer\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-        "\u001b[0;32m<ipython-input-61-c19c6a31408c>\u001b[0m in \u001b[0;36mrun_test_model\u001b[0;34m(classifier, x_train, y_train, x_test, y_test)\u001b[0m\n\u001b[1;32m     24\u001b[0m     \u001b[0mclassifier\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     25\u001b[0m     \u001b[0mpredicted\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mclassifier\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx_test\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 26\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mmetrics\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf1_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_test\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpredicted\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     27\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     28\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mrun_rank_multiple_models\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlist_of_models\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-        "\u001b[0;32m/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py\u001b[0m in \u001b[0;36mf1_score\u001b[0;34m(y_true, y_pred, labels, pos_label, average, sample_weight)\u001b[0m\n\u001b[1;32m   1396\u001b[0m     return fbeta_score(y_true, y_pred, 1, labels=labels,\n\u001b[1;32m   1397\u001b[0m                        \u001b[0mpos_label\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpos_label\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maverage\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maverage\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1398\u001b[0;31m                        sample_weight=sample_weight)\n\u001b[0m\u001b[1;32m   1399\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1400\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-        "\u001b[0;32m/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py\u001b[0m in \u001b[0;36mfbeta_score\u001b[0;34m(y_true, y_pred, beta, labels, pos_label, average, sample_weight)\u001b[0m\n\u001b[1;32m   1493\u001b[0m                                                  \u001b[0maverage\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maverage\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1494\u001b[0m                                                  \u001b[0mwarn_for\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'f-score'\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-> 1495\u001b[0;31m                                                  sample_weight=sample_weight)\n\u001b[0m\u001b[1;32m   1496\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1497\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-        "\u001b[0;32m/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py\u001b[0m in \u001b[0;36mprecision_recall_fscore_support\u001b[0;34m(y_true, y_pred, beta, labels, pos_label, average, warn_for, sample_weight)\u001b[0m\n\u001b[1;32m   1667\u001b[0m         \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"beta should be >0 in the F-beta score\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1668\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1669\u001b[0;31m     \u001b[0my_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_pred\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_check_clf_targets\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_pred\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1670\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1671\u001b[0m     \u001b[0mlabel_order\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlabels\u001b[0m  \u001b[0;31m# save this for later\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-        "\u001b[0;32m/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py\u001b[0m in \u001b[0;36m_check_clf_targets\u001b[0;34m(y_true, y_pred)\u001b[0m\n\u001b[1;32m    107\u001b[0m     \u001b[0my_pred\u001b[0m \u001b[0;34m:\u001b[0m \u001b[0marray\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mindicator\u001b[0m \u001b[0mmatrix\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    108\u001b[0m     \"\"\"\n\u001b[0;32m--> 109\u001b[0;31m     \u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_pred\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_arrays\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_pred\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mallow_lists\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    110\u001b[0m     \u001b[0mtype_true\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtype_of_target\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_true\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    111\u001b[0m     \u001b[0mtype_pred\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtype_of_target\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_pred\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-        "\u001b[0;32m/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36mcheck_arrays\u001b[0;34m(*arrays, **options)\u001b[0m\n\u001b[1;32m    252\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0msize\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mn_samples\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    253\u001b[0m             raise ValueError(\"Found array with dim %d. Expected %d\"\n\u001b[0;32m--> 254\u001b[0;31m                              % (size, n_samples))\n\u001b[0m\u001b[1;32m    255\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    256\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mallow_lists\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"shape\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-        "\u001b[0;31mValueError\u001b[0m: Found array with dim 30. Expected 1"
-       ]
-      }
-     ],
-     "prompt_number": 62
-    },
+        "    <tr>\n",
+        "      <th>11 </th>\n",
+        "      <td>  9</td>\n",
+        "      <td> 0.022440</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004208</td>\n",
+        "      <td> 0.001403</td>\n",
+        "      <td> 0.003506</td>\n",
+        "      <td> 0.009818</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000701</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>12 </th>\n",
+        "      <td>  9</td>\n",
+        "      <td> 0.026920</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004751</td>\n",
+        "      <td> 0.001584</td>\n",
+        "      <td> 0.004751</td>\n",
+        "      <td> 0.011085</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000792</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>13 </th>\n",
+        "      <td>  9</td>\n",
+        "      <td> 0.023955</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002178</td>\n",
+        "      <td> 0.002395</td>\n",
+        "      <td> 0.006533</td>\n",
+        "      <td> 0.006969</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000218</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>14 </th>\n",
+        "      <td>  5</td>\n",
+        "      <td> 0.025814</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.012293</td>\n",
+        "      <td> 0.002459</td>\n",
+        "      <td> 0.001229</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000615</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001229</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>15 </th>\n",
+        "      <td>  5</td>\n",
+        "      <td> 0.034651</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.009773</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.003554</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000888</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000444</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>16 </th>\n",
+        "      <td>  5</td>\n",
+        "      <td> 0.033503</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.010925</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004370</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001457</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000728</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>17 </th>\n",
+        "      <td>  6</td>\n",
+        "      <td> 0.025354</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.007457</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000746</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.042506</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>18 </th>\n",
+        "      <td>  6</td>\n",
+        "      <td> 0.026679</td>\n",
+        "      <td> 0.000953</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.013340</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000476</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.037637</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>19 </th>\n",
+        "      <td>  7</td>\n",
+        "      <td> 0.036755</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.006337</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001267</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.046261</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>20 </th>\n",
+        "      <td>  7</td>\n",
+        "      <td> 0.034674</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.008322</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000693</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.041609</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>21 </th>\n",
+        "      <td>  7</td>\n",
+        "      <td> 0.040650</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.005420</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000678</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.044038</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>22 </th>\n",
+        "      <td>  7</td>\n",
+        "      <td> 0.038144</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.013402</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002835</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.057474</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>23 </th>\n",
+        "      <td>  8</td>\n",
+        "      <td> 0.044543</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002784</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.007795</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000557</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>24 </th>\n",
+        "      <td> 11</td>\n",
+        "      <td> 0.104895</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002914</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001166</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000583</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004662</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>25 </th>\n",
+        "      <td> 11</td>\n",
+        "      <td> 0.095606</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.003380</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000483</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000483</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001449</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>26 </th>\n",
+        "      <td> 11</td>\n",
+        "      <td> 0.096643</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001107</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000738</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000369</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000738</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>27 </th>\n",
+        "      <td> 10</td>\n",
+        "      <td> 0.036036</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004505</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.015444</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000644</td>\n",
+        "      <td> 0.000644</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.003218</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>28 </th>\n",
+        "      <td> 10</td>\n",
+        "      <td> 0.048632</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.003647</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.013374</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001216</td>\n",
+        "      <td> 0.001216</td>\n",
+        "      <td> 0.002432</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004863</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>29 </th>\n",
+        "      <td> 10</td>\n",
+        "      <td> 0.035115</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.003053</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.015267</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000763</td>\n",
+        "      <td> 0.001527</td>\n",
+        "      <td> 0.002290</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004580</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>...</th>\n",
+        "      <td>...</td>\n",
+        "      <td>...</td>\n",
+        "      <td>...</td>\n",
+        "      <td>...</td>\n",
+        "      <td>...</td>\n",
+        "      <td>...</td>\n",
+        "      <td>...</td>\n",
+        "      <td>...</td>\n",
+        "      <td>...</td>\n",
+        "      <td>...</td>\n",
+        "      <td>...</td>\n",
+        "      <td>...</td>\n",
+        "      <td>...</td>\n",
+        "      <td>...</td>\n",
+        "      <td>...</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>357</th>\n",
+        "      <td>  8</td>\n",
+        "      <td> 0.052632</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004848</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000693</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>358</th>\n",
+        "      <td>  8</td>\n",
+        "      <td> 0.044304</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.003956</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000791</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>359</th>\n",
+        "      <td>  8</td>\n",
+        "      <td> 0.036014</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.003001</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000600</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>360</th>\n",
+        "      <td> 11</td>\n",
+        "      <td> 0.090119</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002172</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000543</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>361</th>\n",
+        "      <td> 11</td>\n",
+        "      <td> 0.085551</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001901</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000475</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>362</th>\n",
+        "      <td> 11</td>\n",
+        "      <td> 0.108160</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.003863</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000483</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>363</th>\n",
+        "      <td> 10</td>\n",
+        "      <td> 0.063545</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000836</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002508</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.015050</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.003344</td>\n",
+        "      <td> 0.004181</td>\n",
+        "      <td> 0.000836</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.003344</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>364</th>\n",
+        "      <td> 10</td>\n",
+        "      <td> 0.041924</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001644</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002877</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.013152</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000411</td>\n",
+        "      <td> 0.003288</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004110</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>365</th>\n",
+        "      <td> 10</td>\n",
+        "      <td> 0.042079</td>\n",
+        "      <td> 0.000495</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000248</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002475</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.008911</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004950</td>\n",
+        "      <td> 0.002475</td>\n",
+        "      <td> 0.001238</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.003465</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>366</th>\n",
+        "      <td> 10</td>\n",
+        "      <td> 0.042163</td>\n",
+        "      <td> 0.000687</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000458</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002521</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.009166</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004812</td>\n",
+        "      <td> 0.002521</td>\n",
+        "      <td> 0.001146</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.003208</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>367</th>\n",
+        "      <td>  1</td>\n",
+        "      <td> 0.053812</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001794</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000897</td>\n",
+        "      <td> 0.001794</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000897</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>368</th>\n",
+        "      <td>  1</td>\n",
+        "      <td> 0.050473</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004206</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001052</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>369</th>\n",
+        "      <td>  2</td>\n",
+        "      <td> 0.016092</td>\n",
+        "      <td> 0.001149</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.005747</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001149</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001149</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>370</th>\n",
+        "      <td>  3</td>\n",
+        "      <td> 0.028712</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.014356</td>\n",
+        "      <td> 0.000449</td>\n",
+        "      <td> 0.002692</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>371</th>\n",
+        "      <td>  3</td>\n",
+        "      <td> 0.028812</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.013205</td>\n",
+        "      <td> 0.000600</td>\n",
+        "      <td> 0.004802</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>372</th>\n",
+        "      <td>  3</td>\n",
+        "      <td> 0.020844</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.012710</td>\n",
+        "      <td> 0.000254</td>\n",
+        "      <td> 0.000763</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>373</th>\n",
+        "      <td>  3</td>\n",
+        "      <td> 0.022556</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.015038</td>\n",
+        "      <td> 0.000752</td>\n",
+        "      <td> 0.000752</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>374</th>\n",
+        "      <td>  3</td>\n",
+        "      <td> 0.022871</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.013407</td>\n",
+        "      <td> 0.000394</td>\n",
+        "      <td> 0.001183</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>375</th>\n",
+        "      <td>  3</td>\n",
+        "      <td> 0.028786</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.010013</td>\n",
+        "      <td> 0.000626</td>\n",
+        "      <td> 0.002503</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>376</th>\n",
+        "      <td>  9</td>\n",
+        "      <td> 0.023939</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004353</td>\n",
+        "      <td> 0.010881</td>\n",
+        "      <td> 0.002176</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001088</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>377</th>\n",
+        "      <td>  9</td>\n",
+        "      <td> 0.003378</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.010135</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001689</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>378</th>\n",
+        "      <td>  5</td>\n",
+        "      <td> 0.063861</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.011611</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002903</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001451</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>379</th>\n",
+        "      <td>  5</td>\n",
+        "      <td> 0.056604</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.010613</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004717</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004717</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001179</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>380</th>\n",
+        "      <td>  5</td>\n",
+        "      <td> 0.054570</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.010914</td>\n",
+        "      <td> 0.001364</td>\n",
+        "      <td> 0.002729</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001364</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>381</th>\n",
+        "      <td>  6</td>\n",
+        "      <td> 0.034043</td>\n",
+        "      <td> 0.004255</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.017021</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001064</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.032979</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>382</th>\n",
+        "      <td>  6</td>\n",
+        "      <td> 0.012600</td>\n",
+        "      <td> 0.001260</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.011760</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000420</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.015960</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>383</th>\n",
+        "      <td>  8</td>\n",
+        "      <td> 0.035528</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001045</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001045</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001045</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>384</th>\n",
+        "      <td>  8</td>\n",
+        "      <td> 0.029233</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002436</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001218</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>385</th>\n",
+        "      <td> 11</td>\n",
+        "      <td> 0.080834</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.003911</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001304</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>386</th>\n",
+        "      <td> 10</td>\n",
+        "      <td> 0.033946</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002829</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.019802</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004243</td>\n",
+        "      <td> 0.001414</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004243</td>\n",
+        "    </tr>\n",
+        "  </tbody>\n",
+        "</table>\n",
+        "<p>387 rows \u00d7 15 columns</p>\n",
+        "</div>"
+       ],
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 1,
+       "text": [
+        "    hit_num  parent_count  double_colon  let_exists  less_minus  paren_star  \\\n",
+        "0         1      0.071901      0.000000    0.002066    0.000000    0.001240   \n",
+        "1         1      0.071704      0.000000    0.002699    0.000000    0.000771   \n",
+        "2         1      0.063995      0.000000    0.002695    0.000000    0.000337   \n",
+        "3         2      0.024707      0.002471    0.002471    0.000618    0.000000   \n",
+        "4         2      0.024352      0.002118    0.002647    0.000529    0.000000   \n",
+        "5         2      0.026361      0.002292    0.002865    0.000573    0.000000   \n",
+        "6         3      0.028487      0.000000    0.000000    0.000000    0.000000   \n",
+        "7         3      0.032197      0.000000    0.000000    0.000000    0.000000   \n",
+        "8         3      0.029671      0.000000    0.000000    0.000000    0.000000   \n",
+        "9         4      0.038012      0.000000    0.000000    0.000000    0.000000   \n",
+        "10        9      0.025682      0.000000    0.000000    0.000000    0.004815   \n",
+        "11        9      0.022440      0.000000    0.000000    0.000000    0.004208   \n",
+        "12        9      0.026920      0.000000    0.000000    0.000000    0.004751   \n",
+        "13        9      0.023955      0.000000    0.000000    0.000000    0.002178   \n",
+        "14        5      0.025814      0.000000    0.012293    0.002459    0.001229   \n",
+        "15        5      0.034651      0.000000    0.009773    0.000000    0.003554   \n",
+        "16        5      0.033503      0.000000    0.010925    0.000000    0.004370   \n",
+        "17        6      0.025354      0.000000    0.000000    0.000000    0.000000   \n",
+        "18        6      0.026679      0.000953    0.000000    0.000000    0.000000   \n",
+        "19        7      0.036755      0.000000    0.000000    0.000000    0.000000   \n",
+        "20        7      0.034674      0.000000    0.000000    0.000000    0.000000   \n",
+        "21        7      0.040650      0.000000    0.000000    0.000000    0.000000   \n",
+        "22        7      0.038144      0.000000    0.000000    0.000000    0.000000   \n",
+        "23        8      0.044543      0.000000    0.000000    0.000000    0.000000   \n",
+        "24       11      0.104895      0.000000    0.002914    0.000000    0.001166   \n",
+        "25       11      0.095606      0.000000    0.003380    0.000000    0.000483   \n",
+        "26       11      0.096643      0.000000    0.001107    0.000000    0.000738   \n",
+        "27       10      0.036036      0.000000    0.000000    0.000000    0.000000   \n",
+        "28       10      0.048632      0.000000    0.000000    0.000000    0.000000   \n",
+        "29       10      0.035115      0.000000    0.000000    0.000000    0.000000   \n",
+        "..      ...           ...           ...         ...         ...         ...   \n",
+        "357       8      0.052632      0.000000    0.000000    0.000000    0.000000   \n",
+        "358       8      0.044304      0.000000    0.000000    0.000000    0.000000   \n",
+        "359       8      0.036014      0.000000    0.000000    0.000000    0.000000   \n",
+        "360      11      0.090119      0.000000    0.002172    0.000000    0.000000   \n",
+        "361      11      0.085551      0.000000    0.001901    0.000000    0.000000   \n",
+        "362      11      0.108160      0.000000    0.003863    0.000000    0.000000   \n",
+        "363      10      0.063545      0.000000    0.000000    0.000836    0.000000   \n",
+        "364      10      0.041924      0.000000    0.000000    0.001644    0.000000   \n",
+        "365      10      0.042079      0.000495    0.000000    0.000248    0.000000   \n",
+        "366      10      0.042163      0.000687    0.000000    0.000458    0.000000   \n",
+        "367       1      0.053812      0.000000    0.001794    0.000000    0.000000   \n",
+        "368       1      0.050473      0.000000    0.000000    0.000000    0.000000   \n",
+        "369       2      0.016092      0.001149    0.000000    0.005747    0.000000   \n",
+        "370       3      0.028712      0.000000    0.000000    0.000000    0.000000   \n",
+        "371       3      0.028812      0.000000    0.000000    0.000000    0.000000   \n",
+        "372       3      0.020844      0.000000    0.000000    0.000000    0.000000   \n",
+        "373       3      0.022556      0.000000    0.000000    0.000000    0.000000   \n",
+        "374       3      0.022871      0.000000    0.000000    0.000000    0.000000   \n",
+        "375       3      0.028786      0.000000    0.000000    0.000000    0.000000   \n",
+        "376       9      0.023939      0.000000    0.000000    0.000000    0.000000   \n",
+        "377       9      0.003378      0.000000    0.000000    0.000000    0.000000   \n",
+        "378       5      0.063861      0.000000    0.011611    0.000000    0.002903   \n",
+        "379       5      0.056604      0.000000    0.010613    0.000000    0.004717   \n",
+        "380       5      0.054570      0.000000    0.010914    0.001364    0.002729   \n",
+        "381       6      0.034043      0.004255    0.000000    0.000000    0.000000   \n",
+        "382       6      0.012600      0.001260    0.000000    0.000000    0.000000   \n",
+        "383       8      0.035528      0.000000    0.000000    0.000000    0.000000   \n",
+        "384       8      0.029233      0.000000    0.000000    0.000000    0.000000   \n",
+        "385      11      0.080834      0.000000    0.003911    0.000000    0.000000   \n",
+        "386      10      0.033946      0.000000    0.000000    0.000000    0.000000   \n",
+        "\n",
+        "     def_exists  end_exists  curly_bracket  slash_star_star  forward_slash  \\\n",
+        "0      0.000413    0.000000       0.000000         0.000000       0.000413   \n",
+        "1      0.000386    0.000000       0.000000         0.000000       0.000386   \n",
+        "2      0.000337    0.000000       0.000000         0.000000       0.000337   \n",
+        "3      0.000000    0.000000       0.000000         0.000000       0.000618   \n",
+        "4      0.000000    0.000000       0.001059         0.000000       0.000529   \n",
+        "5      0.000000    0.000000       0.001146         0.000000       0.000573   \n",
+        "6      0.000000    0.000982       0.015226         0.000000       0.000246   \n",
+        "7      0.000000    0.000000       0.010417         0.000000       0.000947   \n",
+        "8      0.000000    0.000000       0.012981         0.000000       0.000464   \n",
+        "9      0.000000    0.000000       0.010234         0.000000       0.000731   \n",
+        "10     0.001605    0.003210       0.011236         0.000000       0.000803   \n",
+        "11     0.001403    0.003506       0.009818         0.000000       0.000701   \n",
+        "12     0.001584    0.004751       0.011085         0.000000       0.000792   \n",
+        "13     0.002395    0.006533       0.006969         0.000000       0.000218   \n",
+        "14     0.000000    0.000000       0.000000         0.000000       0.000615   \n",
+        "15     0.000000    0.000000       0.000888         0.000000       0.000444   \n",
+        "16     0.000000    0.000000       0.001457         0.000000       0.000728   \n",
+        "17     0.000000    0.000000       0.007457         0.000000       0.000746   \n",
+        "18     0.000000    0.000000       0.013340         0.000000       0.000476   \n",
+        "19     0.000000    0.000000       0.006337         0.000000       0.001267   \n",
+        "20     0.000000    0.000000       0.008322         0.000000       0.000693   \n",
+        "21     0.000000    0.000000       0.005420         0.000000       0.000678   \n",
+        "22     0.000000    0.000000       0.013402         0.000000       0.002835   \n",
+        "23     0.002784    0.000000       0.007795         0.000000       0.000557   \n",
+        "24     0.000000    0.000000       0.000000         0.000000       0.000583   \n",
+        "25     0.000000    0.000000       0.000000         0.000000       0.000483   \n",
+        "26     0.000000    0.000000       0.000000         0.000000       0.000369   \n",
+        "27     0.004505    0.000000       0.015444         0.000000       0.000644   \n",
+        "28     0.003647    0.000000       0.013374         0.000000       0.001216   \n",
+        "29     0.003053    0.000000       0.015267         0.000000       0.000763   \n",
+        "..          ...         ...            ...              ...            ...   \n",
+        "357    0.004848    0.000000       0.000000         0.000000       0.000693   \n",
+        "358    0.003956    0.000000       0.000000         0.000000       0.000791   \n",
+        "359    0.003001    0.000000       0.000000         0.000000       0.000600   \n",
+        "360    0.000000    0.000000       0.000000         0.000000       0.000543   \n",
+        "361    0.000000    0.000000       0.000000         0.000000       0.000475   \n",
+        "362    0.000000    0.000000       0.000000         0.000000       0.000483   \n",
+        "363    0.002508    0.000000       0.015050         0.000000       0.003344   \n",
+        "364    0.002877    0.000000       0.013152         0.000000       0.000411   \n",
+        "365    0.002475    0.000000       0.008911         0.000000       0.004950   \n",
+        "366    0.002521    0.000000       0.009166         0.000000       0.004812   \n",
+        "367    0.000000    0.000897       0.001794         0.000000       0.000897   \n",
+        "368    0.000000    0.000000       0.004206         0.000000       0.001052   \n",
+        "369    0.000000    0.000000       0.000000         0.000000       0.001149   \n",
+        "370    0.000000    0.000000       0.014356         0.000449       0.002692   \n",
+        "371    0.000000    0.000000       0.013205         0.000600       0.004802   \n",
+        "372    0.000000    0.000000       0.012710         0.000254       0.000763   \n",
+        "373    0.000000    0.000000       0.015038         0.000752       0.000752   \n",
+        "374    0.000000    0.000000       0.013407         0.000394       0.001183   \n",
+        "375    0.000000    0.000000       0.010013         0.000626       0.002503   \n",
+        "376    0.004353    0.010881       0.002176         0.000000       0.001088   \n",
+        "377    0.000000    0.010135       0.000000         0.000000       0.001689   \n",
+        "378    0.000000    0.000000       0.000000         0.000000       0.001451   \n",
+        "379    0.000000    0.000000       0.004717         0.000000       0.001179   \n",
+        "380    0.000000    0.000000       0.000000         0.000000       0.001364   \n",
+        "381    0.000000    0.000000       0.017021         0.000000       0.001064   \n",
+        "382    0.000000    0.000000       0.011760         0.000000       0.000420   \n",
+        "383    0.001045    0.000000       0.000000         0.000000       0.001045   \n",
+        "384    0.002436    0.000000       0.000000         0.000000       0.001218   \n",
+        "385    0.000000    0.000000       0.000000         0.000000       0.001304   \n",
+        "386    0.002829    0.000000       0.019802         0.000000       0.004243   \n",
+        "\n",
+        "     var_exists  star_count  dollar_sign  val_exists  \n",
+        "0      0.000000    0.000000     0.000000    0.000000  \n",
+        "1      0.000000    0.000000     0.000000    0.000000  \n",
+        "2      0.000000    0.000000     0.000000    0.000000  \n",
+        "3      0.000000    0.001235     0.000000    0.000000  \n",
+        "4      0.000000    0.001059     0.000000    0.000000  \n",
+        "5      0.000000    0.001146     0.000000    0.000000  \n",
+        "6      0.000000    0.000000     0.000000    0.000000  \n",
+        "7      0.000000    0.001420     0.000000    0.000000  \n",
+        "8      0.000000    0.000000     0.000000    0.000000  \n",
+        "9      0.006579    0.002193     0.000000    0.000000  \n",
+        "10     0.000000    0.000000     0.000000    0.000000  \n",
+        "11     0.000000    0.000000     0.000000    0.000000  \n",
+        "12     0.000000    0.000000     0.000000    0.000000  \n",
+        "13     0.000000    0.000000     0.000000    0.000000  \n",
+        "14     0.000000    0.001229     0.000000    0.000000  \n",
+        "15     0.000000    0.000000     0.000000    0.000000  \n",
+        "16     0.000000    0.000000     0.000000    0.000000  \n",
+        "17     0.000000    0.000000     0.042506    0.000000  \n",
+        "18     0.000000    0.000000     0.037637    0.000000  \n",
+        "19     0.000000    0.000000     0.046261    0.000000  \n",
+        "20     0.000000    0.000000     0.041609    0.000000  \n",
+        "21     0.000000    0.000000     0.044038    0.000000  \n",
+        "22     0.000000    0.000000     0.057474    0.000000  \n",
+        "23     0.000000    0.000000     0.000000    0.000000  \n",
+        "24     0.000000    0.000000     0.000000    0.004662  \n",
+        "25     0.000000    0.000000     0.000000    0.001449  \n",
+        "26     0.000000    0.000000     0.000000    0.000738  \n",
+        "27     0.000644    0.000000     0.000000    0.003218  \n",
+        "28     0.001216    0.002432     0.000000    0.004863  \n",
+        "29     0.001527    0.002290     0.000000    0.004580  \n",
+        "..          ...         ...          ...         ...  \n",
+        "357    0.000000    0.000000     0.000000    0.000000  \n",
+        "358    0.000000    0.000000     0.000000    0.000000  \n",
+        "359    0.000000    0.000000     0.000000    0.000000  \n",
+        "360    0.000000    0.000000     0.000000    0.000000  \n",
+        "361    0.000000    0.000000     0.000000    0.000000  \n",
+        "362    0.000000    0.000000     0.000000    0.000000  \n",
+        "363    0.004181    0.000836     0.000000    0.003344  \n",
+        "364    0.003288    0.000000     0.000000    0.004110  \n",
+        "365    0.002475    0.001238     0.000000    0.003465  \n",
+        "366    0.002521    0.001146     0.000000    0.003208  \n",
+        "367    0.000000    0.000000     0.000000    0.000000  \n",
+        "368    0.000000    0.000000     0.000000    0.000000  \n",
+        "369    0.000000    0.000000     0.001149    0.000000  \n",
+        "370    0.000000    0.000000     0.000000    0.000000  \n",
+        "371    0.000000    0.000000     0.000000    0.000000  \n",
+        "372    0.000000    0.000000     0.000000    0.000000  \n",
+        "373    0.000000    0.000000     0.000000    0.000000  \n",
+        "374    0.000000    0.000000     0.000000    0.000000  \n",
+        "375    0.000000    0.000000     0.000000    0.000000  \n",
+        "376    0.000000    0.000000     0.000000    0.000000  \n",
+        "377    0.000000    0.000000     0.000000    0.000000  \n",
+        "378    0.000000    0.000000     0.000000    0.000000  \n",
+        "379    0.000000    0.000000     0.000000    0.000000  \n",
+        "380    0.000000    0.000000     0.000000    0.000000  \n",
+        "381    0.000000    0.000000     0.032979    0.000000  \n",
+        "382    0.000000    0.000000     0.015960    0.000000  \n",
+        "383    0.000000    0.001045     0.000000    0.000000  \n",
+        "384    0.000000    0.000000     0.000000    0.000000  \n",
+        "385    0.000000    0.000000     0.000000    0.000000  \n",
+        "386    0.001414    0.000000     0.000000    0.004243  \n",
+        "\n",
+        "[387 rows x 15 columns]"
+       ]
+      }
+     ],
+     "prompt_number": 1
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "test_info = Corpus([filename for filename in glob.iglob(os.path.join('test/', '*'))])\n",
+      "test_info_df = test_info.compl_df_build(True)\n",
+      "test_info_df['answers'] = pd.read_csv('test_fixed.csv', dtype='object')\n",
+      "test_info_df"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "html": [
+        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+        "<table border=\"1\" class=\"dataframe\">\n",
+        "  <thead>\n",
+        "    <tr style=\"text-align: right;\">\n",
+        "      <th></th>\n",
+        "      <th>parent_count</th>\n",
+        "      <th>double_colon</th>\n",
+        "      <th>let_exists</th>\n",
+        "      <th>less_minus</th>\n",
+        "      <th>paren_star</th>\n",
+        "      <th>def_exists</th>\n",
+        "      <th>end_exists</th>\n",
+        "      <th>curly_bracket</th>\n",
+        "      <th>slash_star_star</th>\n",
+        "      <th>forward_slash</th>\n",
+        "      <th>var_exists</th>\n",
+        "      <th>star_count</th>\n",
+        "      <th>dollar_sign</th>\n",
+        "      <th>val_exists</th>\n",
+        "      <th>answers</th>\n",
+        "    </tr>\n",
+        "  </thead>\n",
+        "  <tbody>\n",
+        "    <tr>\n",
+        "      <th>0 </th>\n",
+        "      <td> 0.045734</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001759</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001759</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  1</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>1 </th>\n",
+        "      <td> 0.063037</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.022923</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002865</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  4</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>2 </th>\n",
+        "      <td> 0.042795</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000058</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000058</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.019122</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.005069</td>\n",
+        "      <td> 0.002477</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000173</td>\n",
+        "      <td> 0.000346</td>\n",
+        "      <td>  4</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>3 </th>\n",
+        "      <td> 0.047059</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.035294</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.011765</td>\n",
+        "      <td> 0.005882</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  4</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>4 </th>\n",
+        "      <td> 0.015708</td>\n",
+        "      <td> 0.000561</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000281</td>\n",
+        "      <td> 0.002805</td>\n",
+        "      <td> 0.004769</td>\n",
+        "      <td> 0.001122</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  9</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>5 </th>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002037</td>\n",
+        "      <td> 0.004073</td>\n",
+        "      <td> 0.008147</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004073</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  9</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>6 </th>\n",
+        "      <td> 0.008163</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.008163</td>\n",
+        "      <td> 0.014286</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  9</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>7 </th>\n",
+        "      <td> 0.013329</td>\n",
+        "      <td> 0.000915</td>\n",
+        "      <td> 0.000065</td>\n",
+        "      <td> 0.000457</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000131</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002483</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.002548</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  2</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>8 </th>\n",
+        "      <td> 0.058065</td>\n",
+        "      <td> 0.006452</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.006452</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  2</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>9 </th>\n",
+        "      <td> 0.013752</td>\n",
+        "      <td> 0.003929</td>\n",
+        "      <td> 0.000491</td>\n",
+        "      <td> 0.002947</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.006876</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.004912</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  2</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>10</th>\n",
+        "      <td> 0.124352</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 11</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>11</th>\n",
+        "      <td> 0.088670</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  1</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>12</th>\n",
+        "      <td> 0.222222</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 11</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>13</th>\n",
+        "      <td> 0.110846</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000894</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000894</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 11</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>14</th>\n",
+        "      <td> 0.006645</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002848</td>\n",
+        "      <td> 0.003797</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  3</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>15</th>\n",
+        "      <td> 0.006572</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002191</td>\n",
+        "      <td> 0.002738</td>\n",
+        "      <td> 0.000548</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  3</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>16</th>\n",
+        "      <td> 0.027182</td>\n",
+        "      <td> 0.001073</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000715</td>\n",
+        "      <td> 0.001788</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.016452</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001073</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.008941</td>\n",
+        "      <td> 0.003577</td>\n",
+        "      <td> 10</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>17</th>\n",
+        "      <td> 0.014606</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004173</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.003130</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001043</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.007825</td>\n",
+        "      <td> 10</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>18</th>\n",
+        "      <td> 0.019254</td>\n",
+        "      <td> 0.000301</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.008123</td>\n",
+        "      <td> 0.003460</td>\n",
+        "      <td> 0.000150</td>\n",
+        "      <td> 0.000301</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.014591</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  7</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>19</th>\n",
+        "      <td> 0.058997</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002950</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.011799</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.005900</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.014749</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  7</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>20</th>\n",
+        "      <td> 0.097902</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  1</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>21</th>\n",
+        "      <td> 0.053224</td>\n",
+        "      <td> 0.001535</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.012282</td>\n",
+        "      <td> 0.001535</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.020983</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  7</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>22</th>\n",
+        "      <td> 0.026448</td>\n",
+        "      <td> 0.000132</td>\n",
+        "      <td> 0.004893</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.005554</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000397</td>\n",
+        "      <td> 0.003967</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000397</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  5</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>23</th>\n",
+        "      <td> 0.017391</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.005217</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  5</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>24</th>\n",
+        "      <td> 0.025854</td>\n",
+        "      <td> 0.000923</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000923</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.014774</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.024007</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  6</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>25</th>\n",
+        "      <td> 0.026801</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001675</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001675</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.003350</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  1</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>26</th>\n",
+        "      <td> 0.039867</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.013289</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  8</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>27</th>\n",
+        "      <td> 0.028050</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001403</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001403</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  8</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>28</th>\n",
+        "      <td> 0.036810</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.012270</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  8</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>29</th>\n",
+        "      <td> 0.029608</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.003059</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000888</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  8</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>30</th>\n",
+        "      <td> 0.053892</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.020958</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002246</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td>  4</td>\n",
+        "    </tr>\n",
+        "  </tbody>\n",
+        "</table>\n",
+        "</div>"
+       ],
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 2,
+       "text": [
+        "    parent_count  double_colon  let_exists  less_minus  paren_star  \\\n",
+        "0       0.045734      0.000000    0.001759    0.000000    0.000000   \n",
+        "1       0.063037      0.000000    0.000000    0.000000    0.000000   \n",
+        "2       0.042795      0.000000    0.000058    0.000000    0.000058   \n",
+        "3       0.047059      0.000000    0.000000    0.000000    0.000000   \n",
+        "4       0.015708      0.000561    0.000000    0.000000    0.000281   \n",
+        "5       0.000000      0.000000    0.000000    0.000000    0.000000   \n",
+        "6       0.008163      0.000000    0.000000    0.000000    0.000000   \n",
+        "7       0.013329      0.000915    0.000065    0.000457    0.000000   \n",
+        "8       0.058065      0.006452    0.000000    0.006452    0.000000   \n",
+        "9       0.013752      0.003929    0.000491    0.002947    0.000000   \n",
+        "10      0.124352      0.000000    0.000000    0.000000    0.000000   \n",
+        "11      0.088670      0.000000    0.000000    0.000000    0.000000   \n",
+        "12      0.222222      0.000000    0.000000    0.000000    0.000000   \n",
+        "13      0.110846      0.000000    0.000894    0.000000    0.000000   \n",
+        "14      0.006645      0.000000    0.000000    0.000000    0.000000   \n",
+        "15      0.006572      0.000000    0.000000    0.000000    0.000000   \n",
+        "16      0.027182      0.001073    0.000000    0.000000    0.000715   \n",
+        "17      0.014606      0.000000    0.000000    0.000000    0.000000   \n",
+        "18      0.019254      0.000301    0.000000    0.000000    0.000000   \n",
+        "19      0.058997      0.000000    0.000000    0.000000    0.002950   \n",
+        "20      0.097902      0.000000    0.000000    0.000000    0.000000   \n",
+        "21      0.053224      0.001535    0.000000    0.000000    0.000000   \n",
+        "22      0.026448      0.000132    0.004893    0.000000    0.005554   \n",
+        "23      0.017391      0.000000    0.005217    0.000000    0.000000   \n",
+        "24      0.025854      0.000923    0.000000    0.000000    0.000000   \n",
+        "25      0.026801      0.000000    0.001675    0.000000    0.000000   \n",
+        "26      0.039867      0.000000    0.000000    0.000000    0.000000   \n",
+        "27      0.028050      0.000000    0.000000    0.000000    0.000000   \n",
+        "28      0.036810      0.000000    0.000000    0.000000    0.000000   \n",
+        "29      0.029608      0.000000    0.000000    0.000000    0.000000   \n",
+        "30      0.053892      0.000000    0.000000    0.000000    0.000000   \n",
+        "\n",
+        "    def_exists  end_exists  curly_bracket  slash_star_star  forward_slash  \\\n",
+        "0     0.000000    0.000000       0.001759         0.000000       0.000000   \n",
+        "1     0.000000    0.000000       0.022923         0.000000       0.000000   \n",
+        "2     0.000000    0.000000       0.019122         0.000000       0.005069   \n",
+        "3     0.000000    0.000000       0.035294         0.000000       0.011765   \n",
+        "4     0.002805    0.004769       0.001122         0.000000       0.000000   \n",
+        "5     0.002037    0.004073       0.008147         0.000000       0.004073   \n",
+        "6     0.008163    0.014286       0.000000         0.000000       0.000000   \n",
+        "7     0.000131    0.000000       0.002483         0.000000       0.000000   \n",
+        "8     0.000000    0.000000       0.000000         0.000000       0.000000   \n",
+        "9     0.000000    0.000000       0.006876         0.000000       0.000000   \n",
+        "10    0.000000    0.000000       0.000000         0.000000       0.000000   \n",
+        "11    0.000000    0.000000       0.000000         0.000000       0.000000   \n",
+        "12    0.000000    0.000000       0.000000         0.000000       0.000000   \n",
+        "13    0.000000    0.000000       0.000000         0.000000       0.000000   \n",
+        "14    0.000000    0.000000       0.002848         0.003797       0.000000   \n",
+        "15    0.000000    0.000000       0.002191         0.002738       0.000548   \n",
+        "16    0.001788    0.000000       0.016452         0.000000       0.001073   \n",
+        "17    0.004173    0.000000       0.003130         0.000000       0.001043   \n",
+        "18    0.000000    0.000000       0.008123         0.003460       0.000150   \n",
+        "19    0.000000    0.000000       0.011799         0.000000       0.005900   \n",
+        "20    0.000000    0.000000       0.000000         0.000000       0.000000   \n",
+        "21    0.000000    0.000000       0.012282         0.001535       0.000000   \n",
+        "22    0.000000    0.000397       0.003967         0.000000       0.000000   \n",
+        "23    0.000000    0.000000       0.000000         0.000000       0.000000   \n",
+        "24    0.000923    0.000000       0.014774         0.000000       0.000000   \n",
+        "25    0.001675    0.000000       0.003350         0.000000       0.000000   \n",
+        "26    0.000000    0.000000       0.013289         0.000000       0.000000   \n",
+        "27    0.001403    0.000000       0.001403         0.000000       0.000000   \n",
+        "28    0.012270    0.000000       0.000000         0.000000       0.000000   \n",
+        "29    0.003059    0.000000       0.000888         0.000000       0.000000   \n",
+        "30    0.000000    0.000000       0.020958         0.000000       0.000000   \n",
+        "\n",
+        "    var_exists  star_count  dollar_sign  val_exists answers  \n",
+        "0     0.000000           0     0.000000    0.000000       1  \n",
+        "1     0.002865           0     0.000000    0.000000       4  \n",
+        "2     0.002477           0     0.000173    0.000346       4  \n",
+        "3     0.005882           0     0.000000    0.000000       4  \n",
+        "4     0.000000           0     0.000000    0.000000       9  \n",
+        "5     0.000000           0     0.000000    0.000000       9  \n",
+        "6     0.000000           0     0.000000    0.000000       9  \n",
+        "7     0.000000           0     0.002548    0.000000       2  \n",
+        "8     0.000000           0     0.000000    0.000000       2  \n",
+        "9     0.000000           0     0.004912    0.000000       2  \n",
+        "10    0.000000           0     0.000000    0.000000      11  \n",
+        "11    0.000000           0     0.000000    0.000000       1  \n",
+        "12    0.000000           0     0.000000    0.000000      11  \n",
+        "13    0.000000           0     0.000894    0.000000      11  \n",
+        "14    0.000000           0     0.000000    0.000000       3  \n",
+        "15    0.000000           0     0.000000    0.000000       3  \n",
+        "16    0.000000           0     0.008941    0.003577      10  \n",
+        "17    0.000000           0     0.000000    0.007825      10  \n",
+        "18    0.000301           0     0.014591    0.000000       7  \n",
+        "19    0.000000           0     0.014749    0.000000       7  \n",
+        "20    0.000000           0     0.000000    0.000000       1  \n",
+        "21    0.000000           0     0.020983    0.000000       7  \n",
+        "22    0.000397           0     0.000000    0.000000       5  \n",
+        "23    0.000000           0     0.000000    0.000000       5  \n",
+        "24    0.000000           0     0.024007    0.000000       6  \n",
+        "25    0.000000           0     0.000000    0.000000       1  \n",
+        "26    0.000000           0     0.000000    0.000000       8  \n",
+        "27    0.000000           0     0.000000    0.000000       8  \n",
+        "28    0.000000           0     0.000000    0.000000       8  \n",
+        "29    0.000000           0     0.000000    0.000000       8  \n",
+        "30    0.002246           0     0.000000    0.000000       4  "
+       ]
+      }
+     ],
+     "prompt_number": 2
+    },
+    {
+     "cell_type": "heading",
+     "level": 1,
+     "metadata": {},
+     "source": [
+      "Choosing the Best Model"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "from sklearn.naive_bayes import GaussianNB\n",
+      "from sklearn.neighbors import KNeighborsClassifier\n",
+      "from sklearn.tree import DecisionTreeClassifier\n",
+      "from sklearn.ensemble import RandomForestClassifier\n",
+      "from sklearn.cluster import KMeans\n",
+      "from sklearn import metrics\n",
+      "import numpy as np\n",
+      "import seaborn as sbn\n",
+      "import matplotlib.pyplot as plt\n",
+      "%matplotlib inline\n",
+      "\n",
+      "corp_train = corpus_df.values[0::,1::]\n",
+      "corp_answer = corpus_df.values[0::,0]\n",
+      "test_train = test_info_df.values[0::,:-1:]\n",
+      "test_answer = test_info_df.values[0::1,-1]\n",
+      "\n",
+      "def run_test_model(classifier, x_train, y_train, x_test, y_test):\n",
+      "\n",
+      "    classifier.fit(x_train, y_train)\n",
+      "    predicted = classifier.predict(x_test)\n",
+      "    print(metrics.classification_report(y_test, predicted))\n",
+      "    print(metrics.confusion_matrix(y_test, predicted))\n",
+      "    return metrics.f1_score(y_test, predicted)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 3
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "run_test_model(RandomForestClassifier(50), corp_train, corp_answer, test_train, test_answer)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        "             precision    recall  f1-score   support\n",
+        "\n",
+        "          1       0.50      0.25      0.33         4\n",
+        "         10       1.00      1.00      1.00         2\n",
+        "         11       0.60      1.00      0.75         3\n",
+        "          2       1.00      1.00      1.00         3\n",
+        "          3       0.50      0.50      0.50         2\n",
+        "          4       1.00      1.00      1.00         4\n",
+        "          5       1.00      1.00      1.00         2\n",
+        "          6       0.33      1.00      0.50         1\n",
+        "          7       1.00      0.33      0.50         3\n",
+        "          8       0.75      0.75      0.75         4\n",
+        "          9       1.00      1.00      1.00         3\n",
+        "\n",
+        "avg / total       0.81      0.77      0.76        31\n",
+        "\n",
+        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
+        " [0 2 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 3 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 3 0 0 0 0 0 0 0]\n",
+        " [1 0 0 0 1 0 0 0 0 0 0]\n",
+        " [0 0 0 0 0 4 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 2 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 1 0 0 0]\n",
+        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 3]]\n"
+       ]
+      },
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 19,
+       "text": [
+        "0.760752688172043"
+       ]
+      }
+     ],
+     "prompt_number": 19
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "answers = []\n",
+      "for num in range(5,100):\n",
+      "    answers.append((num, run_test_model(RandomForestClassifier(num), corp_train, corp_answer, test_train, test_answer)))\n",
+      "answers    "
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        "             precision    recall  f1-score   support\n",
+        "\n",
+        "          1       0.50      1.00      0.67         4\n",
+        "         10       0.00      0.00      0.00         2\n",
+        "         11       1.00      0.33      0.50         3\n",
+        "          2       1.00      1.00      1.00         3\n",
+        "          3       0.00      0.00      0.00         2\n",
+        "          4       1.00      1.00      1.00         4\n",
+        "          5       1.00      0.50      0.67         2\n",
+        "          6       0.33      1.00      0.50         1\n",
+        "          7       1.00      0.33      0.50         3\n",
+        "          8       0.75      0.75      0.75         4\n",
+        "          9       0.60      1.00      0.75         3\n",
+        "\n",
+        "avg / total       0.71      0.68      0.64        31\n",
+        "\n",
+        "[[4 0 0 0 0 0 0 0 0 0 0]\n",
+        " [1 0 0 0 0 0 0 0 0 1 0]\n",
+        " [2 0 1 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 3 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 2]\n",
+        " [0 0 0 0 0 4 0 0 0 0 0]\n",
+        " [1 0 0 0 0 0 1 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 1 0 0 0]\n",
+        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 3]]\n",
+        "             precision    recall  f1-score   support\n",
+        "\n",
+        "          1       0.50      0.25      0.33         4\n",
+        "         10       1.00      1.00      1.00         2\n",
+        "         11       0.50      1.00      0.67         3\n",
+        "          2       1.00      1.00      1.00         3\n",
+        "          3       0.00      0.00      0.00         2\n",
+        "          4       1.00      1.00      1.00         4\n",
+        "          5       1.00      0.50      0.67         2\n",
+        "          6       0.33      1.00      0.50         1\n",
+        "          7       1.00      0.33      0.50         3\n",
+        "          8       0.60      0.75      0.67         4\n",
+        "          9       1.00      1.00      1.00         3\n",
+        "\n",
+        "avg / total       0.75      0.71      0.69        31\n",
+        "\n",
+        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
+        " [0 2 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 3 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 3 0 0 0 0 0 0 0]\n",
+        " [1 0 0 0 0 0 0 0 0 1 0]\n",
+        " [0 0 0 0 0 4 0 0 0 0 0]\n",
+        " [0 0 1 0 0 0 1 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 1 0 0 0]\n",
+        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 3]]\n",
+        "             precision    recall  f1-score   support\n",
+        "\n",
+        "          1       1.00      0.25      0.40         4\n",
+        "         10       1.00      1.00      1.00         2\n",
+        "         11       0.60      1.00      0.75         3\n",
+        "          2       1.00      1.00      1.00         3\n",
+        "          3       0.67      1.00      0.80         2\n",
+        "          4       1.00      1.00      1.00         4\n",
+        "          5       1.00      1.00      1.00         2\n",
+        "          6       0.50      1.00      0.67         1\n",
+        "          7       1.00      0.67      0.80         3\n",
+        "          8       0.75      0.75      0.75         4\n",
+        "          9       1.00      1.00      1.00         3\n",
+        "\n",
+        "avg / total       0.89      0.84      0.82        31\n",
+        "\n",
+        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
+        " [0 2 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 3 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 3 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
+        " [0 0 0 0 0 4 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 2 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 1 0 0 0]\n",
+        " [0 0 0 0 0 0 0 1 2 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 3]]\n",
+        "             precision    recall  f1-score   support\n",
+        "\n",
+        "          1       1.00      0.50      0.67         4\n",
+        "         10       1.00      1.00      1.00         2\n",
+        "         11       0.60      1.00      0.75         3\n",
+        "          2       1.00      1.00      1.00         3\n",
+        "          3       0.00      0.00      0.00         2\n",
+        "          4       1.00      1.00      1.00         4\n",
+        "          5       1.00      1.00      1.00         2\n",
+        "          6       0.50      1.00      0.67         1\n",
+        "          7       1.00      0.67      0.80         3\n",
+        "          8       0.60      0.75      0.67         4\n",
+        "          9       1.00      1.00      1.00         3\n",
+        "\n",
+        "avg / total       0.83      0.81      0.80        31\n"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stderr",
+       "text": [
+        "/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py:1771: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n",
+        "  'precision', 'predicted', average, warn_for)\n",
+        "/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py:1771: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples.\n",
+        "  'precision', 'predicted', average, warn_for)\n",
+        "/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py:1771: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n",
+        "  'precision', 'predicted', average, warn_for)\n"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        "\n",
+        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
+        " [0 2 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 3 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 3 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 0 0 2 0]\n",
+        " [0 0 0 0 0 4 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 2 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 1 0 0 0]\n",
+        " [0 0 0 0 0 0 0 1 2 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 3]]\n",
+        "             precision    recall  f1-score   support\n",
+        "\n",
+        "          1       0.67      0.50      0.57         4\n",
+        "         10       1.00      1.00      1.00         2\n",
+        "         11       0.50      0.67      0.57         3\n",
+        "          2       1.00      1.00      1.00         3\n",
+        "          3       0.50      0.50      0.50         2\n",
+        "          4       1.00      1.00      1.00         4\n",
+        "          5       1.00      1.00      1.00         2\n",
+        "          6       0.25      1.00      0.40         1\n",
+        "          7       0.00      0.00      0.00         3\n",
+        "          8       0.75      0.75      0.75         4\n",
+        "          9       0.67      0.67      0.67         3\n",
+        "\n",
+        "avg / total       0.69      0.71      0.69        31\n",
+        "\n",
+        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
+        " [0 2 0 0 0 0 0 0 0 0 0]\n",
+        " [1 0 2 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 3 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 0 1]\n",
+        " [0 0 0 0 0 4 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 2 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 1 0 0 0]\n",
+        " [0 0 0 0 0 0 0 3 0 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 1 2]]\n",
+        "             precision    recall  f1-score   support\n",
+        "\n",
+        "          1       0.50      0.50      0.50         4\n",
+        "         10       1.00      0.50      0.67         2\n",
+        "         11       0.60      1.00      0.75         3\n",
+        "          2       1.00      1.00      1.00         3\n",
+        "          3       0.00      0.00      0.00         2\n",
+        "          4       1.00      1.00      1.00         4\n",
+        "          5       1.00      1.00      1.00         2\n",
+        "          6       0.33      1.00      0.50         1\n",
+        "          7       1.00      0.67      0.80         3\n",
+        "          8       1.00      0.75      0.86         4\n",
+        "          9       1.00      1.00      1.00         3\n",
+        "\n",
+        "avg / total       0.81      0.77      0.77        31\n",
+        "\n",
+        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
+        " [0 1 0 0 0 0 0 1 0 0 0]\n",
+        " [0 0 3 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 3 0 0 0 0 0 0 0]\n",
+        " [2 0 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 0 4 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 2 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 1 0 0 0]\n",
+        " [0 0 0 0 0 0 0 1 2 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 3]]\n",
+        "             precision    recall  f1-score   support\n",
+        "\n",
+        "          1       1.00      0.25      0.40         4\n",
+        "         10       1.00      1.00      1.00         2\n",
+        "         11       0.60      1.00      0.75         3\n",
+        "          2       1.00      1.00      1.00         3\n",
+        "          3       0.50      0.50      0.50         2\n",
+        "          4       1.00      1.00      1.00         4\n",
+        "          5       1.00      1.00      1.00         2\n",
+        "          6       0.33      1.00      0.50         1\n",
+        "          7       1.00      0.33      0.50         3\n",
+        "          8       0.75      0.75      0.75         4\n",
+        "          9       0.75      1.00      0.86         3\n",
+        "\n",
+        "avg / total       0.85      0.77      0.76        31\n"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        "\n",
+        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
+        " [0 2 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 3 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 3 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 0 1]\n",
+        " [0 0 0 0 0 4 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 2 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 1 0 0 0]\n",
+        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 3]]\n",
+        "             precision    recall  f1-score   support\n",
+        "\n",
+        "          1       1.00      0.50      0.67         4\n",
+        "         10       1.00      1.00      1.00         2\n",
+        "         11       0.60      1.00      0.75         3\n",
+        "          2       1.00      0.67      0.80         3\n",
+        "          3       0.00      0.00      0.00         2\n",
+        "          4       1.00      1.00      1.00         4\n",
+        "          5       1.00      1.00      1.00         2\n",
+        "          6       0.33      1.00      0.50         1\n",
+        "          7       0.50      0.33      0.40         3\n",
+        "          8       1.00      0.75      0.86         4\n",
+        "          9       0.60      1.00      0.75         3\n",
+        "\n",
+        "avg / total       0.79      0.74      0.73        31\n",
+        "\n",
+        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
+        " [0 2 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 3 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 2 0 0 0 0 1 0 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 2]\n",
+        " [0 0 0 0 0 4 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 2 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 1 0 0 0]\n",
+        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 3]]\n",
+        "             precision    recall  f1-score   support\n",
+        "\n",
+        "          1       1.00      0.50      0.67         4\n",
+        "         10       1.00      0.50      0.67         2\n",
+        "         11       0.60      1.00      0.75         3\n",
+        "          2       1.00      1.00      1.00         3\n",
+        "          3       0.00      0.00      0.00         2\n",
+        "          4       1.00      1.00      1.00         4\n",
+        "          5       1.00      1.00      1.00         2\n",
+        "          6       0.33      1.00      0.50         1\n",
+        "          7       1.00      0.33      0.50         3\n",
+        "          8       0.50      0.75      0.60         4\n",
+        "          9       1.00      1.00      1.00         3\n",
+        "\n",
+        "avg / total       0.81      0.74      0.73        31\n"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        "\n",
+        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
+        " [0 1 0 0 0 0 0 0 0 1 0]\n",
+        " [0 0 3 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 3 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 0 0 2 0]\n",
+        " [0 0 0 0 0 4 0 0 0 0 0]\n",
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+        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 3]]\n",
+        "             precision    recall  f1-score   support\n",
+        "\n",
+        "          1       1.00      0.50      0.67         4\n",
+        "         10       1.00      1.00      1.00         2\n",
+        "         11       0.60      1.00      0.75         3\n",
+        "          2       1.00      1.00      1.00         3\n",
+        "          3       0.67      1.00      0.80         2\n",
+        "          4       1.00      1.00      1.00         4\n",
+        "          5       1.00      1.00      1.00         2\n",
+        "          6       0.50      1.00      0.67         1\n",
+        "          7       1.00      0.67      0.80         3\n",
+        "          8       1.00      0.75      0.86         4\n",
+        "          9       1.00      1.00      1.00         3\n",
+        "\n",
+        "avg / total       0.92      0.87      0.87        31\n",
+        "\n",
+        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
+        " [0 2 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 3 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 3 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
+        " [0 0 0 0 0 4 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 2 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 1 0 0 0]\n",
+        " [0 0 0 0 0 0 0 1 2 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 3]]\n",
+        "             precision    recall  f1-score   support\n",
+        "\n",
+        "          1       0.33      0.25      0.29         4\n",
+        "         10       1.00      1.00      1.00         2\n",
+        "         11       0.60      1.00      0.75         3\n",
+        "          2       1.00      1.00      1.00         3\n",
+        "          3       0.00      0.00      0.00         2\n",
+        "          4       1.00      1.00      1.00         4\n",
+        "          5       1.00      1.00      1.00         2\n",
+        "          6       0.33      1.00      0.50         1\n",
+        "          7       1.00      0.33      0.50         3\n",
+        "          8       0.75      0.75      0.75         4\n",
+        "          9       1.00      1.00      1.00         3\n",
+        "\n",
+        "avg / total       0.76      0.74      0.72        31\n"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        "\n",
+        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
+        " [0 2 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 3 0 0 0 0 0 0 0 0]\n",
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+        " [2 0 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 0 4 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 2 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 1 0 0 0]\n",
+        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 3]]\n",
+        "             precision    recall  f1-score   support\n",
+        "\n",
+        "          1       1.00      0.50      0.67         4\n",
+        "         10       1.00      1.00      1.00         2\n",
+        "         11       0.60      1.00      0.75         3\n",
+        "          2       1.00      1.00      1.00         3\n",
+        "          3       0.67      1.00      0.80         2\n",
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+        "          8       1.00      0.75      0.86         4\n",
+        "          9       1.00      1.00      1.00         3\n",
+        "\n",
+        "avg / total       0.92      0.87      0.87        31\n",
+        "\n",
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+        "             precision    recall  f1-score   support\n",
+        "\n",
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+        "          9       1.00      0.67      0.80         3\n",
+        "\n",
+        "avg / total       0.87      0.77      0.76        31\n"
+       ]
+      },
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+        "             precision    recall  f1-score   support\n",
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+        "\n",
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+        "\n",
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+        "             precision    recall  f1-score   support\n",
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+        "          9       1.00      1.00      1.00         3\n",
+        "\n",
+        "avg / total       0.92      0.84      0.84        31\n"
+       ]
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+        "\n",
+        "avg / total       0.87      0.77      0.76        31\n",
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+        "             precision    recall  f1-score   support\n",
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+        "          9       1.00      1.00      1.00         3\n",
+        "\n",
+        "avg / total       0.92      0.84      0.84        31\n"
+       ]
+      },
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+        "\n",
+        "avg / total       0.88      0.81      0.80        31\n",
+        "\n",
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+        "          9       0.75      1.00      0.86         3\n",
+        "\n",
+        "avg / total       0.85      0.77      0.76        31\n"
+       ]
+      },
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+        "          8       0.50      0.75      0.60         4\n",
+        "          9       1.00      1.00      1.00         3\n",
+        "\n",
+        "avg / total       0.81      0.74      0.72        31\n",
+        "\n",
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+        "             precision    recall  f1-score   support\n",
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+        "          9       0.75      1.00      0.86         3\n",
+        "\n",
+        "avg / total       0.88      0.81      0.80        31\n"
+       ]
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+        "\n",
+        "avg / total       0.88      0.81      0.80        31\n"
+       ]
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+      {
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+        "          9       1.00      1.00      1.00         3\n",
+        "\n",
+        "avg / total       0.81      0.77      0.76        31\n"
+       ]
+      },
+      {
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+       "stream": "stdout",
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+        "          9       1.00      1.00      1.00         3\n",
+        "\n",
+        "avg / total       0.82      0.77      0.76        31\n"
+       ]
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+        "          9       1.00      1.00      1.00         3\n",
+        "\n",
+        "avg / total       0.92      0.84      0.84        31\n"
+       ]
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+        "\n",
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+        "\n",
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+        "avg / total       0.92      0.84      0.84        31\n"
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+        "\n",
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+        "\n",
+        "avg / total       0.81      0.77      0.76        31\n"
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+        "\n",
+        "avg / total       0.89      0.84      0.82        31\n"
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+        "\n",
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+        "             precision    recall  f1-score   support\n",
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+        "\n",
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+       ]
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+        "\n",
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+        "\n",
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+        "\n",
+        "avg / total       0.92      0.84      0.84        31\n"
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+        "\n",
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+        "\n",
+        "avg / total       0.81      0.77      0.76        31\n"
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+        "\n",
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+        "\n",
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+        "\n",
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+        "\n",
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+        "\n",
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+        "\n",
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+        "\n",
+        "avg / total       0.92      0.84      0.84        31\n"
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+        "\n",
+        "avg / total       0.86      0.77      0.76        31\n"
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+        "\n",
+        "avg / total       0.92      0.84      0.84        31\n"
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+        "\n",
+        "avg / total       0.88      0.81      0.80        31\n"
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+        "\n",
+        "avg / total       0.92      0.84      0.84        31\n"
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+        "\n",
+        "avg / total       0.92      0.84      0.84        31\n"
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+        "\n",
+        "avg / total       0.82      0.77      0.76        31\n"
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+        "\n",
+        "avg / total       0.89      0.84      0.84        31\n"
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+        "\n",
+        "avg / total       0.92      0.84      0.84        31\n"
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+       "text": [
+        "\n",
+        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
+        " [0 2 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 3 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 3 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
+        " [0 0 0 0 0 4 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 2 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 1 0 0 0]\n",
+        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 3]]\n",
+        "             precision    recall  f1-score   support\n",
+        "\n",
+        "          1       0.50      0.50      0.50         4\n",
+        "         10       1.00      1.00      1.00         2\n",
+        "         11       0.60      1.00      0.75         3\n",
+        "          2       1.00      1.00      1.00         3\n",
+        "          3       0.00      0.00      0.00         2\n",
+        "          4       1.00      1.00      1.00         4\n",
+        "          5       1.00      1.00      1.00         2\n",
+        "          6       0.33      1.00      0.50         1\n",
+        "          7       1.00      0.33      0.50         3\n",
+        "          8       1.00      0.75      0.86         4\n",
+        "          9       1.00      1.00      1.00         3\n",
+        "\n",
+        "avg / total       0.81      0.77      0.76        31\n"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
+        "\n",
+        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
+        " [0 2 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 3 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 3 0 0 0 0 0 0 0]\n",
+        " [2 0 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 0 4 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 2 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 1 0 0 0]\n",
+        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 3]]\n"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stderr",
+       "text": [
+        "/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py:1771: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples.\n",
+        "  'precision', 'predicted', average, warn_for)\n"
+       ]
+      },
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 17,
+       "text": [
+        "[(5, 0.63709677419354838),\n",
+        " (6, 0.68817204301075252),\n",
+        " (7, 0.82311827956989247),\n",
+        " (8, 0.79516129032258065),\n",
+        " (9, 0.69032258064516128),\n",
+        " (10, 0.77135176651305681),\n",
+        " (11, 0.75552995391705069),\n",
+        " (12, 0.73210445468509977),\n",
+        " (13, 0.73064516129032253),\n",
+        " (14, 0.87135176651305668),\n",
+        " (15, 0.72235023041474655),\n",
+        " (16, 0.87135176651305668),\n",
+        " (17, 0.75860215053763436),\n",
+        " (18, 0.71251920122887857),\n",
+        " (19, 0.83694316436251914),\n",
+        " (20, 0.75860215053763436),\n",
+        " (21, 0.83694316436251914),\n",
+        " (22, 0.80376344086021501),\n",
+        " (23, 0.75552995391705069),\n",
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+        " (26, 0.80376344086021501),\n",
+        " (27, 0.76382488479262667),\n",
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+        " (31, 0.76075268817204289),\n",
+        " (32, 0.76113671274961581),\n",
+        " (33, 0.83694316436251914),\n",
+        " (34, 0.82311827956989247),\n",
+        " (35, 0.80314900153609825),\n",
+        " (36, 0.87135176651305668),\n",
+        " (37, 0.78870967741935483),\n",
+        " (38, 0.80376344086021501),\n",
+        " (39, 0.7567588325652842),\n",
+        " (40, 0.80529953917050678),\n",
+        " (41, 0.76113671274961581),\n",
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+        " (44, 0.78870967741935483),\n",
+        " (45, 0.78870967741935483),\n",
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+        " (58, 0.80376344086021501),\n",
+        " (59, 0.75768049155145911),\n",
+        " (60, 0.80376344086021501),\n",
+        " (61, 0.760752688172043),\n",
+        " (62, 0.83694316436251914),\n",
+        " (63, 0.83694316436251914),\n",
+        " (64, 0.87135176651305668),\n",
+        " (65, 0.83694316436251914),\n",
+        " (66, 0.83970814132104454),\n",
+        " (67, 0.80529953917050678),\n",
+        " (68, 0.76382488479262667),\n",
+        " (69, 0.80529953917050678),\n",
+        " (70, 0.83694316436251914),\n",
+        " (71, 0.83694316436251914),\n",
+        " (72, 0.83694316436251914),\n",
+        " (73, 0.80376344086021501),\n",
+        " (74, 0.83694316436251914),\n",
+        " (75, 0.76382488479262667),\n",
+        " (76, 0.78870967741935483),\n",
+        " (77, 0.76382488479262667),\n",
+        " (78, 0.80376344086021501),\n",
+        " (79, 0.76075268817204289),\n",
+        " (80, 0.83694316436251914),\n",
+        " (81, 0.83694316436251914),\n",
+        " (82, 0.76075268817204289),\n",
+        " (83, 0.80529953917050678),\n",
+        " (84, 0.83694316436251914),\n",
+        " (85, 0.83694316436251914),\n",
+        " (86, 0.75921658986175111),\n",
+        " (87, 0.83694316436251914),\n",
+        " (88, 0.80376344086021501),\n",
+        " (89, 0.83694316436251914),\n",
+        " (90, 0.83694316436251914),\n",
+        " (91, 0.75860215053763436),\n",
+        " (92, 0.83694316436251914),\n",
+        " (93, 0.80376344086021501),\n",
+        " (94, 0.83694316436251914),\n",
+        " (95, 0.83694316436251914),\n",
+        " (96, 0.75768049155145911),\n",
+        " (97, 0.83817204301075277),\n",
+        " (98, 0.83694316436251914),\n",
+        " (99, 0.76382488479262667)]"
+       ]
+      }
+     ],
+     "prompt_number": 17
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "clean_answers = [y for x,y in answers]\n",
+      "plt.plot(clean_answers)\n",
+      "plt.show()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "png": 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pbAYMLYHo2YJRhp8HeAG/x5+NiR0kOVZxP7xa4mAev2mMvVqx9yEcRkrxBjGj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\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x10b316c18>"
+       ]
+      }
+     ],
+     "prompt_number": 18
+    },
     {
      "cell_type": "heading",
      "level": 1,
@@ -453,17 +5424,38 @@
      ],
      "language": "python",
      "metadata": {},
-     "outputs": []
+     "outputs": [],
+     "prompt_number": 7
     },
     {
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "check_code_snippet('test/1', corp_train, corp_answer)"
+      "check_code_snippet('test/22', corp_train, corp_answer)"
      ],
      "language": "python",
      "metadata": {},
-     "outputs": []
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 8,
+       "text": [
+        "[('javascript', 1.0),\n",
+        " ('java', 2.7703304550449276e-81),\n",
+        " ('clojure', 0.0),\n",
+        " ('scala', 0.0),\n",
+        " ('scheme', 0.0),\n",
+        " ('haskell', 0.0),\n",
+        " ('ocaml', 0.0),\n",
+        " ('perl', 0.0),\n",
+        " ('php', 0.0),\n",
+        " ('python', 0.0),\n",
+        " ('ruby', 0.0)]"
+       ]
+      }
+     ],
+     "prompt_number": 8
     },
     {
      "cell_type": "code",
diff --git a/test/33 b/test/33
new file mode 100644
index 0000000..5f0b483
--- /dev/null
+++ b/test/33
@@ -0,0 +1,56 @@
+#!/usr/local/bin/perl
+
+use English;
+use Carp;
+use Getopt::Long;
+
+sub Usage{
+  my $message = shift;
+
+  print STDERR $message, "\n" if $message;
+  print STDERR "\nUsage: $0 -d(ef) definition_file < source > newsource\n";
+
+  print STDERR <<'EOM';
+          -d(ef) filename  : Specifies the definition file which is a set of pairs, each corresponding to a "replacement pattern", e.g.,
+                             a A
+                             b B
+           ...
+           z Z
+           would replace all lower cases with upper cases
+
+          -h(elp) 	: display this message
+
+EOM
+
+    exit(1);
+
+}
+
+if (! &GetOptions("help", "def=s") or
+    $opt_help) {
+  &Usage();
+}
+
+open(D, $opt_def) || die "can't open definition file:$opt_def\n";
+while (<D>) {
+    ($oldp, $newp) = split;
+    $dic{$oldp}=$newp;
+}
+close(D);
+
+$oldStr = "";
+$newStr ="";
+while (<STDIN>) {
+    $oldStr = $_;
+    foreach $k (keys %dic) {
+  s/$k/$dic{$k}/g;
+    }
+
+    $newStr = $_;
+    if ($oldStr ne $newStr) {
+  print STDERR "\n";
+  print STDERR "old>>$oldStr";
+  print STDERR "new>>$newStr";
+    }
+    print;
+}
diff --git a/test_fixed.csv b/test_fixed.csv
index 63c3d03..a7f0fb5 100644
--- a/test_fixed.csv
+++ b/test_fixed.csv
@@ -1 +1 @@
-answers
1
4
4
4
9
9
9
2
2
2
11
1
11
11
3
3
10
10
7
7
1
7
5
5
1
8
8
8
8
4
\ No newline at end of file
+answers
1
4
4
4
9
9
9
2
2
2
11
1
11
11
3
3
10
10
7
7
1
7
5
5
6
1
8
8
8
8
4
\ No newline at end of file

From 6ea84782930d924e171ef0ab4ad427da40d92f1b Mon Sep 17 00:00:00 2001
From: Zack Cooper <zackjcooper@gmail.com>
Date: Sun, 15 Feb 2015 23:15:15 -0500
Subject: [PATCH 4/6] finished project

---
 corpus_build.py            |    7 +-
 lang classifier live.ipynb | 2558 ++++++++++--------------------------
 2 files changed, 687 insertions(+), 1878 deletions(-)

diff --git a/corpus_build.py b/corpus_build.py
index 2bf6982..b659079 100644
--- a/corpus_build.py
+++ b/corpus_build.py
@@ -64,7 +64,12 @@
                 ('var_exists', r"\bvar\b"),
                 ('star_count', r"\b\*\b"),
                 ('dollar_sign', r"\$"),
-                ('val_exists', r"\bval\b")]
+                ('val_exists', r"\bval\b"),
+                ('else_if', r"(else if)"),
+                ('elif', r"(elif)"),
+                ('elif', r"(print )"),
+                ('elif', r"(print\()"),
+                ('void', r"(void)")]
 
 
 class Corpus():
diff --git a/lang classifier live.ipynb b/lang classifier live.ipynb
index 9d0abb2..3b16179 100644
--- a/lang classifier live.ipynb	
+++ b/lang classifier live.ipynb	
@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:d283fdea1a61866f7cbeaeeaafff75fcae1237f43b5990f43814c78cd7baa485"
+  "signature": "sha256:351106de656a94ded25f92477ba635151dc3e3be72b67d7f2d9459b9b4fb2be8"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -54,6 +54,8 @@
         "      <th>star_count</th>\n",
         "      <th>dollar_sign</th>\n",
         "      <th>val_exists</th>\n",
+        "      <th>else_if</th>\n",
+        "      <th>elif</th>\n",
         "    </tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
@@ -74,6 +76,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>1  </th>\n",
@@ -92,6 +96,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>2  </th>\n",
@@ -110,6 +116,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>3  </th>\n",
@@ -128,6 +136,8 @@
         "      <td> 0.001235</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>4  </th>\n",
@@ -146,6 +156,8 @@
         "      <td> 0.001059</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>5  </th>\n",
@@ -164,6 +176,8 @@
         "      <td> 0.001146</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>6  </th>\n",
@@ -182,6 +196,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>7  </th>\n",
@@ -200,6 +216,8 @@
         "      <td> 0.001420</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>8  </th>\n",
@@ -218,6 +236,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>9  </th>\n",
@@ -236,6 +256,8 @@
         "      <td> 0.002193</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002193</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>10 </th>\n",
@@ -254,6 +276,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>11 </th>\n",
@@ -272,6 +296,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>12 </th>\n",
@@ -290,6 +316,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>13 </th>\n",
@@ -308,6 +336,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>14 </th>\n",
@@ -326,6 +356,8 @@
         "      <td> 0.001229</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>15 </th>\n",
@@ -344,6 +376,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>16 </th>\n",
@@ -362,6 +396,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>17 </th>\n",
@@ -380,6 +416,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.042506</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>18 </th>\n",
@@ -398,6 +436,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.037637</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>19 </th>\n",
@@ -416,6 +456,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.046261</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>20 </th>\n",
@@ -434,6 +476,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.041609</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>21 </th>\n",
@@ -452,6 +496,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.044038</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>22 </th>\n",
@@ -470,6 +516,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.057474</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000258</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>23 </th>\n",
@@ -488,6 +536,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001670</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>24 </th>\n",
@@ -506,6 +556,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.004662</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>25 </th>\n",
@@ -524,6 +576,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.001449</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>26 </th>\n",
@@ -542,6 +596,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000738</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>27 </th>\n",
@@ -560,6 +616,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.003218</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.002574</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>28 </th>\n",
@@ -578,6 +636,8 @@
         "      <td> 0.002432</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.004863</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>29 </th>\n",
@@ -596,6 +656,8 @@
         "      <td> 0.002290</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.004580</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.003053</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>...</th>\n",
@@ -614,6 +676,8 @@
         "      <td>...</td>\n",
         "      <td>...</td>\n",
         "      <td>...</td>\n",
+        "      <td>...</td>\n",
+        "      <td>...</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>357</th>\n",
@@ -632,6 +696,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000693</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>358</th>\n",
@@ -650,6 +716,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000791</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>359</th>\n",
@@ -668,6 +736,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000600</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>360</th>\n",
@@ -686,6 +756,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>361</th>\n",
@@ -704,6 +776,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>362</th>\n",
@@ -722,6 +796,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>363</th>\n",
@@ -740,6 +816,8 @@
         "      <td> 0.000836</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.003344</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>364</th>\n",
@@ -758,6 +836,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.004110</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>365</th>\n",
@@ -776,6 +856,8 @@
         "      <td> 0.001238</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.003465</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>366</th>\n",
@@ -794,6 +876,8 @@
         "      <td> 0.001146</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.003208</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>367</th>\n",
@@ -812,6 +896,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>368</th>\n",
@@ -830,6 +916,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>369</th>\n",
@@ -848,6 +936,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.001149</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>370</th>\n",
@@ -866,6 +956,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>371</th>\n",
@@ -884,6 +976,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>372</th>\n",
@@ -902,6 +996,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>373</th>\n",
@@ -920,6 +1016,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>374</th>\n",
@@ -938,6 +1036,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>375</th>\n",
@@ -956,6 +1056,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>376</th>\n",
@@ -974,6 +1076,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>377</th>\n",
@@ -992,6 +1096,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>378</th>\n",
@@ -1010,6 +1116,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>379</th>\n",
@@ -1028,6 +1136,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>380</th>\n",
@@ -1046,6 +1156,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>381</th>\n",
@@ -1064,6 +1176,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.032979</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>382</th>\n",
@@ -1082,6 +1196,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.015960</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>383</th>\n",
@@ -1100,6 +1216,8 @@
         "      <td> 0.001045</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001045</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>384</th>\n",
@@ -1118,6 +1236,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.001218</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>385</th>\n",
@@ -1136,6 +1256,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>386</th>\n",
@@ -1154,15 +1276,17 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.004243</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
-        "<p>387 rows \u00d7 15 columns</p>\n",
+        "<p>387 rows \u00d7 17 columns</p>\n",
         "</div>"
        ],
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 1,
+       "prompt_number": 9,
        "text": [
         "    hit_num  parent_count  double_colon  let_exists  less_minus  paren_star  \\\n",
         "0         1      0.071901      0.000000    0.002066    0.000000    0.001240   \n",
@@ -1290,74 +1414,74 @@
         "385    0.000000    0.000000       0.000000         0.000000       0.001304   \n",
         "386    0.002829    0.000000       0.019802         0.000000       0.004243   \n",
         "\n",
-        "     var_exists  star_count  dollar_sign  val_exists  \n",
-        "0      0.000000    0.000000     0.000000    0.000000  \n",
-        "1      0.000000    0.000000     0.000000    0.000000  \n",
-        "2      0.000000    0.000000     0.000000    0.000000  \n",
-        "3      0.000000    0.001235     0.000000    0.000000  \n",
-        "4      0.000000    0.001059     0.000000    0.000000  \n",
-        "5      0.000000    0.001146     0.000000    0.000000  \n",
-        "6      0.000000    0.000000     0.000000    0.000000  \n",
-        "7      0.000000    0.001420     0.000000    0.000000  \n",
-        "8      0.000000    0.000000     0.000000    0.000000  \n",
-        "9      0.006579    0.002193     0.000000    0.000000  \n",
-        "10     0.000000    0.000000     0.000000    0.000000  \n",
-        "11     0.000000    0.000000     0.000000    0.000000  \n",
-        "12     0.000000    0.000000     0.000000    0.000000  \n",
-        "13     0.000000    0.000000     0.000000    0.000000  \n",
-        "14     0.000000    0.001229     0.000000    0.000000  \n",
-        "15     0.000000    0.000000     0.000000    0.000000  \n",
-        "16     0.000000    0.000000     0.000000    0.000000  \n",
-        "17     0.000000    0.000000     0.042506    0.000000  \n",
-        "18     0.000000    0.000000     0.037637    0.000000  \n",
-        "19     0.000000    0.000000     0.046261    0.000000  \n",
-        "20     0.000000    0.000000     0.041609    0.000000  \n",
-        "21     0.000000    0.000000     0.044038    0.000000  \n",
-        "22     0.000000    0.000000     0.057474    0.000000  \n",
-        "23     0.000000    0.000000     0.000000    0.000000  \n",
-        "24     0.000000    0.000000     0.000000    0.004662  \n",
-        "25     0.000000    0.000000     0.000000    0.001449  \n",
-        "26     0.000000    0.000000     0.000000    0.000738  \n",
-        "27     0.000644    0.000000     0.000000    0.003218  \n",
-        "28     0.001216    0.002432     0.000000    0.004863  \n",
-        "29     0.001527    0.002290     0.000000    0.004580  \n",
-        "..          ...         ...          ...         ...  \n",
-        "357    0.000000    0.000000     0.000000    0.000000  \n",
-        "358    0.000000    0.000000     0.000000    0.000000  \n",
-        "359    0.000000    0.000000     0.000000    0.000000  \n",
-        "360    0.000000    0.000000     0.000000    0.000000  \n",
-        "361    0.000000    0.000000     0.000000    0.000000  \n",
-        "362    0.000000    0.000000     0.000000    0.000000  \n",
-        "363    0.004181    0.000836     0.000000    0.003344  \n",
-        "364    0.003288    0.000000     0.000000    0.004110  \n",
-        "365    0.002475    0.001238     0.000000    0.003465  \n",
-        "366    0.002521    0.001146     0.000000    0.003208  \n",
-        "367    0.000000    0.000000     0.000000    0.000000  \n",
-        "368    0.000000    0.000000     0.000000    0.000000  \n",
-        "369    0.000000    0.000000     0.001149    0.000000  \n",
-        "370    0.000000    0.000000     0.000000    0.000000  \n",
-        "371    0.000000    0.000000     0.000000    0.000000  \n",
-        "372    0.000000    0.000000     0.000000    0.000000  \n",
-        "373    0.000000    0.000000     0.000000    0.000000  \n",
-        "374    0.000000    0.000000     0.000000    0.000000  \n",
-        "375    0.000000    0.000000     0.000000    0.000000  \n",
-        "376    0.000000    0.000000     0.000000    0.000000  \n",
-        "377    0.000000    0.000000     0.000000    0.000000  \n",
-        "378    0.000000    0.000000     0.000000    0.000000  \n",
-        "379    0.000000    0.000000     0.000000    0.000000  \n",
-        "380    0.000000    0.000000     0.000000    0.000000  \n",
-        "381    0.000000    0.000000     0.032979    0.000000  \n",
-        "382    0.000000    0.000000     0.015960    0.000000  \n",
-        "383    0.000000    0.001045     0.000000    0.000000  \n",
-        "384    0.000000    0.000000     0.000000    0.000000  \n",
-        "385    0.000000    0.000000     0.000000    0.000000  \n",
-        "386    0.001414    0.000000     0.000000    0.004243  \n",
-        "\n",
-        "[387 rows x 15 columns]"
+        "     var_exists  star_count  dollar_sign  val_exists   else_if      elif  \n",
+        "0      0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "1      0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "2      0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "3      0.000000    0.001235     0.000000    0.000000  0.000000  0.000000  \n",
+        "4      0.000000    0.001059     0.000000    0.000000  0.000000  0.000000  \n",
+        "5      0.000000    0.001146     0.000000    0.000000  0.000000  0.000000  \n",
+        "6      0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "7      0.000000    0.001420     0.000000    0.000000  0.000000  0.000000  \n",
+        "8      0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "9      0.006579    0.002193     0.000000    0.000000  0.000000  0.002193  \n",
+        "10     0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "11     0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "12     0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "13     0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "14     0.000000    0.001229     0.000000    0.000000  0.000000  0.000000  \n",
+        "15     0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "16     0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "17     0.000000    0.000000     0.042506    0.000000  0.000000  0.000000  \n",
+        "18     0.000000    0.000000     0.037637    0.000000  0.000000  0.000000  \n",
+        "19     0.000000    0.000000     0.046261    0.000000  0.000000  0.000000  \n",
+        "20     0.000000    0.000000     0.041609    0.000000  0.000000  0.000000  \n",
+        "21     0.000000    0.000000     0.044038    0.000000  0.000000  0.000000  \n",
+        "22     0.000000    0.000000     0.057474    0.000000  0.000258  0.000000  \n",
+        "23     0.000000    0.000000     0.000000    0.000000  0.000000  0.001670  \n",
+        "24     0.000000    0.000000     0.000000    0.004662  0.000000  0.000000  \n",
+        "25     0.000000    0.000000     0.000000    0.001449  0.000000  0.000000  \n",
+        "26     0.000000    0.000000     0.000000    0.000738  0.000000  0.000000  \n",
+        "27     0.000644    0.000000     0.000000    0.003218  0.000000  0.002574  \n",
+        "28     0.001216    0.002432     0.000000    0.004863  0.000000  0.000000  \n",
+        "29     0.001527    0.002290     0.000000    0.004580  0.000000  0.003053  \n",
+        "..          ...         ...          ...         ...       ...       ...  \n",
+        "357    0.000000    0.000000     0.000000    0.000000  0.000000  0.000693  \n",
+        "358    0.000000    0.000000     0.000000    0.000000  0.000000  0.000791  \n",
+        "359    0.000000    0.000000     0.000000    0.000000  0.000000  0.000600  \n",
+        "360    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "361    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "362    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "363    0.004181    0.000836     0.000000    0.003344  0.000000  0.000000  \n",
+        "364    0.003288    0.000000     0.000000    0.004110  0.000000  0.000000  \n",
+        "365    0.002475    0.001238     0.000000    0.003465  0.000000  0.000000  \n",
+        "366    0.002521    0.001146     0.000000    0.003208  0.000000  0.000000  \n",
+        "367    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "368    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "369    0.000000    0.000000     0.001149    0.000000  0.000000  0.000000  \n",
+        "370    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "371    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "372    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "373    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "374    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "375    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "376    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "377    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "378    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "379    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "380    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "381    0.000000    0.000000     0.032979    0.000000  0.000000  0.000000  \n",
+        "382    0.000000    0.000000     0.015960    0.000000  0.000000  0.000000  \n",
+        "383    0.000000    0.001045     0.000000    0.000000  0.000000  0.001045  \n",
+        "384    0.000000    0.000000     0.000000    0.000000  0.000000  0.001218  \n",
+        "385    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
+        "386    0.001414    0.000000     0.000000    0.004243  0.000000  0.000000  \n",
+        "\n",
+        "[387 rows x 17 columns]"
        ]
       }
      ],
-     "prompt_number": 1
+     "prompt_number": 9
     },
     {
      "cell_type": "code",
@@ -1392,6 +1516,8 @@
         "      <th>star_count</th>\n",
         "      <th>dollar_sign</th>\n",
         "      <th>val_exists</th>\n",
+        "      <th>else_if</th>\n",
+        "      <th>elif</th>\n",
         "      <th>answers</th>\n",
         "    </tr>\n",
         "  </thead>\n",
@@ -1412,6 +1538,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  1</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1430,6 +1558,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1448,6 +1578,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000173</td>\n",
         "      <td> 0.000346</td>\n",
+        "      <td> 0.000288</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1466,6 +1598,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1484,6 +1618,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  9</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1502,6 +1638,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  9</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1520,6 +1658,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  9</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1538,6 +1678,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.002548</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1556,6 +1698,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1574,6 +1718,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.004912</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  2</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1592,6 +1738,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td> 11</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1610,6 +1758,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  1</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1628,6 +1778,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td> 11</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1646,6 +1798,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000894</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td> 11</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1664,6 +1818,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  3</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1682,6 +1838,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  3</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1700,6 +1858,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.008941</td>\n",
         "      <td> 0.003577</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td> 10</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1718,6 +1878,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.007825</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td> 10</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1736,6 +1898,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.014591</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  7</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1754,6 +1918,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.014749</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  7</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1772,6 +1938,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  1</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1790,6 +1958,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.020983</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  7</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1808,6 +1978,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  5</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1826,6 +1998,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  5</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1844,6 +2018,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.024007</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  6</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1862,6 +2038,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  1</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1880,6 +2058,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.004983</td>\n",
         "      <td>  8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1898,6 +2078,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1916,6 +2098,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1934,6 +2118,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  8</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -1952,6 +2138,8 @@
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
+        "      <td> 0.000000</td>\n",
         "      <td>  4</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
@@ -1960,7 +2148,7 @@
        ],
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 2,
+       "prompt_number": 10,
        "text": [
         "    parent_count  double_colon  let_exists  less_minus  paren_star  \\\n",
         "0       0.045734      0.000000    0.001759    0.000000    0.000000   \n",
@@ -2028,60 +2216,89 @@
         "29    0.003059    0.000000       0.000888         0.000000       0.000000   \n",
         "30    0.000000    0.000000       0.020958         0.000000       0.000000   \n",
         "\n",
-        "    var_exists  star_count  dollar_sign  val_exists answers  \n",
-        "0     0.000000           0     0.000000    0.000000       1  \n",
-        "1     0.002865           0     0.000000    0.000000       4  \n",
-        "2     0.002477           0     0.000173    0.000346       4  \n",
-        "3     0.005882           0     0.000000    0.000000       4  \n",
-        "4     0.000000           0     0.000000    0.000000       9  \n",
-        "5     0.000000           0     0.000000    0.000000       9  \n",
-        "6     0.000000           0     0.000000    0.000000       9  \n",
-        "7     0.000000           0     0.002548    0.000000       2  \n",
-        "8     0.000000           0     0.000000    0.000000       2  \n",
-        "9     0.000000           0     0.004912    0.000000       2  \n",
-        "10    0.000000           0     0.000000    0.000000      11  \n",
-        "11    0.000000           0     0.000000    0.000000       1  \n",
-        "12    0.000000           0     0.000000    0.000000      11  \n",
-        "13    0.000000           0     0.000894    0.000000      11  \n",
-        "14    0.000000           0     0.000000    0.000000       3  \n",
-        "15    0.000000           0     0.000000    0.000000       3  \n",
-        "16    0.000000           0     0.008941    0.003577      10  \n",
-        "17    0.000000           0     0.000000    0.007825      10  \n",
-        "18    0.000301           0     0.014591    0.000000       7  \n",
-        "19    0.000000           0     0.014749    0.000000       7  \n",
-        "20    0.000000           0     0.000000    0.000000       1  \n",
-        "21    0.000000           0     0.020983    0.000000       7  \n",
-        "22    0.000397           0     0.000000    0.000000       5  \n",
-        "23    0.000000           0     0.000000    0.000000       5  \n",
-        "24    0.000000           0     0.024007    0.000000       6  \n",
-        "25    0.000000           0     0.000000    0.000000       1  \n",
-        "26    0.000000           0     0.000000    0.000000       8  \n",
-        "27    0.000000           0     0.000000    0.000000       8  \n",
-        "28    0.000000           0     0.000000    0.000000       8  \n",
-        "29    0.000000           0     0.000000    0.000000       8  \n",
-        "30    0.002246           0     0.000000    0.000000       4  "
+        "    var_exists  star_count  dollar_sign  val_exists   else_if      elif  \\\n",
+        "0     0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "1     0.002865           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "2     0.002477           0     0.000173    0.000346  0.000288  0.000000   \n",
+        "3     0.005882           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "4     0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "5     0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "6     0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "7     0.000000           0     0.002548    0.000000  0.000000  0.000000   \n",
+        "8     0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "9     0.000000           0     0.004912    0.000000  0.000000  0.000000   \n",
+        "10    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "11    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "12    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "13    0.000000           0     0.000894    0.000000  0.000000  0.000000   \n",
+        "14    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "15    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "16    0.000000           0     0.008941    0.003577  0.000000  0.000000   \n",
+        "17    0.000000           0     0.000000    0.007825  0.000000  0.000000   \n",
+        "18    0.000301           0     0.014591    0.000000  0.000000  0.000000   \n",
+        "19    0.000000           0     0.014749    0.000000  0.000000  0.000000   \n",
+        "20    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "21    0.000000           0     0.020983    0.000000  0.000000  0.000000   \n",
+        "22    0.000397           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "23    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "24    0.000000           0     0.024007    0.000000  0.000000  0.000000   \n",
+        "25    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "26    0.000000           0     0.000000    0.000000  0.000000  0.004983   \n",
+        "27    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "28    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "29    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "30    0.002246           0     0.000000    0.000000  0.000000  0.000000   \n",
+        "\n",
+        "   answers  \n",
+        "0        1  \n",
+        "1        4  \n",
+        "2        4  \n",
+        "3        4  \n",
+        "4        9  \n",
+        "5        9  \n",
+        "6        9  \n",
+        "7        2  \n",
+        "8        2  \n",
+        "9        2  \n",
+        "10      11  \n",
+        "11       1  \n",
+        "12      11  \n",
+        "13      11  \n",
+        "14       3  \n",
+        "15       3  \n",
+        "16      10  \n",
+        "17      10  \n",
+        "18       7  \n",
+        "19       7  \n",
+        "20       1  \n",
+        "21       7  \n",
+        "22       5  \n",
+        "23       5  \n",
+        "24       6  \n",
+        "25       1  \n",
+        "26       8  \n",
+        "27       8  \n",
+        "28       8  \n",
+        "29       8  \n",
+        "30       4  "
        ]
       }
      ],
-     "prompt_number": 2
+     "prompt_number": 10
     },
     {
      "cell_type": "heading",
      "level": 1,
      "metadata": {},
      "source": [
-      "Choosing the Best Model"
+      "RandomForestClassifier Model"
      ]
     },
     {
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "from sklearn.naive_bayes import GaussianNB\n",
-      "from sklearn.neighbors import KNeighborsClassifier\n",
-      "from sklearn.tree import DecisionTreeClassifier\n",
       "from sklearn.ensemble import RandomForestClassifier\n",
-      "from sklearn.cluster import KMeans\n",
       "from sklearn import metrics\n",
       "import numpy as np\n",
       "import seaborn as sbn\n",
@@ -2104,7 +2321,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 3
+     "prompt_number": 11
     },
     {
      "cell_type": "code",
@@ -2121,25 +2338,25 @@
        "text": [
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.50      0.25      0.33         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.50      0.50      0.50         2\n",
+        "          3       0.00      0.00      0.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          8       1.00      0.75      0.86         4\n",
+        "          9       0.60      1.00      0.75         3\n",
         "\n",
-        "avg / total       0.81      0.77      0.76        31\n",
+        "avg / total       0.84      0.77      0.76        31\n",
         "\n",
-        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
+        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [1 0 0 0 1 0 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 2]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -2151,20 +2368,20 @@
       {
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 19,
+       "prompt_number": 12,
        "text": [
-        "0.760752688172043"
+        "0.76113671274961581"
        ]
       }
      ],
-     "prompt_number": 19
+     "prompt_number": 12
     },
     {
      "cell_type": "code",
      "collapsed": false,
      "input": [
       "answers = []\n",
-      "for num in range(5,100):\n",
+      "for num in range(20,70):\n",
       "    answers.append((num, run_test_model(RandomForestClassifier(num), corp_train, corp_answer, test_train, test_answer)))\n",
       "answers    "
      ],
@@ -2177,1423 +2394,112 @@
        "text": [
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.50      1.00      0.67         4\n",
-        "         10       0.00      0.00      0.00         2\n",
-        "         11       1.00      0.33      0.50         3\n",
+        "          1       0.50      0.50      0.50         4\n",
+        "         10       1.00      1.00      1.00         2\n",
+        "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
         "          3       0.00      0.00      0.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
-        "          5       1.00      0.50      0.67         2\n",
+        "          4       0.80      1.00      0.89         4\n",
+        "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
-        "          9       0.60      1.00      0.75         3\n",
+        "          8       1.00      0.75      0.86         4\n",
+        "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.71      0.68      0.64        31\n",
+        "avg / total       0.78      0.77      0.75        31\n",
         "\n",
-        "[[4 0 0 0 0 0 0 0 0 0 0]\n",
-        " [1 0 0 0 0 0 0 0 0 1 0]\n",
-        " [2 0 1 0 0 0 0 0 0 0 0]\n",
+        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
+        " [0 2 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 0 2]\n",
+        " [2 0 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
-        " [1 0 0 0 0 0 1 0 0 0 0]\n",
+        " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.50      0.25      0.33         4\n",
+        "          1       0.50      0.50      0.50         4\n",
         "         10       1.00      1.00      1.00         2\n",
-        "         11       0.50      1.00      0.67         3\n",
+        "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
         "          3       0.00      0.00      0.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
-        "          5       1.00      0.50      0.67         2\n",
+        "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.60      0.75      0.67         4\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.75      0.71      0.69        31\n",
+        "avg / total       0.81      0.77      0.76        31\n",
         "\n",
-        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
+        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [1 0 0 0 0 0 0 0 0 1 0]\n",
+        " [2 0 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
-        " [0 0 1 0 0 0 1 0 0 0 0]\n",
+        " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
         " [0 0 0 0 1 0 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       1.00      0.25      0.40         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
+        "          3       0.50      0.50      0.50         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.50      1.00      0.67         1\n",
-        "          7       1.00      0.67      0.80         3\n",
+        "          6       0.33      1.00      0.50         1\n",
+        "          7       1.00      0.33      0.50         3\n",
         "          8       0.75      0.75      0.75         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.89      0.84      0.82        31\n",
+        "avg / total       0.88      0.81      0.80        31\n"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
+       "text": [
         "\n",
-        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
+        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 2 0 0 0 0 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 1 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 1 2 0 0]\n",
+        " [0 0 0 0 0 0 0 2 1 0 0]\n",
         " [0 0 0 0 1 0 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       1.00      0.50      0.67         4\n",
+        "          1       0.50      0.50      0.50         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
         "          3       0.00      0.00      0.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.50      1.00      0.67         1\n",
-        "          7       1.00      0.67      0.80         3\n",
-        "          8       0.60      0.75      0.67         4\n",
+        "          6       0.33      1.00      0.50         1\n",
+        "          7       1.00      0.33      0.50         3\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.83      0.81      0.80        31\n"
-       ]
-      },
-      {
-       "output_type": "stream",
-       "stream": "stderr",
-       "text": [
-        "/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py:1771: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n",
-        "  'precision', 'predicted', average, warn_for)\n",
-        "/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py:1771: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples.\n",
-        "  'precision', 'predicted', average, warn_for)\n",
-        "/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py:1771: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n",
-        "  'precision', 'predicted', average, warn_for)\n"
-       ]
-      },
-      {
-       "output_type": "stream",
-       "stream": "stdout",
-       "text": [
-        "\n",
-        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
-        " [0 2 0 0 0 0 0 0 0 0 0]\n",
-        " [0 0 3 0 0 0 0 0 0 0 0]\n",
-        " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 2 0]\n",
-        " [0 0 0 0 0 4 0 0 0 0 0]\n",
-        " [0 0 0 0 0 0 2 0 0 0 0]\n",
-        " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 1 2 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
-        " [0 0 0 0 0 0 0 0 0 0 3]]\n",
-        "             precision    recall  f1-score   support\n",
-        "\n",
-        "          1       0.67      0.50      0.57         4\n",
-        "         10       1.00      1.00      1.00         2\n",
-        "         11       0.50      0.67      0.57         3\n",
-        "          2       1.00      1.00      1.00         3\n",
-        "          3       0.50      0.50      0.50         2\n",
-        "          4       1.00      1.00      1.00         4\n",
-        "          5       1.00      1.00      1.00         2\n",
-        "          6       0.25      1.00      0.40         1\n",
-        "          7       0.00      0.00      0.00         3\n",
-        "          8       0.75      0.75      0.75         4\n",
-        "          9       0.67      0.67      0.67         3\n",
-        "\n",
-        "avg / total       0.69      0.71      0.69        31\n",
-        "\n",
-        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
-        " [0 2 0 0 0 0 0 0 0 0 0]\n",
-        " [1 0 2 0 0 0 0 0 0 0 0]\n",
-        " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 0 1]\n",
-        " [0 0 0 0 0 4 0 0 0 0 0]\n",
-        " [0 0 0 0 0 0 2 0 0 0 0]\n",
-        " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 3 0 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
-        " [0 0 0 0 0 0 0 0 0 1 2]]\n",
-        "             precision    recall  f1-score   support\n",
-        "\n",
-        "          1       0.50      0.50      0.50         4\n",
-        "         10       1.00      0.50      0.67         2\n",
-        "         11       0.60      1.00      0.75         3\n",
-        "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
-        "          5       1.00      1.00      1.00         2\n",
-        "          6       0.33      1.00      0.50         1\n",
-        "          7       1.00      0.67      0.80         3\n",
-        "          8       1.00      0.75      0.86         4\n",
-        "          9       1.00      1.00      1.00         3\n",
-        "\n",
-        "avg / total       0.81      0.77      0.77        31\n",
-        "\n",
-        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
-        " [0 1 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 3 0 0 0 0 0 0 0 0]\n",
-        " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [2 0 0 0 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 0 4 0 0 0 0 0]\n",
-        " [0 0 0 0 0 0 2 0 0 0 0]\n",
-        " [0 0 0 0 0 0 0 1 0 0 0]\n",
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-        "             precision    recall  f1-score   support\n",
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         "\n",
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@@ -3639,27 +2545,21 @@
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-        "          8       1.00      0.75      0.86         4\n",
+        "          8       0.60      0.75      0.67         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
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         "\n",
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@@ -3672,15 +2572,15 @@
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         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
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         "          4       1.00      1.00      1.00         4\n",
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+        "          8       0.75      0.75      0.75         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.88      0.81      0.80        31\n"
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@@ -3705,15 +2605,15 @@
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         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
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         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       1.00      0.75      0.86         4\n",
+        "          8       0.60      0.75      0.67         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.82      0.77      0.76        31\n"
        ]
       },
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@@ -3725,7 +2625,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
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         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -3734,7 +2634,7 @@
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.50      0.50      0.50         4\n",
+        "          1       0.50      0.25      0.33         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
@@ -3743,43 +2643,22 @@
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       1.00      0.75      0.86         4\n",
+        "          8       0.60      0.75      0.67         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.81      0.77      0.76        31\n"
-       ]
-      },
-      {
-       "output_type": "stream",
-       "stream": "stdout",
-       "text": [
+        "avg / total       0.76      0.74      0.72        31\n",
         "\n",
-        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
+        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
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         " [0 0 0 0 0 0 0 2 1 0 0]\n",
         " [0 0 0 0 1 0 0 0 0 3 0]\n",
-        " [0 0 0 0 0 0 0 0 0 0 3]]\n",
-        "             precision    recall  f1-score   support\n",
-        "\n",
-        "          1       1.00      0.25      0.40         4\n",
-        "         10       1.00      1.00      1.00         2\n",
-        "         11       0.60      1.00      0.75         3\n",
-        "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
-        "          5       1.00      1.00      1.00         2\n",
-        "          6       0.50      1.00      0.67         1\n",
-        "          7       1.00      0.67      0.80         3\n",
-        "          8       0.75      0.75      0.75         4\n",
-        "          9       1.00      1.00      1.00         3\n",
-        "\n",
-        "avg / total       0.89      0.84      0.82        31\n"
+        " [0 0 0 0 0 0 0 0 0 0 3]]"
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@@ -3787,98 +2666,33 @@
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-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
-        " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
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         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
-        "          5       1.00      1.00      1.00         2\n",
-        "          6       0.33      1.00      0.50         1\n",
-        "          7       1.00      0.33      0.50         3\n",
-        "          8       1.00      0.75      0.86         4\n",
-        "          9       1.00      1.00      1.00         3\n",
-        "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
-       ]
-      },
-      {
-       "output_type": "stream",
-       "stream": "stdout",
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-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
-        " [0 0 0 0 0 0 0 0 0 0 3]]\n",
-        "             precision    recall  f1-score   support\n",
-        "\n",
-        "          1       0.67      0.50      0.57         4\n",
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-        "         11       0.60      1.00      0.75         3\n",
-        "          2       1.00      1.00      1.00         3\n",
         "          3       0.50      0.50      0.50         2\n",
         "          4       1.00      1.00      1.00         4\n",
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         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          9       0.75      1.00      0.86         3\n",
         "\n",
-        "avg / total       0.86      0.81      0.81        31\n"
-       ]
-      },
-      {
-       "output_type": "stream",
-       "stream": "stdout",
-       "text": [
+        "avg / total       0.88      0.81      0.80        31\n",
         "\n",
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         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
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         " [0 0 0 0 0 0 0 2 1 0 0]\n",
         " [0 0 0 0 1 0 0 0 0 3 0]\n",
-        " [0 0 0 0 0 0 0 0 0 0 3]]\n",
-        "             precision    recall  f1-score   support\n",
-        "\n",
-        "          1       1.00      0.50      0.67         4\n",
-        "         10       1.00      1.00      1.00         2\n",
-        "         11       0.60      1.00      0.75         3\n",
-        "          2       1.00      1.00      1.00         3\n",
-        "          3       0.50      0.50      0.50         2\n",
-        "          4       1.00      1.00      1.00         4\n",
-        "          5       1.00      1.00      1.00         2\n",
-        "          6       0.33      1.00      0.50         1\n",
-        "          7       1.00      0.33      0.50         3\n",
-        "          8       1.00      0.75      0.86         4\n",
-        "          9       0.75      1.00      0.86         3\n",
-        "\n",
-        "avg / total       0.88      0.81      0.80        31\n"
+        " [0 0 0 0 0 0 0 0 0 0 3]]"
        ]
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       {
@@ -3886,17 +2700,6 @@
        "stream": "stdout",
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-        " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 0 1]\n",
-        " [0 0 0 0 0 4 0 0 0 0 0]\n",
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-        " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
-        " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
         "          1       1.00      0.50      0.67         4\n",
@@ -3941,8 +2744,8 @@
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          8       1.00      0.75      0.86         4\n",
+        "          9       0.75      1.00      0.86         3\n",
         "\n",
         "avg / total       0.88      0.81      0.80        31\n"
        ]
@@ -3956,7 +2759,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 1 0]\n",
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         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -3965,17 +2768,17 @@
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.50      0.25      0.33         4\n",
+        "          1       0.67      0.50      0.57         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.50      0.50      0.50         2\n",
+        "          3       0.00      0.00      0.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          8       1.00      0.75      0.86         4\n",
+        "          9       0.75      1.00      0.86         3\n",
         "\n",
         "avg / total       0.81      0.77      0.76        31\n"
        ]
@@ -3985,11 +2788,11 @@
        "stream": "stdout",
        "text": [
         "\n",
-        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
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@@ -3998,11 +2801,11 @@
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         "             precision    recall  f1-score   support\n",
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-        "          1       1.00      0.50      0.67         4\n",
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         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
+        "          3       0.00      0.00      0.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
@@ -4010,7 +2813,7 @@
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.81      0.77      0.76        31\n"
        ]
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@@ -4022,7 +2825,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
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         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4101,15 +2904,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
+        "          3       0.00      0.00      0.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          9       0.60      1.00      0.75         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.84      0.77      0.76        31\n"
        ]
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@@ -4121,7 +2924,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
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         " [0 0 0 3 0 0 0 0 0 0 0]\n",
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         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4130,19 +2933,19 @@
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.67      0.50      0.57         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.50      0.50      0.50         2\n",
+        "          3       0.00      0.00      0.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.50      1.00      0.67         1\n",
         "          7       1.00      0.67      0.80         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          9       0.60      1.00      0.75         3\n",
         "\n",
-        "avg / total       0.87      0.84      0.84        31\n"
+        "avg / total       0.84      0.81      0.80        31\n"
        ]
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@@ -4154,7 +2957,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
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         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4167,15 +2970,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.50      0.50      0.50         2\n",
+        "          3       0.00      0.00      0.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       1.00      0.75      0.86         4\n",
+        "          8       0.75      0.75      0.75         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.86      0.81      0.81        31\n"
+        "avg / total       0.80      0.77      0.76        31\n"
        ]
       },
       {
@@ -4187,7 +2990,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
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         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4196,19 +2999,19 @@
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.50      0.50      0.50         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
+        "          3       0.50      0.50      0.50         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       1.00      0.75      0.86         4\n",
+        "          8       0.75      0.75      0.75         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.81      0.77      0.76        31\n"
+        "avg / total       0.88      0.81      0.80        31\n"
        ]
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@@ -4220,7 +3023,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
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         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4229,11 +3032,11 @@
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.67      0.50      0.57         4\n",
+        "          1       0.50      0.50      0.50         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.50      0.50      0.50         2\n",
+        "          3       0.00      0.00      0.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
@@ -4241,7 +3044,7 @@
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.86      0.81      0.81        31\n"
+        "avg / total       0.81      0.77      0.76        31\n"
        ]
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@@ -4253,7 +3056,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
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         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4266,15 +3069,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
+        "          3       0.00      0.00      0.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       1.00      0.75      0.86         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          8       0.75      0.75      0.75         4\n",
+        "          9       0.75      1.00      0.86         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.82      0.77      0.76        31\n"
        ]
       },
       {
@@ -4286,7 +3089,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 2 0 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 0 0 1 1]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4295,19 +3098,19 @@
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       1.00      0.50      0.67         4\n",
+        "          1       0.67      0.50      0.57         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
+        "          3       0.00      0.00      0.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       1.00      0.75      0.86         4\n",
+        "          8       0.75      0.75      0.75         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.80      0.77      0.76        31\n"
        ]
       },
       {
@@ -4319,7 +3122,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 2 0 0 0 0 0 0]\n",
+        " [1 0 0 0 0 0 0 0 0 1 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4361,19 +3164,19 @@
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       1.00      0.50      0.67         4\n",
+        "          1       0.50      0.50      0.50         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.50      0.50      0.50         2\n",
+        "          3       0.00      0.00      0.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.88      0.81      0.80        31\n"
+        "avg / total       0.81      0.77      0.76        31\n"
        ]
       },
       {
@@ -4385,7 +3188,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 1 0]\n",
+        " [2 0 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4394,19 +3197,19 @@
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       1.00      0.50      0.67         4\n",
+        "          1       0.67      0.50      0.57         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
+        "          3       0.00      0.00      0.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       1.00      0.75      0.86         4\n",
+        "          8       0.75      0.75      0.75         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.80      0.77      0.76        31\n"
        ]
       },
       {
@@ -4418,7 +3221,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 2 0 0 0 0 0 0]\n",
+        " [1 0 0 0 0 0 0 0 0 1 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4427,7 +3230,7 @@
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.50      0.50      0.50         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
@@ -4437,9 +3240,9 @@
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          9       0.60      1.00      0.75         3\n",
         "\n",
-        "avg / total       0.81      0.77      0.76        31\n"
+        "avg / total       0.84      0.77      0.76        31\n"
        ]
       },
       {
@@ -4451,7 +3254,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [2 0 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 2]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4460,19 +3263,19 @@
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       1.00      0.25      0.40         4\n",
+        "          1       0.50      0.50      0.50         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
+        "          3       0.00      0.00      0.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.89      0.81      0.79        31\n"
+        "avg / total       0.81      0.77      0.76        31\n"
        ]
       },
       {
@@ -4480,11 +3283,11 @@
        "stream": "stdout",
        "text": [
         "\n",
-        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
+        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 2 0 0 0 0 0 0]\n",
+        " [2 0 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4493,7 +3296,7 @@
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.50      0.50      0.50         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
@@ -4503,9 +3306,9 @@
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          9       0.60      1.00      0.75         3\n",
         "\n",
-        "avg / total       0.81      0.77      0.76        31\n"
+        "avg / total       0.84      0.77      0.76        31\n"
        ]
       },
       {
@@ -4517,7 +3320,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [2 0 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 2]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4530,15 +3333,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.50      0.50      0.50         2\n",
+        "          3       0.67      1.00      0.80         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.88      0.81      0.80        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -4550,7 +3353,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 1 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4563,15 +3366,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
+        "          3       0.67      1.00      0.80         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.60      0.75      0.67         4\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.82      0.77      0.76        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -4583,7 +3386,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 2 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4596,15 +3399,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
+        "          3       0.50      0.50      0.50         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          9       0.75      1.00      0.86         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.88      0.81      0.80        31\n"
        ]
       },
       {
@@ -4616,7 +3419,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 2 0 0 0 0 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 0 1]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4667,10 +3470,10 @@
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.60      0.75      0.67         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          8       1.00      0.75      0.86         4\n",
+        "          9       0.60      1.00      0.75         3\n",
         "\n",
-        "avg / total       0.82      0.77      0.76        31\n"
+        "avg / total       0.84      0.77      0.76        31\n"
        ]
       },
       {
@@ -4682,7 +3485,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 2 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 2]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4691,19 +3494,19 @@
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.67      0.50      0.57         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.50      0.50      0.50         2\n",
+        "          3       0.00      0.00      0.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          9       0.60      1.00      0.75         3\n",
         "\n",
-        "avg / total       0.86      0.81      0.81        31\n"
+        "avg / total       0.84      0.77      0.76        31\n"
        ]
       },
       {
@@ -4715,7 +3518,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [1 0 0 0 1 0 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 2]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4761,15 +3564,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
+        "          3       0.00      0.00      0.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          9       0.60      1.00      0.75         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.84      0.77      0.76        31\n"
        ]
       },
       {
@@ -4781,7 +3584,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 2 0 0 0 0 0 0]\n",
+        " [0 0 0 0 0 0 0 0 0 0 2]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4794,15 +3597,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
+        "          3       0.50      0.50      0.50         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.80      0.77      0.76        31\n"
+        "avg / total       0.86      0.81      0.81        31\n"
        ]
       },
       {
@@ -4814,7 +3617,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [1 0 0 0 0 0 0 0 0 1 0]\n",
+        " [1 0 0 0 1 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -4860,15 +3663,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.50      0.50      0.50         2\n",
+        "          3       0.67      1.00      0.80         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.88      0.81      0.80        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -4880,7 +3683,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 1 0]\n",
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         "\n",
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         "          9       1.00      1.00      1.00         3\n",
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@@ -5033,7 +3836,7 @@
         "          8       0.75      0.75      0.75         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
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@@ -5054,11 +3857,11 @@
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@@ -5066,7 +3869,7 @@
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
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@@ -5078,7 +3881,7 @@
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@@ -5120,7 +3923,7 @@
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         "          2       1.00      1.00      1.00         3\n",
@@ -5129,10 +3932,10 @@
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         "\n",
-        "avg / total       0.82      0.77      0.76        31\n"
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@@ -5140,11 +3943,11 @@
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@@ -5157,15 +3960,15 @@
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         "\n",
-        "avg / total       0.89      0.84      0.84        31\n"
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-        "\n",
-        "avg / total       0.81      0.77      0.76        31\n"
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@@ -5256,6 +4026,8 @@
        "output_type": "stream",
        "stream": "stderr",
        "text": [
+        "/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py:1771: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n",
+        "  'precision', 'predicted', average, warn_for)\n",
         "/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py:1771: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples.\n",
         "  'precision', 'predicted', average, warn_for)\n"
        ]
@@ -5263,107 +4035,62 @@
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pbAYMLYHo2YJRhp8HeAG/x5+NiR0kOVZxP7xa4mAev2mMvVqx9yEcRkrxBjGj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\nOXmLIAjiWiHO8JcAbAmv+5b8I/JWAN/WNO30ANs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N161RTNQ6ftSmbT4rQhDGV9KpLRbQ6Q5wkpDsldHymcU6DX4645xNOUqUiYaa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\nzAkU8AmCIOaE/x8Ys6GoNREgGQAAAABJRU5ErkJggg==\n",
        "text": [
-        "<matplotlib.figure.Figure at 0x10b316c18>"
+        "<matplotlib.figure.Figure at 0x10827a828>"
        ]
       }
      ],
-     "prompt_number": 18
+     "prompt_number": 14
     },
     {
      "cell_type": "heading",
      "level": 1,
      "metadata": {},
      "source": [
-      "Pass in code file for response"
+      "Pass in any file of code"
      ]
     },
     {
@@ -5405,14 +4132,78 @@
       "    reversed_dict = dict((v,k) for k,v in a_dictionary.items())\n",
       "    return [(reversed_dict.get(x),y) for x,y in a_list]\n",
       "\n",
-      "def check_code_snippet(a_file, corp_train, corp_answer):\n",
+      "def check_code_file(a_file, corp_train, corp_answer):\n",
       "    \n",
       "    # Ingest and featurizes file\n",
       "    request = Corpus([a_file])\n",
       "    request_df = request.compl_df_build()\n",
       "\n",
       "    # Run model\n",
-      "    model_created = GaussianNB()\n",
+      "    model_created = RandomForestClassifier(50)\n",
+      "    model_created.fit(corp_train, corp_answer)\n",
+      "    predicted = model_created.predict(request_df.values)\n",
+      "    predict_prob = model_created.predict_proba(request_df.values)\n",
+      "    \n",
+      "    #Pretty response\n",
+      "    answer_list = list(zip(model_created.classes_, predict_prob[0]))\n",
+      "    answer_list.sort(key=lambda x: x[1], reverse=True)\n",
+      "    return reverse_dict_match(hit_num, answer_list)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 31
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "check_code_file('test/22', corp_train, corp_answer)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 28,
+       "text": [
+        "[('ruby', 0.26000000000000001),\n",
+        " ('java', 0.16),\n",
+        " ('python', 0.16),\n",
+        " ('clojure', 0.14000000000000001),\n",
+        " ('scheme', 0.10000000000000001),\n",
+        " ('php', 0.059999999999999998),\n",
+        " ('haskell', 0.040000000000000001),\n",
+        " ('javascript', 0.040000000000000001),\n",
+        " ('perl', 0.040000000000000001),\n",
+        " ('scala', 0.0),\n",
+        " ('ocaml', 0.0)]"
+       ]
+      }
+     ],
+     "prompt_number": 28
+    },
+    {
+     "cell_type": "heading",
+     "level": 1,
+     "metadata": {},
+     "source": [
+      "Pass in any code snippet"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "def check_code_snippet(code_snippet, corp_train, corp_answer):\n",
+      "    request = Corpus()\n",
+      "    code_snippet_df = pd.DataFrame(code_snippet, columns=['raw_text'])\n",
+      "    code_snippet_df = request.feature_breakout(code_snippet_df)\n",
+      "    request_df = request.clean_df(code_snippet_df, snippet='True')\n",
+      "\n",
+      "    # Run model\n",
+      "    model_created = RandomForestClassifier(50)\n",
       "    model_created.fit(corp_train, corp_answer)\n",
       "    predicted = model_created.predict(request_df.values)\n",
       "    predict_prob = model_created.predict_proba(request_df.values)\n",
@@ -5425,13 +4216,21 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 7
+     "prompt_number": 34
     },
     {
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "check_code_snippet('test/22', corp_train, corp_answer)"
+      "ocaml = \"\"\"| pid ->\n",
+      "      Unix.close output;\n",
+      "      let input = Unix.in_channel_of_descr input in fun () ->\n",
+      "        let v = Marshal.from_channel input in\n",
+      "        ignore (Unix.waitpid [] pid);\n",
+      "        close_in input;\n",
+      "        match v with `Res x -> x | `Exn e -> raise e\"\"\"\n",
+      "\n",
+      "check_code_snippet([ocaml], corp_train, corp_answer)"
      ],
      "language": "python",
      "metadata": {},
@@ -5439,23 +4238,23 @@
       {
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 8,
+       "prompt_number": 33,
        "text": [
-        "[('javascript', 1.0),\n",
-        " ('java', 2.7703304550449276e-81),\n",
-        " ('clojure', 0.0),\n",
+        "[('ocaml', 0.73999999999999999),\n",
+        " ('clojure', 0.10000000000000001),\n",
+        " ('scheme', 0.059999999999999998),\n",
+        " ('python', 0.059999999999999998),\n",
+        " ('haskell', 0.02),\n",
+        " ('java', 0.02),\n",
         " ('scala', 0.0),\n",
-        " ('scheme', 0.0),\n",
-        " ('haskell', 0.0),\n",
-        " ('ocaml', 0.0),\n",
+        " ('javascript', 0.0),\n",
         " ('perl', 0.0),\n",
         " ('php', 0.0),\n",
-        " ('python', 0.0),\n",
         " ('ruby', 0.0)]"
        ]
       }
      ],
-     "prompt_number": 8
+     "prompt_number": 33
     },
     {
      "cell_type": "code",
@@ -5463,7 +4262,8 @@
      "input": [],
      "language": "python",
      "metadata": {},
-     "outputs": []
+     "outputs": [],
+     "prompt_number": 16
     },
     {
      "cell_type": "code",
@@ -5471,7 +4271,8 @@
      "input": [],
      "language": "python",
      "metadata": {},
-     "outputs": []
+     "outputs": [],
+     "prompt_number": 16
     },
     {
      "cell_type": "code",
@@ -5479,7 +4280,8 @@
      "input": [],
      "language": "python",
      "metadata": {},
-     "outputs": []
+     "outputs": [],
+     "prompt_number": 16
     },
     {
      "cell_type": "code",
@@ -5487,7 +4289,8 @@
      "input": [],
      "language": "python",
      "metadata": {},
-     "outputs": []
+     "outputs": [],
+     "prompt_number": 16
     },
     {
      "cell_type": "code",
@@ -5495,7 +4298,8 @@
      "input": [],
      "language": "python",
      "metadata": {},
-     "outputs": []
+     "outputs": [],
+     "prompt_number": 16
     }
    ],
    "metadata": {}

From 0628242b4ed37f49fbb80723d4a2e60d8e1ff4c8 Mon Sep 17 00:00:00 2001
From: Zack Cooper <zackjcooper@gmail.com>
Date: Mon, 16 Feb 2015 08:51:58 -0500
Subject: [PATCH 5/6] again

---
 lang classifier live.ipynb | 3052 +++++++-----------------------------
 1 file changed, 565 insertions(+), 2487 deletions(-)

diff --git a/lang classifier live.ipynb b/lang classifier live.ipynb
index 3b16179..d9ebd8b 100644
--- a/lang classifier live.ipynb	
+++ b/lang classifier live.ipynb	
@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:351106de656a94ded25f92477ba635151dc3e3be72b67d7f2d9459b9b4fb2be8"
+  "signature": "sha256:5d38ae2fb3758ef4f48e8df732eaeef65eb86124e67ec22c3c221b664a5301d2"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -27,7 +27,7 @@
       "\n",
       "corpus = Corpus(raw_file_list)\n",
       "corpus_df = corpus.compl_df_build(False)\n",
-      "corpus_df"
+      "corpus_df.head()"
      ],
      "language": "python",
      "metadata": {},
@@ -56,2091 +56,292 @@
         "      <th>val_exists</th>\n",
         "      <th>else_if</th>\n",
         "      <th>elif</th>\n",
+        "      <th>void</th>\n",
         "    </tr>\n",
         "  </thead>\n",
         "  <tbody>\n",
         "    <tr>\n",
-        "      <th>0  </th>\n",
-        "      <td>  1</td>\n",
+        "      <th>0</th>\n",
+        "      <td> 1</td>\n",
         "      <td> 0.071901</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.002066</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.001240</td>\n",
         "      <td> 0.000413</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000413</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-        "      <th>1  </th>\n",
-        "      <td>  1</td>\n",
+        "      <th>1</th>\n",
+        "      <td> 1</td>\n",
         "      <td> 0.071704</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.002699</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000771</td>\n",
         "      <td> 0.000386</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000386</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-        "      <th>2  </th>\n",
-        "      <td>  1</td>\n",
+        "      <th>2</th>\n",
+        "      <td> 1</td>\n",
         "      <td> 0.063995</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.002695</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000337</td>\n",
         "      <td> 0.000337</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000337</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000337</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-        "      <th>3  </th>\n",
-        "      <td>  2</td>\n",
+        "      <th>3</th>\n",
+        "      <td> 2</td>\n",
         "      <td> 0.024707</td>\n",
         "      <td> 0.002471</td>\n",
         "      <td> 0.002471</td>\n",
         "      <td> 0.000618</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000618</td>\n",
-        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.001235</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-        "      <th>4  </th>\n",
-        "      <td>  2</td>\n",
+        "      <th>4</th>\n",
+        "      <td> 2</td>\n",
         "      <td> 0.024352</td>\n",
         "      <td> 0.002118</td>\n",
         "      <td> 0.002647</td>\n",
         "      <td> 0.000529</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.001059</td>\n",
-        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000529</td>\n",
-        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.001059</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>5  </th>\n",
-        "      <td>  2</td>\n",
-        "      <td> 0.026361</td>\n",
-        "      <td> 0.002292</td>\n",
-        "      <td> 0.002865</td>\n",
-        "      <td> 0.000573</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001146</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000573</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001146</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>6  </th>\n",
-        "      <td>  3</td>\n",
-        "      <td> 0.028487</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000982</td>\n",
-        "      <td> 0.015226</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000246</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>7  </th>\n",
-        "      <td>  3</td>\n",
-        "      <td> 0.032197</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.010417</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000947</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001420</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>8  </th>\n",
-        "      <td>  3</td>\n",
-        "      <td> 0.029671</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.012981</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000464</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>9  </th>\n",
-        "      <td>  4</td>\n",
-        "      <td> 0.038012</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.010234</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000731</td>\n",
-        "      <td> 0.006579</td>\n",
-        "      <td> 0.002193</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002193</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>10 </th>\n",
-        "      <td>  9</td>\n",
-        "      <td> 0.025682</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004815</td>\n",
-        "      <td> 0.001605</td>\n",
-        "      <td> 0.003210</td>\n",
-        "      <td> 0.011236</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000803</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>11 </th>\n",
-        "      <td>  9</td>\n",
-        "      <td> 0.022440</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004208</td>\n",
-        "      <td> 0.001403</td>\n",
-        "      <td> 0.003506</td>\n",
-        "      <td> 0.009818</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000701</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>12 </th>\n",
-        "      <td>  9</td>\n",
-        "      <td> 0.026920</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004751</td>\n",
-        "      <td> 0.001584</td>\n",
-        "      <td> 0.004751</td>\n",
-        "      <td> 0.011085</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000792</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>13 </th>\n",
-        "      <td>  9</td>\n",
-        "      <td> 0.023955</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002178</td>\n",
-        "      <td> 0.002395</td>\n",
-        "      <td> 0.006533</td>\n",
-        "      <td> 0.006969</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000218</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>14 </th>\n",
-        "      <td>  5</td>\n",
-        "      <td> 0.025814</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.012293</td>\n",
-        "      <td> 0.002459</td>\n",
-        "      <td> 0.001229</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000615</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001229</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>15 </th>\n",
-        "      <td>  5</td>\n",
-        "      <td> 0.034651</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.009773</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.003554</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000888</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000444</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>16 </th>\n",
-        "      <td>  5</td>\n",
-        "      <td> 0.033503</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.010925</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004370</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001457</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000728</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>17 </th>\n",
-        "      <td>  6</td>\n",
-        "      <td> 0.025354</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.007457</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000746</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.042506</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>18 </th>\n",
-        "      <td>  6</td>\n",
-        "      <td> 0.026679</td>\n",
-        "      <td> 0.000953</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.013340</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000476</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.037637</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "    </tr>\n",
-        "    <tr>\n",
-        "      <th>19 </th>\n",
-        "      <td>  7</td>\n",
-        "      <td> 0.036755</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.006337</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001267</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.046261</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>20 </th>\n",
-        "      <td>  7</td>\n",
-        "      <td> 0.034674</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.008322</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000693</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.041609</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>21 </th>\n",
-        "      <td>  7</td>\n",
-        "      <td> 0.040650</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.005420</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000678</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.044038</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>22 </th>\n",
-        "      <td>  7</td>\n",
-        "      <td> 0.038144</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.013402</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002835</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.057474</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000258</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>23 </th>\n",
-        "      <td>  8</td>\n",
-        "      <td> 0.044543</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002784</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.007795</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000557</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001670</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>24 </th>\n",
-        "      <td> 11</td>\n",
-        "      <td> 0.104895</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002914</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001166</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000583</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004662</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>25 </th>\n",
-        "      <td> 11</td>\n",
-        "      <td> 0.095606</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.003380</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000483</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000483</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001449</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>26 </th>\n",
-        "      <td> 11</td>\n",
-        "      <td> 0.096643</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001107</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000738</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000369</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000738</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>27 </th>\n",
-        "      <td> 10</td>\n",
-        "      <td> 0.036036</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004505</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.015444</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000644</td>\n",
-        "      <td> 0.000644</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.003218</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002574</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>28 </th>\n",
-        "      <td> 10</td>\n",
-        "      <td> 0.048632</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.003647</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.013374</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001216</td>\n",
-        "      <td> 0.001216</td>\n",
-        "      <td> 0.002432</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004863</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>29 </th>\n",
-        "      <td> 10</td>\n",
-        "      <td> 0.035115</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.003053</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.015267</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000763</td>\n",
-        "      <td> 0.001527</td>\n",
-        "      <td> 0.002290</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004580</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.003053</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>...</th>\n",
-        "      <td>...</td>\n",
-        "      <td>...</td>\n",
-        "      <td>...</td>\n",
-        "      <td>...</td>\n",
-        "      <td>...</td>\n",
-        "      <td>...</td>\n",
-        "      <td>...</td>\n",
-        "      <td>...</td>\n",
-        "      <td>...</td>\n",
-        "      <td>...</td>\n",
-        "      <td>...</td>\n",
-        "      <td>...</td>\n",
-        "      <td>...</td>\n",
-        "      <td>...</td>\n",
-        "      <td>...</td>\n",
-        "      <td>...</td>\n",
-        "      <td>...</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>357</th>\n",
-        "      <td>  8</td>\n",
-        "      <td> 0.052632</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004848</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000693</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000693</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>358</th>\n",
-        "      <td>  8</td>\n",
-        "      <td> 0.044304</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.003956</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000791</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000791</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>359</th>\n",
-        "      <td>  8</td>\n",
-        "      <td> 0.036014</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.003001</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000600</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000600</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>360</th>\n",
-        "      <td> 11</td>\n",
-        "      <td> 0.090119</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002172</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000543</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>361</th>\n",
-        "      <td> 11</td>\n",
-        "      <td> 0.085551</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001901</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000475</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>362</th>\n",
-        "      <td> 11</td>\n",
-        "      <td> 0.108160</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.003863</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000483</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>363</th>\n",
-        "      <td> 10</td>\n",
-        "      <td> 0.063545</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000836</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002508</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.015050</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.003344</td>\n",
-        "      <td> 0.004181</td>\n",
-        "      <td> 0.000836</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.003344</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>364</th>\n",
-        "      <td> 10</td>\n",
-        "      <td> 0.041924</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001644</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002877</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.013152</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000411</td>\n",
-        "      <td> 0.003288</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004110</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>365</th>\n",
-        "      <td> 10</td>\n",
-        "      <td> 0.042079</td>\n",
-        "      <td> 0.000495</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000248</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002475</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.008911</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004950</td>\n",
-        "      <td> 0.002475</td>\n",
-        "      <td> 0.001238</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.003465</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>366</th>\n",
-        "      <td> 10</td>\n",
-        "      <td> 0.042163</td>\n",
-        "      <td> 0.000687</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000458</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002521</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.009166</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004812</td>\n",
-        "      <td> 0.002521</td>\n",
-        "      <td> 0.001146</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.003208</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>367</th>\n",
-        "      <td>  1</td>\n",
-        "      <td> 0.053812</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001794</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000897</td>\n",
-        "      <td> 0.001794</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000897</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>368</th>\n",
-        "      <td>  1</td>\n",
-        "      <td> 0.050473</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004206</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001052</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>369</th>\n",
-        "      <td>  2</td>\n",
-        "      <td> 0.016092</td>\n",
-        "      <td> 0.001149</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.005747</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001149</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001149</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>370</th>\n",
-        "      <td>  3</td>\n",
-        "      <td> 0.028712</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.014356</td>\n",
-        "      <td> 0.000449</td>\n",
-        "      <td> 0.002692</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>371</th>\n",
-        "      <td>  3</td>\n",
-        "      <td> 0.028812</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.013205</td>\n",
-        "      <td> 0.000600</td>\n",
-        "      <td> 0.004802</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>372</th>\n",
-        "      <td>  3</td>\n",
-        "      <td> 0.020844</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.012710</td>\n",
-        "      <td> 0.000254</td>\n",
-        "      <td> 0.000763</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>373</th>\n",
-        "      <td>  3</td>\n",
-        "      <td> 0.022556</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.015038</td>\n",
-        "      <td> 0.000752</td>\n",
-        "      <td> 0.000752</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>374</th>\n",
-        "      <td>  3</td>\n",
-        "      <td> 0.022871</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.013407</td>\n",
-        "      <td> 0.000394</td>\n",
-        "      <td> 0.001183</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>375</th>\n",
-        "      <td>  3</td>\n",
-        "      <td> 0.028786</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.010013</td>\n",
-        "      <td> 0.000626</td>\n",
-        "      <td> 0.002503</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>376</th>\n",
-        "      <td>  9</td>\n",
-        "      <td> 0.023939</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004353</td>\n",
-        "      <td> 0.010881</td>\n",
-        "      <td> 0.002176</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001088</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>377</th>\n",
-        "      <td>  9</td>\n",
-        "      <td> 0.003378</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.010135</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001689</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>378</th>\n",
-        "      <td>  5</td>\n",
-        "      <td> 0.063861</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.011611</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002903</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001451</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>379</th>\n",
-        "      <td>  5</td>\n",
-        "      <td> 0.056604</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.010613</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004717</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004717</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001179</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>380</th>\n",
-        "      <td>  5</td>\n",
-        "      <td> 0.054570</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.010914</td>\n",
-        "      <td> 0.001364</td>\n",
-        "      <td> 0.002729</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001364</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>381</th>\n",
-        "      <td>  6</td>\n",
-        "      <td> 0.034043</td>\n",
-        "      <td> 0.004255</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.017021</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001064</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.032979</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>382</th>\n",
-        "      <td>  6</td>\n",
-        "      <td> 0.012600</td>\n",
-        "      <td> 0.001260</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.011760</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000420</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.015960</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>383</th>\n",
-        "      <td>  8</td>\n",
-        "      <td> 0.035528</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001045</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001045</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001045</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001045</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>384</th>\n",
-        "      <td>  8</td>\n",
-        "      <td> 0.029233</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002436</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001218</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001218</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>385</th>\n",
-        "      <td> 11</td>\n",
-        "      <td> 0.080834</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.003911</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001304</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>386</th>\n",
-        "      <td> 10</td>\n",
-        "      <td> 0.033946</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002829</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.019802</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004243</td>\n",
-        "      <td> 0.001414</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004243</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "    </tr>\n",
-        "  </tbody>\n",
-        "</table>\n",
-        "<p>387 rows \u00d7 17 columns</p>\n",
-        "</div>"
-       ],
-       "metadata": {},
-       "output_type": "pyout",
-       "prompt_number": 9,
-       "text": [
-        "    hit_num  parent_count  double_colon  let_exists  less_minus  paren_star  \\\n",
-        "0         1      0.071901      0.000000    0.002066    0.000000    0.001240   \n",
-        "1         1      0.071704      0.000000    0.002699    0.000000    0.000771   \n",
-        "2         1      0.063995      0.000000    0.002695    0.000000    0.000337   \n",
-        "3         2      0.024707      0.002471    0.002471    0.000618    0.000000   \n",
-        "4         2      0.024352      0.002118    0.002647    0.000529    0.000000   \n",
-        "5         2      0.026361      0.002292    0.002865    0.000573    0.000000   \n",
-        "6         3      0.028487      0.000000    0.000000    0.000000    0.000000   \n",
-        "7         3      0.032197      0.000000    0.000000    0.000000    0.000000   \n",
-        "8         3      0.029671      0.000000    0.000000    0.000000    0.000000   \n",
-        "9         4      0.038012      0.000000    0.000000    0.000000    0.000000   \n",
-        "10        9      0.025682      0.000000    0.000000    0.000000    0.004815   \n",
-        "11        9      0.022440      0.000000    0.000000    0.000000    0.004208   \n",
-        "12        9      0.026920      0.000000    0.000000    0.000000    0.004751   \n",
-        "13        9      0.023955      0.000000    0.000000    0.000000    0.002178   \n",
-        "14        5      0.025814      0.000000    0.012293    0.002459    0.001229   \n",
-        "15        5      0.034651      0.000000    0.009773    0.000000    0.003554   \n",
-        "16        5      0.033503      0.000000    0.010925    0.000000    0.004370   \n",
-        "17        6      0.025354      0.000000    0.000000    0.000000    0.000000   \n",
-        "18        6      0.026679      0.000953    0.000000    0.000000    0.000000   \n",
-        "19        7      0.036755      0.000000    0.000000    0.000000    0.000000   \n",
-        "20        7      0.034674      0.000000    0.000000    0.000000    0.000000   \n",
-        "21        7      0.040650      0.000000    0.000000    0.000000    0.000000   \n",
-        "22        7      0.038144      0.000000    0.000000    0.000000    0.000000   \n",
-        "23        8      0.044543      0.000000    0.000000    0.000000    0.000000   \n",
-        "24       11      0.104895      0.000000    0.002914    0.000000    0.001166   \n",
-        "25       11      0.095606      0.000000    0.003380    0.000000    0.000483   \n",
-        "26       11      0.096643      0.000000    0.001107    0.000000    0.000738   \n",
-        "27       10      0.036036      0.000000    0.000000    0.000000    0.000000   \n",
-        "28       10      0.048632      0.000000    0.000000    0.000000    0.000000   \n",
-        "29       10      0.035115      0.000000    0.000000    0.000000    0.000000   \n",
-        "..      ...           ...           ...         ...         ...         ...   \n",
-        "357       8      0.052632      0.000000    0.000000    0.000000    0.000000   \n",
-        "358       8      0.044304      0.000000    0.000000    0.000000    0.000000   \n",
-        "359       8      0.036014      0.000000    0.000000    0.000000    0.000000   \n",
-        "360      11      0.090119      0.000000    0.002172    0.000000    0.000000   \n",
-        "361      11      0.085551      0.000000    0.001901    0.000000    0.000000   \n",
-        "362      11      0.108160      0.000000    0.003863    0.000000    0.000000   \n",
-        "363      10      0.063545      0.000000    0.000000    0.000836    0.000000   \n",
-        "364      10      0.041924      0.000000    0.000000    0.001644    0.000000   \n",
-        "365      10      0.042079      0.000495    0.000000    0.000248    0.000000   \n",
-        "366      10      0.042163      0.000687    0.000000    0.000458    0.000000   \n",
-        "367       1      0.053812      0.000000    0.001794    0.000000    0.000000   \n",
-        "368       1      0.050473      0.000000    0.000000    0.000000    0.000000   \n",
-        "369       2      0.016092      0.001149    0.000000    0.005747    0.000000   \n",
-        "370       3      0.028712      0.000000    0.000000    0.000000    0.000000   \n",
-        "371       3      0.028812      0.000000    0.000000    0.000000    0.000000   \n",
-        "372       3      0.020844      0.000000    0.000000    0.000000    0.000000   \n",
-        "373       3      0.022556      0.000000    0.000000    0.000000    0.000000   \n",
-        "374       3      0.022871      0.000000    0.000000    0.000000    0.000000   \n",
-        "375       3      0.028786      0.000000    0.000000    0.000000    0.000000   \n",
-        "376       9      0.023939      0.000000    0.000000    0.000000    0.000000   \n",
-        "377       9      0.003378      0.000000    0.000000    0.000000    0.000000   \n",
-        "378       5      0.063861      0.000000    0.011611    0.000000    0.002903   \n",
-        "379       5      0.056604      0.000000    0.010613    0.000000    0.004717   \n",
-        "380       5      0.054570      0.000000    0.010914    0.001364    0.002729   \n",
-        "381       6      0.034043      0.004255    0.000000    0.000000    0.000000   \n",
-        "382       6      0.012600      0.001260    0.000000    0.000000    0.000000   \n",
-        "383       8      0.035528      0.000000    0.000000    0.000000    0.000000   \n",
-        "384       8      0.029233      0.000000    0.000000    0.000000    0.000000   \n",
-        "385      11      0.080834      0.000000    0.003911    0.000000    0.000000   \n",
-        "386      10      0.033946      0.000000    0.000000    0.000000    0.000000   \n",
-        "\n",
-        "     def_exists  end_exists  curly_bracket  slash_star_star  forward_slash  \\\n",
-        "0      0.000413    0.000000       0.000000         0.000000       0.000413   \n",
-        "1      0.000386    0.000000       0.000000         0.000000       0.000386   \n",
-        "2      0.000337    0.000000       0.000000         0.000000       0.000337   \n",
-        "3      0.000000    0.000000       0.000000         0.000000       0.000618   \n",
-        "4      0.000000    0.000000       0.001059         0.000000       0.000529   \n",
-        "5      0.000000    0.000000       0.001146         0.000000       0.000573   \n",
-        "6      0.000000    0.000982       0.015226         0.000000       0.000246   \n",
-        "7      0.000000    0.000000       0.010417         0.000000       0.000947   \n",
-        "8      0.000000    0.000000       0.012981         0.000000       0.000464   \n",
-        "9      0.000000    0.000000       0.010234         0.000000       0.000731   \n",
-        "10     0.001605    0.003210       0.011236         0.000000       0.000803   \n",
-        "11     0.001403    0.003506       0.009818         0.000000       0.000701   \n",
-        "12     0.001584    0.004751       0.011085         0.000000       0.000792   \n",
-        "13     0.002395    0.006533       0.006969         0.000000       0.000218   \n",
-        "14     0.000000    0.000000       0.000000         0.000000       0.000615   \n",
-        "15     0.000000    0.000000       0.000888         0.000000       0.000444   \n",
-        "16     0.000000    0.000000       0.001457         0.000000       0.000728   \n",
-        "17     0.000000    0.000000       0.007457         0.000000       0.000746   \n",
-        "18     0.000000    0.000000       0.013340         0.000000       0.000476   \n",
-        "19     0.000000    0.000000       0.006337         0.000000       0.001267   \n",
-        "20     0.000000    0.000000       0.008322         0.000000       0.000693   \n",
-        "21     0.000000    0.000000       0.005420         0.000000       0.000678   \n",
-        "22     0.000000    0.000000       0.013402         0.000000       0.002835   \n",
-        "23     0.002784    0.000000       0.007795         0.000000       0.000557   \n",
-        "24     0.000000    0.000000       0.000000         0.000000       0.000583   \n",
-        "25     0.000000    0.000000       0.000000         0.000000       0.000483   \n",
-        "26     0.000000    0.000000       0.000000         0.000000       0.000369   \n",
-        "27     0.004505    0.000000       0.015444         0.000000       0.000644   \n",
-        "28     0.003647    0.000000       0.013374         0.000000       0.001216   \n",
-        "29     0.003053    0.000000       0.015267         0.000000       0.000763   \n",
-        "..          ...         ...            ...              ...            ...   \n",
-        "357    0.004848    0.000000       0.000000         0.000000       0.000693   \n",
-        "358    0.003956    0.000000       0.000000         0.000000       0.000791   \n",
-        "359    0.003001    0.000000       0.000000         0.000000       0.000600   \n",
-        "360    0.000000    0.000000       0.000000         0.000000       0.000543   \n",
-        "361    0.000000    0.000000       0.000000         0.000000       0.000475   \n",
-        "362    0.000000    0.000000       0.000000         0.000000       0.000483   \n",
-        "363    0.002508    0.000000       0.015050         0.000000       0.003344   \n",
-        "364    0.002877    0.000000       0.013152         0.000000       0.000411   \n",
-        "365    0.002475    0.000000       0.008911         0.000000       0.004950   \n",
-        "366    0.002521    0.000000       0.009166         0.000000       0.004812   \n",
-        "367    0.000000    0.000897       0.001794         0.000000       0.000897   \n",
-        "368    0.000000    0.000000       0.004206         0.000000       0.001052   \n",
-        "369    0.000000    0.000000       0.000000         0.000000       0.001149   \n",
-        "370    0.000000    0.000000       0.014356         0.000449       0.002692   \n",
-        "371    0.000000    0.000000       0.013205         0.000600       0.004802   \n",
-        "372    0.000000    0.000000       0.012710         0.000254       0.000763   \n",
-        "373    0.000000    0.000000       0.015038         0.000752       0.000752   \n",
-        "374    0.000000    0.000000       0.013407         0.000394       0.001183   \n",
-        "375    0.000000    0.000000       0.010013         0.000626       0.002503   \n",
-        "376    0.004353    0.010881       0.002176         0.000000       0.001088   \n",
-        "377    0.000000    0.010135       0.000000         0.000000       0.001689   \n",
-        "378    0.000000    0.000000       0.000000         0.000000       0.001451   \n",
-        "379    0.000000    0.000000       0.004717         0.000000       0.001179   \n",
-        "380    0.000000    0.000000       0.000000         0.000000       0.001364   \n",
-        "381    0.000000    0.000000       0.017021         0.000000       0.001064   \n",
-        "382    0.000000    0.000000       0.011760         0.000000       0.000420   \n",
-        "383    0.001045    0.000000       0.000000         0.000000       0.001045   \n",
-        "384    0.002436    0.000000       0.000000         0.000000       0.001218   \n",
-        "385    0.000000    0.000000       0.000000         0.000000       0.001304   \n",
-        "386    0.002829    0.000000       0.019802         0.000000       0.004243   \n",
-        "\n",
-        "     var_exists  star_count  dollar_sign  val_exists   else_if      elif  \n",
-        "0      0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "1      0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "2      0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "3      0.000000    0.001235     0.000000    0.000000  0.000000  0.000000  \n",
-        "4      0.000000    0.001059     0.000000    0.000000  0.000000  0.000000  \n",
-        "5      0.000000    0.001146     0.000000    0.000000  0.000000  0.000000  \n",
-        "6      0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "7      0.000000    0.001420     0.000000    0.000000  0.000000  0.000000  \n",
-        "8      0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "9      0.006579    0.002193     0.000000    0.000000  0.000000  0.002193  \n",
-        "10     0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "11     0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "12     0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "13     0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "14     0.000000    0.001229     0.000000    0.000000  0.000000  0.000000  \n",
-        "15     0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "16     0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "17     0.000000    0.000000     0.042506    0.000000  0.000000  0.000000  \n",
-        "18     0.000000    0.000000     0.037637    0.000000  0.000000  0.000000  \n",
-        "19     0.000000    0.000000     0.046261    0.000000  0.000000  0.000000  \n",
-        "20     0.000000    0.000000     0.041609    0.000000  0.000000  0.000000  \n",
-        "21     0.000000    0.000000     0.044038    0.000000  0.000000  0.000000  \n",
-        "22     0.000000    0.000000     0.057474    0.000000  0.000258  0.000000  \n",
-        "23     0.000000    0.000000     0.000000    0.000000  0.000000  0.001670  \n",
-        "24     0.000000    0.000000     0.000000    0.004662  0.000000  0.000000  \n",
-        "25     0.000000    0.000000     0.000000    0.001449  0.000000  0.000000  \n",
-        "26     0.000000    0.000000     0.000000    0.000738  0.000000  0.000000  \n",
-        "27     0.000644    0.000000     0.000000    0.003218  0.000000  0.002574  \n",
-        "28     0.001216    0.002432     0.000000    0.004863  0.000000  0.000000  \n",
-        "29     0.001527    0.002290     0.000000    0.004580  0.000000  0.003053  \n",
-        "..          ...         ...          ...         ...       ...       ...  \n",
-        "357    0.000000    0.000000     0.000000    0.000000  0.000000  0.000693  \n",
-        "358    0.000000    0.000000     0.000000    0.000000  0.000000  0.000791  \n",
-        "359    0.000000    0.000000     0.000000    0.000000  0.000000  0.000600  \n",
-        "360    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "361    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "362    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "363    0.004181    0.000836     0.000000    0.003344  0.000000  0.000000  \n",
-        "364    0.003288    0.000000     0.000000    0.004110  0.000000  0.000000  \n",
-        "365    0.002475    0.001238     0.000000    0.003465  0.000000  0.000000  \n",
-        "366    0.002521    0.001146     0.000000    0.003208  0.000000  0.000000  \n",
-        "367    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "368    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "369    0.000000    0.000000     0.001149    0.000000  0.000000  0.000000  \n",
-        "370    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "371    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "372    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "373    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "374    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "375    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "376    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "377    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "378    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "379    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "380    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "381    0.000000    0.000000     0.032979    0.000000  0.000000  0.000000  \n",
-        "382    0.000000    0.000000     0.015960    0.000000  0.000000  0.000000  \n",
-        "383    0.000000    0.001045     0.000000    0.000000  0.000000  0.001045  \n",
-        "384    0.000000    0.000000     0.000000    0.000000  0.000000  0.001218  \n",
-        "385    0.000000    0.000000     0.000000    0.000000  0.000000  0.000000  \n",
-        "386    0.001414    0.000000     0.000000    0.004243  0.000000  0.000000  \n",
-        "\n",
-        "[387 rows x 17 columns]"
-       ]
-      }
-     ],
-     "prompt_number": 9
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "test_info = Corpus([filename for filename in glob.iglob(os.path.join('test/', '*'))])\n",
-      "test_info_df = test_info.compl_df_build(True)\n",
-      "test_info_df['answers'] = pd.read_csv('test_fixed.csv', dtype='object')\n",
-      "test_info_df"
-     ],
-     "language": "python",
-     "metadata": {},
-     "outputs": [
-      {
-       "html": [
-        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
-        "<table border=\"1\" class=\"dataframe\">\n",
-        "  <thead>\n",
-        "    <tr style=\"text-align: right;\">\n",
-        "      <th></th>\n",
-        "      <th>parent_count</th>\n",
-        "      <th>double_colon</th>\n",
-        "      <th>let_exists</th>\n",
-        "      <th>less_minus</th>\n",
-        "      <th>paren_star</th>\n",
-        "      <th>def_exists</th>\n",
-        "      <th>end_exists</th>\n",
-        "      <th>curly_bracket</th>\n",
-        "      <th>slash_star_star</th>\n",
-        "      <th>forward_slash</th>\n",
-        "      <th>var_exists</th>\n",
-        "      <th>star_count</th>\n",
-        "      <th>dollar_sign</th>\n",
-        "      <th>val_exists</th>\n",
-        "      <th>else_if</th>\n",
-        "      <th>elif</th>\n",
-        "      <th>answers</th>\n",
-        "    </tr>\n",
-        "  </thead>\n",
-        "  <tbody>\n",
-        "    <tr>\n",
-        "      <th>0 </th>\n",
-        "      <td> 0.045734</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001759</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001759</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  1</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>1 </th>\n",
-        "      <td> 0.063037</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.022923</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002865</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  4</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>2 </th>\n",
-        "      <td> 0.042795</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000058</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000058</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.019122</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.005069</td>\n",
-        "      <td> 0.002477</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.000173</td>\n",
-        "      <td> 0.000346</td>\n",
-        "      <td> 0.000288</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  4</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>3 </th>\n",
-        "      <td> 0.047059</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.035294</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.011765</td>\n",
-        "      <td> 0.005882</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  4</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>4 </th>\n",
-        "      <td> 0.015708</td>\n",
-        "      <td> 0.000561</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000281</td>\n",
-        "      <td> 0.002805</td>\n",
-        "      <td> 0.004769</td>\n",
-        "      <td> 0.001122</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  9</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>5 </th>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002037</td>\n",
-        "      <td> 0.004073</td>\n",
-        "      <td> 0.008147</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004073</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  9</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>6 </th>\n",
-        "      <td> 0.008163</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.008163</td>\n",
-        "      <td> 0.014286</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  9</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>7 </th>\n",
-        "      <td> 0.013329</td>\n",
-        "      <td> 0.000915</td>\n",
-        "      <td> 0.000065</td>\n",
-        "      <td> 0.000457</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000131</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002483</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.002548</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  2</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>8 </th>\n",
-        "      <td> 0.058065</td>\n",
-        "      <td> 0.006452</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.006452</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  2</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>9 </th>\n",
-        "      <td> 0.013752</td>\n",
-        "      <td> 0.003929</td>\n",
-        "      <td> 0.000491</td>\n",
-        "      <td> 0.002947</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.006876</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.004912</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  2</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>10</th>\n",
-        "      <td> 0.124352</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 11</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>11</th>\n",
-        "      <td> 0.088670</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  1</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>12</th>\n",
-        "      <td> 0.222222</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 11</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>13</th>\n",
-        "      <td> 0.110846</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000894</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.000894</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 11</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>14</th>\n",
-        "      <td> 0.006645</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002848</td>\n",
-        "      <td> 0.003797</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  3</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>15</th>\n",
-        "      <td> 0.006572</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002191</td>\n",
-        "      <td> 0.002738</td>\n",
-        "      <td> 0.000548</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  3</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>16</th>\n",
-        "      <td> 0.027182</td>\n",
-        "      <td> 0.001073</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000715</td>\n",
-        "      <td> 0.001788</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.016452</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001073</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.008941</td>\n",
-        "      <td> 0.003577</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 10</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>17</th>\n",
-        "      <td> 0.014606</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004173</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.003130</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001043</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.007825</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 10</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>18</th>\n",
-        "      <td> 0.019254</td>\n",
-        "      <td> 0.000301</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.008123</td>\n",
-        "      <td> 0.003460</td>\n",
-        "      <td> 0.000150</td>\n",
-        "      <td> 0.000301</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.014591</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  7</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>19</th>\n",
-        "      <td> 0.058997</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.002950</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.011799</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.005900</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.014749</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  7</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>20</th>\n",
-        "      <td> 0.097902</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  1</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>21</th>\n",
-        "      <td> 0.053224</td>\n",
-        "      <td> 0.001535</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.012282</td>\n",
-        "      <td> 0.001535</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0</td>\n",
-        "      <td> 0.020983</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  7</td>\n",
+        "  </tbody>\n",
+        "</table>\n",
+        "</div>"
+       ],
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 11,
+       "text": [
+        "  hit_num  parent_count  double_colon  let_exists  less_minus  paren_star  \\\n",
+        "0       1      0.071901      0.000000    0.002066    0.000000    0.001240   \n",
+        "1       1      0.071704      0.000000    0.002699    0.000000    0.000771   \n",
+        "2       1      0.063995      0.000000    0.002695    0.000000    0.000337   \n",
+        "3       2      0.024707      0.002471    0.002471    0.000618    0.000000   \n",
+        "4       2      0.024352      0.002118    0.002647    0.000529    0.000000   \n",
+        "\n",
+        "   def_exists  end_exists  curly_bracket  slash_star_star  forward_slash  \\\n",
+        "0    0.000413           0       0.000000                0       0.000413   \n",
+        "1    0.000386           0       0.000000                0       0.000386   \n",
+        "2    0.000337           0       0.000000                0       0.000337   \n",
+        "3    0.000000           0       0.000000                0       0.000618   \n",
+        "4    0.000000           0       0.001059                0       0.000529   \n",
+        "\n",
+        "   var_exists  star_count  dollar_sign  val_exists  else_if  elif      void  \n",
+        "0           0    0.000000            0           0        0     0  0.000000  \n",
+        "1           0    0.000000            0           0        0     0  0.000000  \n",
+        "2           0    0.000000            0           0        0     0  0.000337  \n",
+        "3           0    0.001235            0           0        0     0  0.000000  \n",
+        "4           0    0.001059            0           0        0     0  0.000000  "
+       ]
+      }
+     ],
+     "prompt_number": 11
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "test_info = Corpus([filename for filename in glob.iglob(os.path.join('test/', '*'))])\n",
+      "test_info_df = test_info.compl_df_build(True)\n",
+      "test_info_df['answers'] = pd.read_csv('test_fixed.csv', dtype='object')\n",
+      "test_info_df.head()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "html": [
+        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
+        "<table border=\"1\" class=\"dataframe\">\n",
+        "  <thead>\n",
+        "    <tr style=\"text-align: right;\">\n",
+        "      <th></th>\n",
+        "      <th>parent_count</th>\n",
+        "      <th>double_colon</th>\n",
+        "      <th>let_exists</th>\n",
+        "      <th>less_minus</th>\n",
+        "      <th>paren_star</th>\n",
+        "      <th>def_exists</th>\n",
+        "      <th>end_exists</th>\n",
+        "      <th>curly_bracket</th>\n",
+        "      <th>slash_star_star</th>\n",
+        "      <th>forward_slash</th>\n",
+        "      <th>var_exists</th>\n",
+        "      <th>star_count</th>\n",
+        "      <th>dollar_sign</th>\n",
+        "      <th>val_exists</th>\n",
+        "      <th>else_if</th>\n",
+        "      <th>elif</th>\n",
+        "      <th>void</th>\n",
+        "      <th>answers</th>\n",
         "    </tr>\n",
+        "  </thead>\n",
+        "  <tbody>\n",
         "    <tr>\n",
-        "      <th>22</th>\n",
-        "      <td> 0.026448</td>\n",
-        "      <td> 0.000132</td>\n",
-        "      <td> 0.004893</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.005554</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000397</td>\n",
-        "      <td> 0.003967</td>\n",
-        "      <td> 0.000000</td>\n",
+        "      <th>0</th>\n",
+        "      <td> 0.045734</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.000397</td>\n",
+        "      <td> 0.001759</td>\n",
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  5</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>23</th>\n",
-        "      <td> 0.017391</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.005217</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
+        "      <td> 0.001759</td>\n",
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  5</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>24</th>\n",
-        "      <td> 0.025854</td>\n",
-        "      <td> 0.000923</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000923</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.014774</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
         "      <td> 0</td>\n",
-        "      <td> 0.024007</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  6</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>25</th>\n",
-        "      <td> 0.026801</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001675</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.001675</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.003350</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  1</td>\n",
-        "    </tr>\n",
-        "    <tr>\n",
-        "      <th>26</th>\n",
-        "      <td> 0.039867</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.013289</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
         "      <td> 0</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.004983</td>\n",
-        "      <td>  8</td>\n",
+        "      <td> 1</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-        "      <th>27</th>\n",
-        "      <td> 0.028050</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
+        "      <th>1</th>\n",
+        "      <td> 0.063037</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.001403</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.001403</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.022923</td>\n",
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.002865</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td>  8</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-        "      <th>28</th>\n",
-        "      <td> 0.036810</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.012270</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
+        "      <th>2</th>\n",
+        "      <td> 0.042795</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.000058</td>\n",
         "      <td> 0</td>\n",
+        "      <td> 0.000058</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  8</td>\n",
+        "      <td> 0.019122</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.005069</td>\n",
+        "      <td> 0.002477</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000173</td>\n",
+        "      <td> 0.000346</td>\n",
+        "      <td> 0.000288</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-        "      <th>29</th>\n",
-        "      <td> 0.029608</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
+        "      <th>3</th>\n",
+        "      <td> 0.047059</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.003059</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.000888</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
+        "      <td> 0.035294</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.011765</td>\n",
+        "      <td> 0.005882</td>\n",
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  8</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
-        "      <th>30</th>\n",
-        "      <td> 0.053892</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
+        "      <th>4</th>\n",
+        "      <td> 0.015708</td>\n",
+        "      <td> 0.000561</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.020958</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0.000281</td>\n",
+        "      <td> 0.002805</td>\n",
+        "      <td> 0.004769</td>\n",
+        "      <td> 0.001122</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.002246</td>\n",
         "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
         "      <td> 0.000000</td>\n",
-        "      <td> 0.000000</td>\n",
-        "      <td>  4</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 9</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
@@ -2148,143 +349,32 @@
        ],
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 10,
+       "prompt_number": 12,
        "text": [
-        "    parent_count  double_colon  let_exists  less_minus  paren_star  \\\n",
-        "0       0.045734      0.000000    0.001759    0.000000    0.000000   \n",
-        "1       0.063037      0.000000    0.000000    0.000000    0.000000   \n",
-        "2       0.042795      0.000000    0.000058    0.000000    0.000058   \n",
-        "3       0.047059      0.000000    0.000000    0.000000    0.000000   \n",
-        "4       0.015708      0.000561    0.000000    0.000000    0.000281   \n",
-        "5       0.000000      0.000000    0.000000    0.000000    0.000000   \n",
-        "6       0.008163      0.000000    0.000000    0.000000    0.000000   \n",
-        "7       0.013329      0.000915    0.000065    0.000457    0.000000   \n",
-        "8       0.058065      0.006452    0.000000    0.006452    0.000000   \n",
-        "9       0.013752      0.003929    0.000491    0.002947    0.000000   \n",
-        "10      0.124352      0.000000    0.000000    0.000000    0.000000   \n",
-        "11      0.088670      0.000000    0.000000    0.000000    0.000000   \n",
-        "12      0.222222      0.000000    0.000000    0.000000    0.000000   \n",
-        "13      0.110846      0.000000    0.000894    0.000000    0.000000   \n",
-        "14      0.006645      0.000000    0.000000    0.000000    0.000000   \n",
-        "15      0.006572      0.000000    0.000000    0.000000    0.000000   \n",
-        "16      0.027182      0.001073    0.000000    0.000000    0.000715   \n",
-        "17      0.014606      0.000000    0.000000    0.000000    0.000000   \n",
-        "18      0.019254      0.000301    0.000000    0.000000    0.000000   \n",
-        "19      0.058997      0.000000    0.000000    0.000000    0.002950   \n",
-        "20      0.097902      0.000000    0.000000    0.000000    0.000000   \n",
-        "21      0.053224      0.001535    0.000000    0.000000    0.000000   \n",
-        "22      0.026448      0.000132    0.004893    0.000000    0.005554   \n",
-        "23      0.017391      0.000000    0.005217    0.000000    0.000000   \n",
-        "24      0.025854      0.000923    0.000000    0.000000    0.000000   \n",
-        "25      0.026801      0.000000    0.001675    0.000000    0.000000   \n",
-        "26      0.039867      0.000000    0.000000    0.000000    0.000000   \n",
-        "27      0.028050      0.000000    0.000000    0.000000    0.000000   \n",
-        "28      0.036810      0.000000    0.000000    0.000000    0.000000   \n",
-        "29      0.029608      0.000000    0.000000    0.000000    0.000000   \n",
-        "30      0.053892      0.000000    0.000000    0.000000    0.000000   \n",
-        "\n",
-        "    def_exists  end_exists  curly_bracket  slash_star_star  forward_slash  \\\n",
-        "0     0.000000    0.000000       0.001759         0.000000       0.000000   \n",
-        "1     0.000000    0.000000       0.022923         0.000000       0.000000   \n",
-        "2     0.000000    0.000000       0.019122         0.000000       0.005069   \n",
-        "3     0.000000    0.000000       0.035294         0.000000       0.011765   \n",
-        "4     0.002805    0.004769       0.001122         0.000000       0.000000   \n",
-        "5     0.002037    0.004073       0.008147         0.000000       0.004073   \n",
-        "6     0.008163    0.014286       0.000000         0.000000       0.000000   \n",
-        "7     0.000131    0.000000       0.002483         0.000000       0.000000   \n",
-        "8     0.000000    0.000000       0.000000         0.000000       0.000000   \n",
-        "9     0.000000    0.000000       0.006876         0.000000       0.000000   \n",
-        "10    0.000000    0.000000       0.000000         0.000000       0.000000   \n",
-        "11    0.000000    0.000000       0.000000         0.000000       0.000000   \n",
-        "12    0.000000    0.000000       0.000000         0.000000       0.000000   \n",
-        "13    0.000000    0.000000       0.000000         0.000000       0.000000   \n",
-        "14    0.000000    0.000000       0.002848         0.003797       0.000000   \n",
-        "15    0.000000    0.000000       0.002191         0.002738       0.000548   \n",
-        "16    0.001788    0.000000       0.016452         0.000000       0.001073   \n",
-        "17    0.004173    0.000000       0.003130         0.000000       0.001043   \n",
-        "18    0.000000    0.000000       0.008123         0.003460       0.000150   \n",
-        "19    0.000000    0.000000       0.011799         0.000000       0.005900   \n",
-        "20    0.000000    0.000000       0.000000         0.000000       0.000000   \n",
-        "21    0.000000    0.000000       0.012282         0.001535       0.000000   \n",
-        "22    0.000000    0.000397       0.003967         0.000000       0.000000   \n",
-        "23    0.000000    0.000000       0.000000         0.000000       0.000000   \n",
-        "24    0.000923    0.000000       0.014774         0.000000       0.000000   \n",
-        "25    0.001675    0.000000       0.003350         0.000000       0.000000   \n",
-        "26    0.000000    0.000000       0.013289         0.000000       0.000000   \n",
-        "27    0.001403    0.000000       0.001403         0.000000       0.000000   \n",
-        "28    0.012270    0.000000       0.000000         0.000000       0.000000   \n",
-        "29    0.003059    0.000000       0.000888         0.000000       0.000000   \n",
-        "30    0.000000    0.000000       0.020958         0.000000       0.000000   \n",
-        "\n",
-        "    var_exists  star_count  dollar_sign  val_exists   else_if      elif  \\\n",
-        "0     0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "1     0.002865           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "2     0.002477           0     0.000173    0.000346  0.000288  0.000000   \n",
-        "3     0.005882           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "4     0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "5     0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "6     0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "7     0.000000           0     0.002548    0.000000  0.000000  0.000000   \n",
-        "8     0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "9     0.000000           0     0.004912    0.000000  0.000000  0.000000   \n",
-        "10    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "11    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "12    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "13    0.000000           0     0.000894    0.000000  0.000000  0.000000   \n",
-        "14    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "15    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "16    0.000000           0     0.008941    0.003577  0.000000  0.000000   \n",
-        "17    0.000000           0     0.000000    0.007825  0.000000  0.000000   \n",
-        "18    0.000301           0     0.014591    0.000000  0.000000  0.000000   \n",
-        "19    0.000000           0     0.014749    0.000000  0.000000  0.000000   \n",
-        "20    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "21    0.000000           0     0.020983    0.000000  0.000000  0.000000   \n",
-        "22    0.000397           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "23    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "24    0.000000           0     0.024007    0.000000  0.000000  0.000000   \n",
-        "25    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "26    0.000000           0     0.000000    0.000000  0.000000  0.004983   \n",
-        "27    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "28    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "29    0.000000           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "30    0.002246           0     0.000000    0.000000  0.000000  0.000000   \n",
-        "\n",
-        "   answers  \n",
-        "0        1  \n",
-        "1        4  \n",
-        "2        4  \n",
-        "3        4  \n",
-        "4        9  \n",
-        "5        9  \n",
-        "6        9  \n",
-        "7        2  \n",
-        "8        2  \n",
-        "9        2  \n",
-        "10      11  \n",
-        "11       1  \n",
-        "12      11  \n",
-        "13      11  \n",
-        "14       3  \n",
-        "15       3  \n",
-        "16      10  \n",
-        "17      10  \n",
-        "18       7  \n",
-        "19       7  \n",
-        "20       1  \n",
-        "21       7  \n",
-        "22       5  \n",
-        "23       5  \n",
-        "24       6  \n",
-        "25       1  \n",
-        "26       8  \n",
-        "27       8  \n",
-        "28       8  \n",
-        "29       8  \n",
-        "30       4  "
+        "   parent_count  double_colon  let_exists  less_minus  paren_star  def_exists  \\\n",
+        "0      0.045734      0.000000    0.001759           0    0.000000    0.000000   \n",
+        "1      0.063037      0.000000    0.000000           0    0.000000    0.000000   \n",
+        "2      0.042795      0.000000    0.000058           0    0.000058    0.000000   \n",
+        "3      0.047059      0.000000    0.000000           0    0.000000    0.000000   \n",
+        "4      0.015708      0.000561    0.000000           0    0.000281    0.002805   \n",
+        "\n",
+        "   end_exists  curly_bracket  slash_star_star  forward_slash  var_exists  \\\n",
+        "0    0.000000       0.001759                0       0.000000    0.000000   \n",
+        "1    0.000000       0.022923                0       0.000000    0.002865   \n",
+        "2    0.000000       0.019122                0       0.005069    0.002477   \n",
+        "3    0.000000       0.035294                0       0.011765    0.005882   \n",
+        "4    0.004769       0.001122                0       0.000000    0.000000   \n",
+        "\n",
+        "   star_count  dollar_sign  val_exists   else_if  elif  void answers  \n",
+        "0           0     0.000000    0.000000  0.000000     0     0       1  \n",
+        "1           0     0.000000    0.000000  0.000000     0     0       4  \n",
+        "2           0     0.000173    0.000346  0.000288     0     0       4  \n",
+        "3           0     0.000000    0.000000  0.000000     0     0       4  \n",
+        "4           0     0.000000    0.000000  0.000000     0     0       9  "
        ]
       }
      ],
-     "prompt_number": 10
+     "prompt_number": 12
     },
     {
      "cell_type": "heading",
@@ -2321,7 +411,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 11
+     "prompt_number": 3
     },
     {
      "cell_type": "code",
@@ -2342,21 +432,21 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
+        "          3       0.67      1.00      0.80         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       0.60      1.00      0.75         3\n",
+        "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.84      0.77      0.76        31\n",
+        "avg / total       0.92      0.84      0.84        31\n",
         "\n",
         "[[2 0 2 0 0 0 0 0 0 0 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 0 2]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -2368,13 +458,13 @@
       {
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 12,
+       "prompt_number": 4,
        "text": [
-        "0.76113671274961581"
+        "0.83694316436251914"
        ]
       }
      ],
-     "prompt_number": 12
+     "prompt_number": 4
     },
     {
      "cell_type": "code",
@@ -2394,73 +484,73 @@
        "text": [
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.50      0.50      0.50         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
+        "          3       1.00      1.00      1.00         2\n",
         "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.33      1.00      0.50         1\n",
-        "          7       1.00      0.33      0.50         3\n",
+        "          6       0.50      1.00      0.67         1\n",
+        "          7       1.00      0.67      0.80         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.78      0.77      0.75        31\n",
+        "avg / total       0.92      0.87      0.87        31\n",
         "\n",
         "[[2 0 2 0 0 0 0 0 0 0 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [2 0 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 0 0 0 1 2 0 0]\n",
         " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.50      0.50      0.50         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
+        "          3       1.00      1.00      1.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.33      1.00      0.50         1\n",
-        "          7       1.00      0.33      0.50         3\n",
+        "          6       0.50      1.00      0.67         1\n",
+        "          7       1.00      0.67      0.80         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          9       0.75      1.00      0.86         3\n",
         "\n",
-        "avg / total       0.81      0.77      0.76        31\n",
+        "avg / total       0.92      0.87      0.87        31\n",
         "\n",
         "[[2 0 2 0 0 0 0 0 0 0 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [2 0 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 1 2 0 0]\n",
+        " [0 0 0 0 0 0 0 0 0 3 1]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       1.00      0.50      0.67         4\n",
+        "          1       1.00      0.25      0.40         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.50      0.50      0.50         2\n",
+        "          3       1.00      1.00      1.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.33      1.00      0.50         1\n",
-        "          7       1.00      0.33      0.50         3\n",
+        "          6       0.50      1.00      0.67         1\n",
+        "          7       1.00      0.67      0.80         3\n",
         "          8       0.75      0.75      0.75         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          9       0.75      1.00      0.86         3\n",
         "\n",
-        "avg / total       0.88      0.81      0.80        31\n"
+        "avg / total       0.89      0.84      0.82        31\n"
        ]
       },
       {
@@ -2468,43 +558,43 @@
        "stream": "stdout",
        "text": [
         "\n",
-        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
+        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 1 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 1 2 0 0]\n",
+        " [0 0 0 0 0 0 0 0 0 3 1]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.50      0.50      0.50         4\n",
+        "          1       0.50      0.25      0.33         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
+        "          3       1.00      1.00      1.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       1.00      0.75      0.86         4\n",
+        "          8       0.75      0.75      0.75         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.81      0.77      0.76        31\n",
+        "avg / total       0.84      0.81      0.79        31\n",
         "\n",
-        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
+        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [2 0 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [1 0 0 0 0 0 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -2512,15 +602,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -2537,7 +627,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -2545,26 +635,26 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.33      1.00      0.50         1\n",
-        "          7       1.00      0.33      0.50         3\n",
-        "          8       0.60      0.75      0.67         4\n",
+        "          6       0.50      1.00      0.67         1\n",
+        "          7       1.00      0.67      0.80         3\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.82      0.77      0.76        31\n",
+        "avg / total       0.92      0.87      0.87        31\n",
         "\n",
         "[[2 0 2 0 0 0 0 0 0 0 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 2 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 1 2 0 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -2572,15 +662,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.50      0.50      0.50         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.88      0.81      0.80        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -2592,12 +682,12 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 1 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -2605,15 +695,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.60      0.75      0.67         4\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.82      0.77      0.76        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -2625,96 +715,94 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 2 0]\n",
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         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.50      0.25      0.33         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
+        "          3       0.67      1.00      0.80         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.33      1.00      0.50         1\n",
-        "          7       1.00      0.33      0.50         3\n",
-        "          8       0.60      0.75      0.67         4\n",
+        "          6       0.50      1.00      0.67         1\n",
+        "          7       1.00      0.67      0.80         3\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.76      0.74      0.72        31\n",
+        "avg / total       0.92      0.87      0.87        31\n"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
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         "\n",
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         " [0 0 3 0 0 0 0 0 0 0 0]\n",
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         " [0 0 0 0 1 0 0 0 0 3 0]\n",
-        " [0 0 0 0 0 0 0 0 0 0 3]]"
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-      {
-       "output_type": "stream",
-       "stream": "stdout",
-       "text": [
-        "\n",
+        " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       1.00      0.50      0.67         4\n",
+        "          1       1.00      0.25      0.40         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.50      0.50      0.50         2\n",
+        "          3       0.67      1.00      0.80         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.33      1.00      0.50         1\n",
-        "          7       1.00      0.33      0.50         3\n",
-        "          8       1.00      0.75      0.86         4\n",
-        "          9       0.75      1.00      0.86         3\n",
+        "          6       0.50      1.00      0.67         1\n",
+        "          7       1.00      0.67      0.80         3\n",
+        "          8       0.75      0.75      0.75         4\n",
+        "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.88      0.81      0.80        31\n",
+        "avg / total       0.89      0.84      0.82        31\n"
+       ]
+      },
+      {
+       "output_type": "stream",
+       "stream": "stdout",
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         "\n",
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-       "output_type": "stream",
-       "stream": "stdout",
-       "text": [
-        "\n",
+        " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
         "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
-        "          9       0.75      1.00      0.86         3\n",
+        "          8       1.00      0.75      0.86         4\n",
+        "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.82      0.77      0.76        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -2726,12 +814,12 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 1 1]\n",
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         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -2739,15 +827,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.50      0.50      0.50         2\n",
+        "          3       0.67      1.00      0.80         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       0.75      1.00      0.86         3\n",
+        "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.88      0.81      0.80        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -2759,7 +847,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 0 1]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -2768,19 +856,19 @@
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.67      0.50      0.57         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
+        "          3       0.67      1.00      0.80         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       0.75      1.00      0.86         3\n",
+        "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.81      0.77      0.76        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -2792,7 +880,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [1 0 0 0 0 0 0 0 0 0 1]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -2801,19 +889,19 @@
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.50      0.50      0.50         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.81      0.77      0.76        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -2825,12 +913,12 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [2 0 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -2838,15 +926,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -2863,7 +951,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -2871,15 +959,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.50      1.00      0.67         1\n",
-        "          7       1.00      0.67      0.80         3\n",
+        "          6       0.33      1.00      0.50         1\n",
+        "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.87      0.87        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -2895,8 +983,8 @@
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 1 2 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -2904,15 +992,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
+        "          3       1.00      1.00      1.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       1.00      0.75      0.86         4\n",
-        "          9       0.60      1.00      0.75         3\n",
+        "          8       1.00      1.00      1.00         4\n",
+        "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.84      0.77      0.76        31\n"
+        "avg / total       0.94      0.87      0.87        31\n"
        ]
       },
       {
@@ -2924,28 +1012,28 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 0 2]\n",
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         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 4 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       1.00      0.50      0.67         4\n",
+        "          1       1.00      0.25      0.40         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
+        "          3       0.67      1.00      0.80         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.50      1.00      0.67         1\n",
-        "          7       1.00      0.67      0.80         3\n",
-        "          8       1.00      0.75      0.86         4\n",
-        "          9       0.60      1.00      0.75         3\n",
+        "          6       0.33      1.00      0.50         1\n",
+        "          7       1.00      0.33      0.50         3\n",
+        "          8       0.75      0.75      0.75         4\n",
+        "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.84      0.81      0.80        31\n"
+        "avg / total       0.89      0.81      0.79        31\n"
        ]
       },
       {
@@ -2953,32 +1041,32 @@
        "stream": "stdout",
        "text": [
         "\n",
-        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
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         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.67      0.50      0.57         4\n",
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         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.80      0.77      0.76        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -2990,12 +1078,12 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [1 0 0 0 0 0 0 0 0 1 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -3003,15 +1091,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.50      0.50      0.50         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.88      0.81      0.80        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -3023,28 +1111,28 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 1 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.50      0.50      0.50         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.81      0.77      0.76        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -3056,12 +1144,12 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [2 0 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -3069,15 +1157,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
-        "          9       0.75      1.00      0.86         3\n",
+        "          8       1.00      0.75      0.86         4\n",
+        "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.82      0.77      0.76        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -3089,28 +1177,28 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 1 1]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.67      0.50      0.57         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.80      0.77      0.76        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -3122,12 +1210,12 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [1 0 0 0 0 0 0 0 0 1 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -3164,19 +1252,19 @@
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.50      0.50      0.50         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.81      0.77      0.76        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -3188,28 +1276,28 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [2 0 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.67      0.50      0.57         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.80      0.77      0.76        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -3221,12 +1309,12 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [1 0 0 0 0 0 0 0 0 1 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -3234,15 +1322,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
+        "          3       1.00      1.00      1.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       0.60      1.00      0.75         3\n",
+        "          9       0.75      1.00      0.86         3\n",
         "\n",
-        "avg / total       0.84      0.77      0.76        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -3254,20 +1342,20 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 0 2]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 3 1]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.50      0.50      0.50         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
+        "          3       0.67      1.00      0.80         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
@@ -3275,7 +1363,7 @@
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.81      0.77      0.76        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -3287,7 +1375,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [2 0 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -3300,15 +1388,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
+        "          3       0.67      1.00      0.80         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       0.60      1.00      0.75         3\n",
+        "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.84      0.77      0.76        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -3320,7 +1408,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 0 2]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -3333,15 +1421,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -3358,7 +1446,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -3366,15 +1454,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -3391,7 +1479,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -3399,15 +1487,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.50      0.50      0.50         2\n",
+        "          3       0.67      1.00      0.80         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       0.75      1.00      0.86         3\n",
+        "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.88      0.81      0.80        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -3419,7 +1507,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 0 1]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -3465,15 +1553,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
+        "          3       0.67      1.00      0.80         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       0.60      1.00      0.75         3\n",
+        "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.84      0.77      0.76        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -3485,7 +1573,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 0 2]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -3498,15 +1586,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
+        "          3       0.67      1.00      0.80         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       0.60      1.00      0.75         3\n",
+        "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.84      0.77      0.76        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -3518,7 +1606,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 0 2]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -3564,15 +1652,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       0.60      1.00      0.75         3\n",
+        "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.84      0.77      0.76        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -3584,28 +1672,28 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 0 2]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.67      0.50      0.57         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.50      0.50      0.50         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.86      0.81      0.81        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -3617,12 +1705,12 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [1 0 0 0 1 0 0 0 0 0 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -3663,13 +1751,13 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
+        "          3       1.00      1.00      1.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          9       0.75      1.00      0.86         3\n",
         "\n",
         "avg / total       0.92      0.84      0.84        31\n"
        ]
@@ -3688,7 +1776,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 3 1]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -3725,19 +1813,19 @@
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.67      0.50      0.57         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.80      0.77      0.76        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -3749,28 +1837,28 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [1 0 0 0 0 0 0 0 0 1 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.33      0.25      0.29         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.76      0.74      0.72        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -3778,16 +1866,16 @@
        "stream": "stdout",
        "text": [
         "\n",
-        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
+        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [2 0 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -3795,15 +1883,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -3820,23 +1908,23 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.67      0.50      0.57         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.80      0.77      0.76        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -3848,28 +1936,28 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [1 0 0 0 0 0 0 0 0 1 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.50      0.50      0.50         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.81      0.77      0.76        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -3881,12 +1969,12 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [2 0 0 0 0 0 0 0 0 0 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -3894,15 +1982,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -3919,23 +2007,23 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.50      0.25      0.33         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       0.60      0.75      0.67         4\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.76      0.74      0.72        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -3943,16 +2031,16 @@
        "stream": "stdout",
        "text": [
         "\n",
-        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
+        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [1 0 0 0 0 0 0 0 0 1 0]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -3960,15 +2048,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.00      0.00      0.00         2\n",
+        "          3       0.67      1.00      0.80         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       0.60      1.00      0.75         3\n",
+        "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.84      0.77      0.76        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -3980,7 +2068,7 @@
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 0 2]\n",
+        " [0 0 0 0 2 0 0 0 0 0 0]\n",
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
@@ -3993,15 +2081,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
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@@ -4018,79 +2106,69 @@
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         " [0 0 0 0 0 0 0 0 0 0 3]]\n"
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-       "output_type": "stream",
-       "stream": "stderr",
-       "text": [
-        "/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py:1771: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n",
-        "  'precision', 'predicted', average, warn_for)\n",
-        "/Users/zackjcooper/.pyenv/versions/sandbox/lib/python3.4/site-packages/sklearn/metrics/metrics.py:1771: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples.\n",
-        "  'precision', 'predicted', average, warn_for)\n"
-       ]
-      },
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        "metadata": {},
        "output_type": "pyout",
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-     "prompt_number": 13
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     {
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@@ -4106,13 +2184,13 @@
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N161RTNQ6ftSmbT4rQhDGV9KpLRbQ6Q5wkpDsldHymcU6DX4645xNOUqUiYaa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\n9wGoKIryKVmW1wAcBb0nud0lCIIgoiLoup72PhA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4vTRQq2b4I16lU1PS+dHhJMWSE8hyDtRk+C366VRbI+uirYgfBC/g99BALTXi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\nAAAAAElFTkSuQmCC\n",
        "text": [
-        "<matplotlib.figure.Figure at 0x10827a828>"
+        "<matplotlib.figure.Figure at 0x10cd1bda0>"
        ]
       }
      ],
-     "prompt_number": 14
+     "prompt_number": 6
     },
     {
      "cell_type": "heading",
@@ -4152,7 +2230,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 31
+     "prompt_number": 7
     },
     {
      "cell_type": "code",
@@ -4166,23 +2244,23 @@
       {
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 28,
+       "prompt_number": 8,
        "text": [
-        "[('ruby', 0.26000000000000001),\n",
-        " ('java', 0.16),\n",
-        " ('python', 0.16),\n",
-        " ('clojure', 0.14000000000000001),\n",
-        " ('scheme', 0.10000000000000001),\n",
-        " ('php', 0.059999999999999998),\n",
+        "[('java', 0.46000000000000002),\n",
+        " ('ruby', 0.20000000000000001),\n",
+        " ('scheme', 0.16),\n",
+        " ('clojure', 0.059999999999999998),\n",
+        " ('python', 0.059999999999999998),\n",
         " ('haskell', 0.040000000000000001),\n",
-        " ('javascript', 0.040000000000000001),\n",
-        " ('perl', 0.040000000000000001),\n",
+        " ('php', 0.02),\n",
         " ('scala', 0.0),\n",
-        " ('ocaml', 0.0)]"
+        " ('javascript', 0.0),\n",
+        " ('ocaml', 0.0),\n",
+        " ('perl', 0.0)]"
        ]
       }
      ],
-     "prompt_number": 28
+     "prompt_number": 8
     },
     {
      "cell_type": "heading",
@@ -4216,7 +2294,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 34
+     "prompt_number": 9
     },
     {
      "cell_type": "code",
@@ -4238,23 +2316,23 @@
       {
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 33,
+       "prompt_number": 10,
        "text": [
-        "[('ocaml', 0.73999999999999999),\n",
-        " ('clojure', 0.10000000000000001),\n",
-        " ('scheme', 0.059999999999999998),\n",
-        " ('python', 0.059999999999999998),\n",
+        "[('ocaml', 0.66000000000000003),\n",
+        " ('clojure', 0.12),\n",
+        " ('scheme', 0.12),\n",
+        " ('python', 0.040000000000000001),\n",
+        " ('ruby', 0.040000000000000001),\n",
         " ('haskell', 0.02),\n",
-        " ('java', 0.02),\n",
         " ('scala', 0.0),\n",
+        " ('java', 0.0),\n",
         " ('javascript', 0.0),\n",
         " ('perl', 0.0),\n",
-        " ('php', 0.0),\n",
-        " ('ruby', 0.0)]"
+        " ('php', 0.0)]"
        ]
       }
      ],
-     "prompt_number": 33
+     "prompt_number": 10
     },
     {
      "cell_type": "code",
@@ -4263,7 +2341,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 16
+     "prompt_number": 10
     },
     {
      "cell_type": "code",
@@ -4272,7 +2350,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 16
+     "prompt_number": 10
     },
     {
      "cell_type": "code",
@@ -4281,7 +2359,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 16
+     "prompt_number": 10
     },
     {
      "cell_type": "code",
@@ -4290,7 +2368,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 16
+     "prompt_number": 10
     },
     {
      "cell_type": "code",
@@ -4299,7 +2377,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 16
+     "prompt_number": 10
     }
    ],
    "metadata": {}

From 1698c61b714957bb3f83a8c28d187df260401863 Mon Sep 17 00:00:00 2001
From: Zack Cooper <zackjcooper@gmail.com>
Date: Mon, 16 Feb 2015 09:10:38 -0500
Subject: [PATCH 6/6] changed features

---
 corpus_build.py            |   4 +-
 lang classifier live.ipynb | 596 +++++++++++++++++++------------------
 2 files changed, 316 insertions(+), 284 deletions(-)

diff --git a/corpus_build.py b/corpus_build.py
index b659079..2b7fce0 100644
--- a/corpus_build.py
+++ b/corpus_build.py
@@ -67,8 +67,8 @@
                 ('val_exists', r"\bval\b"),
                 ('else_if', r"(else if)"),
                 ('elif', r"(elif)"),
-                ('elif', r"(print )"),
-                ('elif', r"(print\()"),
+                ('print_space', r"(print )"),
+                ('pyth_print', r"(print\()"),
                 ('void', r"(void)")]
 
 
diff --git a/lang classifier live.ipynb b/lang classifier live.ipynb
index d9ebd8b..fc999af 100644
--- a/lang classifier live.ipynb	
+++ b/lang classifier live.ipynb	
@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:5d38ae2fb3758ef4f48e8df732eaeef65eb86124e67ec22c3c221b664a5301d2"
+  "signature": "sha256:67cb485a11f3574e7154427b6ce8b9cb5f0788005d345301cc83874050c10871"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -56,6 +56,8 @@
         "      <th>val_exists</th>\n",
         "      <th>else_if</th>\n",
         "      <th>elif</th>\n",
+        "      <th>print_space</th>\n",
+        "      <th>pyth_print</th>\n",
         "      <th>void</th>\n",
         "    </tr>\n",
         "  </thead>\n",
@@ -79,6 +81,8 @@
         "      <td> 0</td>\n",
         "      <td> 0</td>\n",
         "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -100,6 +104,8 @@
         "      <td> 0</td>\n",
         "      <td> 0</td>\n",
         "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -121,6 +127,8 @@
         "      <td> 0</td>\n",
         "      <td> 0</td>\n",
         "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000337</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -142,6 +150,8 @@
         "      <td> 0</td>\n",
         "      <td> 0</td>\n",
         "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -163,6 +173,8 @@
         "      <td> 0</td>\n",
         "      <td> 0</td>\n",
         "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 0.000000</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
@@ -187,12 +199,19 @@
         "3    0.000000           0       0.000000                0       0.000618   \n",
         "4    0.000000           0       0.001059                0       0.000529   \n",
         "\n",
-        "   var_exists  star_count  dollar_sign  val_exists  else_if  elif      void  \n",
-        "0           0    0.000000            0           0        0     0  0.000000  \n",
-        "1           0    0.000000            0           0        0     0  0.000000  \n",
-        "2           0    0.000000            0           0        0     0  0.000337  \n",
-        "3           0    0.001235            0           0        0     0  0.000000  \n",
-        "4           0    0.001059            0           0        0     0  0.000000  "
+        "   var_exists  star_count  dollar_sign  val_exists  else_if  elif  \\\n",
+        "0           0    0.000000            0           0        0     0   \n",
+        "1           0    0.000000            0           0        0     0   \n",
+        "2           0    0.000000            0           0        0     0   \n",
+        "3           0    0.001235            0           0        0     0   \n",
+        "4           0    0.001059            0           0        0     0   \n",
+        "\n",
+        "   print_space  pyth_print      void  \n",
+        "0            0           0  0.000000  \n",
+        "1            0           0  0.000000  \n",
+        "2            0           0  0.000337  \n",
+        "3            0           0  0.000000  \n",
+        "4            0           0  0.000000  "
        ]
       }
      ],
@@ -233,6 +252,8 @@
         "      <th>val_exists</th>\n",
         "      <th>else_if</th>\n",
         "      <th>elif</th>\n",
+        "      <th>print_space</th>\n",
+        "      <th>pyth_print</th>\n",
         "      <th>void</th>\n",
         "      <th>answers</th>\n",
         "    </tr>\n",
@@ -257,6 +278,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0</td>\n",
         "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 1</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -278,6 +301,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0</td>\n",
         "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -299,6 +324,8 @@
         "      <td> 0.000288</td>\n",
         "      <td> 0</td>\n",
         "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -320,6 +347,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0</td>\n",
         "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 4</td>\n",
         "    </tr>\n",
         "    <tr>\n",
@@ -341,6 +370,8 @@
         "      <td> 0.000000</td>\n",
         "      <td> 0</td>\n",
         "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
+        "      <td> 0</td>\n",
         "      <td> 9</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
@@ -365,12 +396,19 @@
         "3    0.000000       0.035294                0       0.011765    0.005882   \n",
         "4    0.004769       0.001122                0       0.000000    0.000000   \n",
         "\n",
-        "   star_count  dollar_sign  val_exists   else_if  elif  void answers  \n",
-        "0           0     0.000000    0.000000  0.000000     0     0       1  \n",
-        "1           0     0.000000    0.000000  0.000000     0     0       4  \n",
-        "2           0     0.000173    0.000346  0.000288     0     0       4  \n",
-        "3           0     0.000000    0.000000  0.000000     0     0       4  \n",
-        "4           0     0.000000    0.000000  0.000000     0     0       9  "
+        "   star_count  dollar_sign  val_exists   else_if  elif  print_space  \\\n",
+        "0           0     0.000000    0.000000  0.000000     0            0   \n",
+        "1           0     0.000000    0.000000  0.000000     0            0   \n",
+        "2           0     0.000173    0.000346  0.000288     0            0   \n",
+        "3           0     0.000000    0.000000  0.000000     0            0   \n",
+        "4           0     0.000000    0.000000  0.000000     0            0   \n",
+        "\n",
+        "   pyth_print  void answers  \n",
+        "0           0     0       1  \n",
+        "1           0     0       4  \n",
+        "2           0     0       4  \n",
+        "3           0     0       4  \n",
+        "4           0     0       9  "
        ]
       }
      ],
@@ -411,13 +449,13 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 3
+     "prompt_number": 13
     },
     {
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "run_test_model(RandomForestClassifier(50), corp_train, corp_answer, test_train, test_answer)"
+      "run_test_model(RandomForestClassifier(40), corp_train, corp_answer, test_train, test_answer)"
      ],
      "language": "python",
      "metadata": {},
@@ -432,15 +470,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.33      1.00      0.50         1\n",
-        "          7       1.00      0.33      0.50         3\n",
+        "          6       0.50      1.00      0.67         1\n",
+        "          7       1.00      0.67      0.80         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n",
+        "avg / total       0.92      0.87      0.87        31\n",
         "\n",
         "[[2 0 2 0 0 0 0 0 0 0 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
@@ -450,21 +488,21 @@
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 1 2 0 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n"
        ]
       },
       {
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 4,
+       "prompt_number": 14,
        "text": [
-        "0.83694316436251914"
+        "0.86991807475678429"
        ]
       }
      ],
-     "prompt_number": 4
+     "prompt_number": 14
     },
     {
      "cell_type": "code",
@@ -484,21 +522,21 @@
        "text": [
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       1.00      0.50      0.67         4\n",
+        "          1       1.00      0.25      0.40         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
         "          3       1.00      1.00      1.00         2\n",
-        "          4       0.80      1.00      0.89         4\n",
+        "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.50      1.00      0.67         1\n",
-        "          7       1.00      0.67      0.80         3\n",
+        "          6       0.33      1.00      0.50         1\n",
+        "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          9       0.60      1.00      0.75         3\n",
         "\n",
-        "avg / total       0.92      0.87      0.87        31\n",
+        "avg / total       0.90      0.81      0.79        31\n",
         "\n",
-        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
+        "[[1 0 2 0 0 0 0 0 0 0 1]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
@@ -506,8 +544,8 @@
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 1 2 0 0]\n",
-        " [0 0 0 0 0 1 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 0 0 0 0 0 3 1]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -515,15 +553,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       1.00      1.00      1.00         2\n",
+        "          3       0.67      1.00      0.80         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.50      1.00      0.67         1\n",
-        "          7       1.00      0.67      0.80         3\n",
+        "          6       0.33      1.00      0.50         1\n",
+        "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       0.75      1.00      0.86         3\n",
+        "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.87      0.87        31\n",
+        "avg / total       0.92      0.84      0.84        31\n",
         "\n",
         "[[2 0 2 0 0 0 0 0 0 0 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
@@ -533,24 +571,24 @@
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 1 2 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 3 1]\n",
+        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       1.00      0.25      0.40         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       1.00      1.00      1.00         2\n",
+        "          3       0.67      1.00      0.80         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.50      1.00      0.67         1\n",
-        "          7       1.00      0.67      0.80         3\n",
-        "          8       0.75      0.75      0.75         4\n",
-        "          9       0.75      1.00      0.86         3\n",
+        "          6       0.33      1.00      0.50         1\n",
+        "          7       1.00      0.33      0.50         3\n",
+        "          8       1.00      0.75      0.86         4\n",
+        "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.89      0.84      0.82        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -558,7 +596,7 @@
        "stream": "stdout",
        "text": [
         "\n",
-        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
+        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
@@ -566,24 +604,24 @@
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 1 2 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 3 1]\n",
+        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       0.50      0.25      0.33         4\n",
+        "          1       1.00      0.25      0.40         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
         "          3       1.00      1.00      1.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       0.75      0.75      0.75         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.84      0.81      0.79        31\n",
+        "avg / total       0.88      0.81      0.79        31\n",
         "\n",
         "[[1 0 2 0 0 0 0 0 0 1 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
@@ -594,7 +632,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [1 0 0 0 0 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -605,12 +643,12 @@
         "          3       1.00      1.00      1.00         2\n",
         "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.33      1.00      0.50         1\n",
-        "          7       1.00      0.33      0.50         3\n",
+        "          6       0.50      1.00      0.67         1\n",
+        "          7       1.00      0.67      0.80         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.91      0.84      0.84        31\n"
+        "avg / total       0.92      0.87      0.87        31\n"
        ]
       },
       {
@@ -626,7 +664,7 @@
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 0 0 0 1 2 0 0]\n",
         " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
@@ -636,14 +674,14 @@
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
         "          3       1.00      1.00      1.00         2\n",
-        "          4       0.80      1.00      0.89         4\n",
+        "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.50      1.00      0.67         1\n",
-        "          7       1.00      0.67      0.80         3\n",
-        "          8       1.00      0.75      0.86         4\n",
+        "          6       0.33      1.00      0.50         1\n",
+        "          7       1.00      0.33      0.50         3\n",
+        "          8       1.00      1.00      1.00         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.87      0.87        31\n",
+        "avg / total       0.94      0.87      0.87        31\n",
         "\n",
         "[[2 0 2 0 0 0 0 0 0 0 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
@@ -653,8 +691,8 @@
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 1 2 0 0]\n",
-        " [0 0 0 0 0 1 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 0 0 0 0 0 4 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -703,13 +741,7 @@
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.91      0.84      0.84        31\n"
-       ]
-      },
-      {
-       "output_type": "stream",
-       "stream": "stdout",
-       "text": [
+        "avg / total       0.91      0.84      0.84        31\n",
         "\n",
         "[[2 0 2 0 0 0 0 0 0 0 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
@@ -728,15 +760,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.50      1.00      0.67         1\n",
-        "          7       1.00      0.67      0.80         3\n",
+        "          6       0.33      1.00      0.50         1\n",
+        "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.87      0.87        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -752,24 +784,24 @@
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 1 2 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       1.00      0.25      0.40         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.50      1.00      0.67         1\n",
         "          7       1.00      0.67      0.80         3\n",
-        "          8       0.75      0.75      0.75         4\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.89      0.84      0.82        31\n"
+        "avg / total       0.92      0.87      0.87        31\n"
        ]
       },
       {
@@ -777,7 +809,7 @@
        "stream": "stdout",
        "text": [
         "\n",
-        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
+        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
@@ -786,7 +818,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 2 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -823,7 +855,7 @@
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       1.00      0.50      0.67         4\n",
+        "          1       1.00      0.25      0.40         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
@@ -832,10 +864,10 @@
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       1.00      0.75      0.86         4\n",
+        "          8       0.75      0.75      0.75         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.89      0.81      0.79        31\n"
        ]
       },
       {
@@ -843,7 +875,7 @@
        "stream": "stdout",
        "text": [
         "\n",
-        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
+        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
@@ -889,7 +921,7 @@
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       1.00      0.50      0.67         4\n",
+        "          1       1.00      0.25      0.40         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
@@ -898,10 +930,10 @@
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       1.00      0.75      0.86         4\n",
+        "          8       0.75      0.75      0.75         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.91      0.84      0.84        31\n"
+        "avg / total       0.88      0.81      0.79        31\n"
        ]
       },
       {
@@ -909,7 +941,7 @@
        "stream": "stdout",
        "text": [
         "\n",
-        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
+        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
@@ -929,12 +961,12 @@
         "          3       1.00      1.00      1.00         2\n",
         "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.33      1.00      0.50         1\n",
-        "          7       1.00      0.33      0.50         3\n",
+        "          6       0.50      1.00      0.67         1\n",
+        "          7       1.00      0.67      0.80         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.91      0.84      0.84        31\n"
+        "avg / total       0.92      0.87      0.87        31\n"
        ]
       },
       {
@@ -950,7 +982,7 @@
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 0 0 0 1 2 0 0]\n",
         " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
@@ -959,15 +991,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       1.00      1.00      1.00         2\n",
-        "          4       0.80      1.00      0.89         4\n",
+        "          3       0.67      1.00      0.80         2\n",
+        "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.33      1.00      0.50         1\n",
-        "          7       1.00      0.33      0.50         3\n",
+        "          6       0.50      1.00      0.67         1\n",
+        "          7       1.00      0.67      0.80         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.91      0.84      0.84        31\n"
+        "avg / total       0.92      0.87      0.87        31\n"
        ]
       },
       {
@@ -983,8 +1015,8 @@
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 0 1 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 1 2 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -993,14 +1025,14 @@
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
         "          3       1.00      1.00      1.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       1.00      1.00      1.00         4\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.94      0.87      0.87        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -1017,23 +1049,23 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 4 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       1.00      0.25      0.40         4\n",
+        "          1       1.00      0.50      0.67         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.33      1.00      0.50         1\n",
-        "          7       1.00      0.33      0.50         3\n",
-        "          8       0.75      0.75      0.75         4\n",
+        "          6       0.50      1.00      0.67         1\n",
+        "          7       1.00      0.67      0.80         3\n",
+        "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.89      0.81      0.79        31\n"
+        "avg / total       0.92      0.87      0.87        31\n"
        ]
       },
       {
@@ -1041,7 +1073,7 @@
        "stream": "stdout",
        "text": [
         "\n",
-        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
+        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
@@ -1049,8 +1081,8 @@
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 1 2 0 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -1091,15 +1123,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       1.00      1.00      1.00         2\n",
-        "          4       0.80      1.00      0.89         4\n",
+        "          3       0.67      1.00      0.80         2\n",
+        "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.91      0.84      0.84        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -1116,7 +1148,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 0 1 0 0 0 3 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -1157,15 +1189,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       1.00      1.00      1.00         2\n",
-        "          4       0.80      1.00      0.89         4\n",
+        "          3       0.67      1.00      0.80         2\n",
+        "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.91      0.84      0.84        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -1182,7 +1214,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 0 1 0 0 0 3 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -1223,15 +1255,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -1248,7 +1280,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -1257,14 +1289,14 @@
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
         "          3       1.00      1.00      1.00         2\n",
-        "          4       0.80      1.00      0.89         4\n",
+        "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          9       0.75      1.00      0.86         3\n",
         "\n",
-        "avg / total       0.91      0.84      0.84        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -1281,7 +1313,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 0 1 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 3 1]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -1355,13 +1387,13 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
+        "          3       1.00      1.00      1.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          9       0.75      1.00      0.86         3\n",
         "\n",
         "avg / total       0.92      0.84      0.84        31\n"
        ]
@@ -1380,7 +1412,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 3 1]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -1388,15 +1420,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -1413,7 +1445,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -1421,15 +1453,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       1.00      1.00      1.00         2\n",
-        "          4       0.80      1.00      0.89         4\n",
+        "          3       0.67      1.00      0.80         2\n",
+        "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.33      1.00      0.50         1\n",
-        "          7       1.00      0.33      0.50         3\n",
+        "          6       0.50      1.00      0.67         1\n",
+        "          7       1.00      0.67      0.80         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.91      0.84      0.84        31\n"
+        "avg / total       0.92      0.87      0.87        31\n"
        ]
       },
       {
@@ -1445,8 +1477,8 @@
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 0 1 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 1 2 0 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -1454,15 +1486,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       1.00      1.00      1.00         2\n",
-        "          4       0.80      1.00      0.89         4\n",
+        "          3       0.67      1.00      0.80         2\n",
+        "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.91      0.84      0.84        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -1479,7 +1511,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 0 1 0 0 0 3 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -1487,15 +1519,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -1512,7 +1544,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -1553,15 +1585,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.33      1.00      0.50         1\n",
-        "          7       1.00      0.33      0.50         3\n",
+        "          6       0.50      1.00      0.67         1\n",
+        "          7       1.00      0.67      0.80         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.92      0.87      0.87        31\n"
        ]
       },
       {
@@ -1577,12 +1609,12 @@
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 1 2 0 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
-        "          1       1.00      0.50      0.67         4\n",
+        "          1       1.00      0.25      0.40         4\n",
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
@@ -1591,10 +1623,10 @@
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
-        "          8       1.00      0.75      0.86         4\n",
+        "          8       0.75      0.75      0.75         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.89      0.81      0.79        31\n"
        ]
       },
       {
@@ -1602,7 +1634,7 @@
        "stream": "stdout",
        "text": [
         "\n",
-        "[[2 0 2 0 0 0 0 0 0 0 0]\n",
+        "[[1 0 2 0 0 0 0 0 0 1 0]\n",
         " [0 2 0 0 0 0 0 0 0 0 0]\n",
         " [0 0 3 0 0 0 0 0 0 0 0]\n",
         " [0 0 0 3 0 0 0 0 0 0 0]\n",
@@ -1619,15 +1651,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -1644,7 +1676,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -1688,12 +1720,12 @@
         "          3       1.00      1.00      1.00         2\n",
         "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.33      1.00      0.50         1\n",
-        "          7       1.00      0.33      0.50         3\n",
+        "          6       0.50      1.00      0.67         1\n",
+        "          7       1.00      0.67      0.80         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.91      0.84      0.84        31\n"
+        "avg / total       0.92      0.87      0.87        31\n"
        ]
       },
       {
@@ -1709,7 +1741,7 @@
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 0 0 0 1 2 0 0]\n",
         " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
@@ -1718,15 +1750,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -1743,7 +1775,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -1752,14 +1784,14 @@
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
         "          3       1.00      1.00      1.00         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       0.75      1.00      0.86         3\n",
+        "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -1776,7 +1808,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 0 0 0 0 0 3 1]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -1784,15 +1816,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
-        "          4       1.00      1.00      1.00         4\n",
+        "          3       1.00      1.00      1.00         2\n",
+        "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.92      0.84      0.84        31\n"
+        "avg / total       0.91      0.84      0.84        31\n"
        ]
       },
       {
@@ -1809,7 +1841,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -1817,15 +1849,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       1.00      1.00      1.00         2\n",
-        "          4       0.80      1.00      0.89         4\n",
+        "          3       0.67      1.00      0.80         2\n",
+        "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.91      0.84      0.84        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -1842,7 +1874,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 0 1 0 0 0 3 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -1952,12 +1984,12 @@
         "          3       1.00      1.00      1.00         2\n",
         "          4       0.80      1.00      0.89         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.33      1.00      0.50         1\n",
-        "          7       1.00      0.33      0.50         3\n",
+        "          6       0.50      1.00      0.67         1\n",
+        "          7       1.00      0.67      0.80         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.91      0.84      0.84        31\n"
+        "avg / total       0.92      0.87      0.87        31\n"
        ]
       },
       {
@@ -1973,7 +2005,7 @@
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 2 1 0 0]\n",
+        " [0 0 0 0 0 0 0 1 2 0 0]\n",
         " [0 0 0 0 0 1 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
@@ -1982,15 +2014,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       1.00      1.00      1.00         2\n",
-        "          4       0.80      1.00      0.89         4\n",
+        "          3       0.67      1.00      0.80         2\n",
+        "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.91      0.84      0.84        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -2007,7 +2039,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 0 1 0 0 0 3 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -2016,14 +2048,14 @@
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
         "          3       1.00      1.00      1.00         2\n",
-        "          4       0.80      1.00      0.89         4\n",
+        "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
-        "          6       0.33      1.00      0.50         1\n",
-        "          7       1.00      0.33      0.50         3\n",
+        "          6       0.50      1.00      0.67         1\n",
+        "          7       1.00      0.67      0.80         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          9       0.75      1.00      0.86         3\n",
         "\n",
-        "avg / total       0.91      0.84      0.84        31\n"
+        "avg / total       0.92      0.87      0.87        31\n"
        ]
       },
       {
@@ -2039,8 +2071,8 @@
         " [0 0 0 0 0 4 0 0 0 0 0]\n",
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
-        " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 0 1 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 1 2 0 0]\n",
+        " [0 0 0 0 0 0 0 0 0 3 1]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -2048,13 +2080,13 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       0.67      1.00      0.80         2\n",
+        "          3       1.00      1.00      1.00         2\n",
         "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
-        "          9       1.00      1.00      1.00         3\n",
+        "          9       0.75      1.00      0.86         3\n",
         "\n",
         "avg / total       0.92      0.84      0.84        31\n"
        ]
@@ -2073,7 +2105,7 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 1 0 0 0 0 3 0]\n",
+        " [0 0 0 0 0 0 0 0 0 3 1]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n",
         "             precision    recall  f1-score   support\n",
         "\n",
@@ -2081,15 +2113,15 @@
         "         10       1.00      1.00      1.00         2\n",
         "         11       0.60      1.00      0.75         3\n",
         "          2       1.00      1.00      1.00         3\n",
-        "          3       1.00      1.00      1.00         2\n",
-        "          4       0.80      1.00      0.89         4\n",
+        "          3       0.67      1.00      0.80         2\n",
+        "          4       1.00      1.00      1.00         4\n",
         "          5       1.00      1.00      1.00         2\n",
         "          6       0.33      1.00      0.50         1\n",
         "          7       1.00      0.33      0.50         3\n",
         "          8       1.00      0.75      0.86         4\n",
         "          9       1.00      1.00      1.00         3\n",
         "\n",
-        "avg / total       0.91      0.84      0.84        31\n"
+        "avg / total       0.92      0.84      0.84        31\n"
        ]
       },
       {
@@ -2106,69 +2138,69 @@
         " [0 0 0 0 0 0 2 0 0 0 0]\n",
         " [0 0 0 0 0 0 0 1 0 0 0]\n",
         " [0 0 0 0 0 0 0 2 1 0 0]\n",
-        " [0 0 0 0 0 1 0 0 0 3 0]\n",
+        " [0 0 0 0 1 0 0 0 0 3 0]\n",
         " [0 0 0 0 0 0 0 0 0 0 3]]\n"
        ]
       },
       {
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 5,
+       "prompt_number": 15,
        "text": [
-        "[(20, 0.86991807475678429),\n",
-        " (21, 0.87043010752688177),\n",
-        " (22, 0.82219662058371723),\n",
-        " (23, 0.793010752688172),\n",
-        " (24, 0.83550947260624675),\n",
-        " (25, 0.86991807475678429),\n",
+        "[(20, 0.79124423963133639),\n",
+        " (21, 0.83694316436251914),\n",
+        " (22, 0.83694316436251914),\n",
+        " (23, 0.78727598566308243),\n",
+        " (24, 0.86991807475678429),\n",
+        " (25, 0.86827956989247301),\n",
         " (26, 0.83550947260624675),\n",
         " (27, 0.83550947260624675),\n",
-        " (28, 0.87135176651305668),\n",
-        " (29, 0.82311827956989247),\n",
+        " (28, 0.83550947260624675),\n",
+        " (29, 0.86991807475678429),\n",
         " (30, 0.83550947260624675),\n",
-        " (31, 0.83694316436251914),\n",
+        " (31, 0.78870967741935483),\n",
         " (32, 0.83694316436251914),\n",
-        " (33, 0.83550947260624675),\n",
-        " (34, 0.83550947260624675),\n",
-        " (35, 0.83550947260624675),\n",
-        " (36, 0.86827956989247301),\n",
-        " (37, 0.78870967741935483),\n",
+        " (33, 0.78727598566308243),\n",
+        " (34, 0.86991807475678429),\n",
+        " (35, 0.87135176651305668),\n",
+        " (36, 0.83550947260624675),\n",
+        " (37, 0.86991807475678429),\n",
         " (38, 0.83550947260624675),\n",
-        " (39, 0.83550947260624675),\n",
+        " (39, 0.83694316436251914),\n",
         " (40, 0.83550947260624675),\n",
-        " (41, 0.83550947260624675),\n",
+        " (41, 0.83694316436251914),\n",
         " (42, 0.83550947260624675),\n",
-        " (43, 0.83694316436251914),\n",
-        " (44, 0.83550947260624675),\n",
+        " (43, 0.83550947260624675),\n",
+        " (44, 0.83602150537634401),\n",
         " (45, 0.83550947260624675),\n",
         " (46, 0.83602150537634401),\n",
-        " (47, 0.83694316436251914),\n",
-        " (48, 0.83694316436251914),\n",
-        " (49, 0.83550947260624675),\n",
-        " (50, 0.83550947260624675),\n",
-        " (51, 0.83694316436251914),\n",
+        " (47, 0.83602150537634401),\n",
+        " (48, 0.83550947260624675),\n",
+        " (49, 0.87135176651305668),\n",
+        " (50, 0.83694316436251914),\n",
+        " (51, 0.83550947260624675),\n",
         " (52, 0.83694316436251914),\n",
-        " (53, 0.83694316436251914),\n",
-        " (54, 0.83694316436251914),\n",
-        " (55, 0.83694316436251914),\n",
+        " (53, 0.86991807475678429),\n",
+        " (54, 0.78870967741935483),\n",
+        " (55, 0.83550947260624675),\n",
         " (56, 0.83550947260624675),\n",
-        " (57, 0.83550947260624675),\n",
-        " (58, 0.83694316436251914),\n",
-        " (59, 0.83602150537634401),\n",
-        " (60, 0.83694316436251914),\n",
-        " (61, 0.83550947260624675),\n",
+        " (57, 0.86991807475678429),\n",
+        " (58, 0.83550947260624675),\n",
+        " (59, 0.83550947260624675),\n",
+        " (60, 0.83550947260624675),\n",
+        " (61, 0.83694316436251914),\n",
         " (62, 0.83550947260624675),\n",
         " (63, 0.83550947260624675),\n",
         " (64, 0.83550947260624675),\n",
-        " (65, 0.83550947260624675),\n",
-        " (66, 0.83550947260624675),\n",
-        " (67, 0.83550947260624675),\n",
-        " (68, 0.83694316436251914),\n",
-        " (69, 0.83550947260624675)]"
+        " (65, 0.86991807475678429),\n",
+        " (66, 0.83694316436251914),\n",
+        " (67, 0.87043010752688177),\n",
+        " (68, 0.83602150537634401),\n",
+        " (69, 0.83694316436251914)]"
        ]
       }
      ],
-     "prompt_number": 5
+     "prompt_number": 15
     },
     {
      "cell_type": "code",
@@ -2184,13 +2216,13 @@
       {
        "metadata": {},
        "output_type": "display_data",
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7KPQJdtoCbDqZDZMq/Ciz/LwKqE2q8NfXRD2dbrSB7bxnr6Wz5ZEpsmr4Hf4+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\nRfj/AVqKnSI9NotsAAAAAElFTkSuQmCC\n",
        "text": [
-        "<matplotlib.figure.Figure at 0x10cd1bda0>"
+        "<matplotlib.figure.Figure at 0x10c3e3b70>"
        ]
       }
      ],
-     "prompt_number": 6
+     "prompt_number": 16
     },
     {
      "cell_type": "heading",
@@ -2217,7 +2249,7 @@
       "    request_df = request.compl_df_build()\n",
       "\n",
       "    # Run model\n",
-      "    model_created = RandomForestClassifier(50)\n",
+      "    model_created = RandomForestClassifier(40)\n",
       "    model_created.fit(corp_train, corp_answer)\n",
       "    predicted = model_created.predict(request_df.values)\n",
       "    predict_prob = model_created.predict_proba(request_df.values)\n",
@@ -2230,7 +2262,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 7
+     "prompt_number": 17
     },
     {
      "cell_type": "code",
@@ -2244,23 +2276,23 @@
       {
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 8,
+       "prompt_number": 22,
        "text": [
-        "[('java', 0.46000000000000002),\n",
-        " ('ruby', 0.20000000000000001),\n",
-        " ('scheme', 0.16),\n",
-        " ('clojure', 0.059999999999999998),\n",
-        " ('python', 0.059999999999999998),\n",
-        " ('haskell', 0.040000000000000001),\n",
-        " ('php', 0.02),\n",
+        "[('java', 0.52500000000000002),\n",
+        " ('ruby', 0.17499999999999999),\n",
+        " ('clojure', 0.10000000000000001),\n",
+        " ('scheme', 0.074999999999999997),\n",
+        " ('haskell', 0.074999999999999997),\n",
+        " ('python', 0.050000000000000003),\n",
         " ('scala', 0.0),\n",
         " ('javascript', 0.0),\n",
         " ('ocaml', 0.0),\n",
-        " ('perl', 0.0)]"
+        " ('perl', 0.0),\n",
+        " ('php', 0.0)]"
        ]
       }
      ],
-     "prompt_number": 8
+     "prompt_number": 22
     },
     {
      "cell_type": "heading",
@@ -2294,7 +2326,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 9
+     "prompt_number": 19
     },
     {
      "cell_type": "code",
@@ -2316,23 +2348,23 @@
       {
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 10,
+       "prompt_number": 20,
        "text": [
-        "[('ocaml', 0.66000000000000003),\n",
-        " ('clojure', 0.12),\n",
-        " ('scheme', 0.12),\n",
-        " ('python', 0.040000000000000001),\n",
+        "[('ocaml', 0.57999999999999996),\n",
+        " ('clojure', 0.14000000000000001),\n",
+        " ('scheme', 0.080000000000000002),\n",
+        " ('haskell', 0.080000000000000002),\n",
+        " ('python', 0.059999999999999998),\n",
         " ('ruby', 0.040000000000000001),\n",
-        " ('haskell', 0.02),\n",
+        " ('perl', 0.02),\n",
         " ('scala', 0.0),\n",
         " ('java', 0.0),\n",
         " ('javascript', 0.0),\n",
-        " ('perl', 0.0),\n",
         " ('php', 0.0)]"
        ]
       }
      ],
-     "prompt_number": 10
+     "prompt_number": 20
     },
     {
      "cell_type": "code",
@@ -2341,7 +2373,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 10
+     "prompt_number": 20
     },
     {
      "cell_type": "code",
@@ -2350,7 +2382,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 10
+     "prompt_number": 20
     },
     {
      "cell_type": "code",
@@ -2359,7 +2391,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 10
+     "prompt_number": 20
     },
     {
      "cell_type": "code",
@@ -2368,7 +2400,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 10
+     "prompt_number": 20
     },
     {
      "cell_type": "code",
@@ -2377,7 +2409,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 10
+     "prompt_number": 20
     }
    ],
    "metadata": {}