test_alt_subset.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "from scipy.stats import hmean\n",
    "import lda\n",
    "from sklearn.metrics import roc_auc_score, roc_curve, auc, \\\n",
    "                            precision_recall_curve, average_precision_score\n",
    "\n",
    "import tokenizers as t\n",
    "import lda_implementation\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# read in data (2nd subset)\n",
    "filtered_10K = pd.read_csv('datasets/2nd_10K_filtered_restaurant_reviews.csv', encoding='utf-8')\n",
    "\n",
    "coded = pd.read_excel('datasets/manually_coded_reviews.xlsx', encoding='utf-8')\n",
    "coded.fillna(0, inplace=True)\n",
    "coded['serv'] = (coded.service + coded.staff).apply(lambda x: 1 if x > 0 else 0)\n",
    "coded['pos_serv'] = (coded.pos_service + coded.pos_staff).apply(lambda x: 1 if x > 0 else 0)\n",
    "coded['neg_serv'] = (coded.neg_service + coded.neg_staff).apply(lambda x: 1 if x > 0 else 0)\n",
    "coded.drop(['service', 'staff', 'pos_service', 'pos_staff', 'neg_service', 'neg_staff'], axis=1, inplace=True)\n",
    "coded.drop(['ambiance', 'cleanliness', 'pos_amb', u'neg_amb', 'pos_clean', 'neg_clean'], axis=1, inplace=True)\n",
    "\n",
    "rest1 = pd.read_excel('datasets/one_business_categorized.xlsx', encoding='utf-8')\n",
    "rest1.fillna(0, inplace=True)\n",
    "rest1['serv'] = (rest1.service + rest1.staff).apply(lambda x: 1 if x > 0 else 0)\n",
    "rest1['pos_serv'] = (rest1.pos_service + rest1.pos_staff).apply(lambda x: 1 if x > 0 else 0)\n",
    "rest1['neg_serv'] = (rest1.neg_service + rest1.neg_staff).apply(lambda x: 1 if x > 0 else 0)\n",
    "rest1.drop(['service', 'staff', 'pos_service', 'pos_staff', 'neg_service', 'neg_staff'], axis=1, inplace=True)\n",
    "rest1.drop(['ambiance', 'cleanliness', 'pos_amb', u'neg_amb', 'pos_clean', 'neg_clean'], axis=1, inplace=True)\n",
    "\n",
    "rest2 = pd.read_excel('datasets/cat20rest1.xlsx', encoding='utf-8')\n",
    "rest2.fillna(0, inplace=True)\n",
    "rest2['serv'] = (rest2.service + rest2.staff).apply(lambda x: 1 if x > 0 else 0)\n",
    "rest2['pos_serv'] = (rest2.pos_service + rest2.pos_staff).apply(lambda x: 1 if x > 0 else 0)\n",
    "rest2['neg_serv'] = (rest2.neg_service + rest2.neg_staff).apply(lambda x: 1 if x > 0 else 0)\n",
    "rest2.drop(['service', 'staff', 'pos_service', 'pos_staff', 'neg_service', 'neg_staff'], axis=1, inplace=True)\n",
    "rest2.drop(['ambiance', 'cleanliness', 'pos_amb', u'neg_amb', 'pos_clean', 'neg_clean'], axis=1, inplace=True)\n",
    "\n",
    "rest3 = pd.read_excel('datasets/cat20rest2.xlsx', encoding='utf-8')\n",
    "rest3.fillna(0, inplace=True)\n",
    "rest3['serv'] = (rest3.service + rest3.staff).apply(lambda x: 1 if x > 0 else 0)\n",
    "rest3['pos_serv'] = (rest3.pos_service + rest3.pos_staff).apply(lambda x: 1 if x > 0 else 0)\n",
    "rest3['neg_serv'] = (rest3.neg_service + rest3.neg_staff).apply(lambda x: 1 if x > 0 else 0)\n",
    "rest3.drop(['service', 'staff', 'pos_service', 'pos_staff', 'neg_service', 'neg_staff'], axis=1, inplace=True)\n",
    "rest3.drop(['ambiance', 'cleanliness', 'pos_amb', u'neg_amb', 'pos_clean', 'neg_clean'], axis=1, inplace=True)\n",
    "\n",
    "rest4 = pd.read_excel('datasets/cat20rest3.xlsx', encoding='utf-8')\n",
    "rest4.fillna(0, inplace=True)\n",
    "rest4['serv'] = (rest4.service + rest4.staff).apply(lambda x: 1 if x > 0 else 0)\n",
    "rest4['pos_serv'] = (rest4.pos_service + rest4.pos_staff).apply(lambda x: 1 if x > 0 else 0)\n",
    "rest4['neg_serv'] = (rest4.neg_service + rest4.neg_staff).apply(lambda x: 1 if x > 0 else 0)\n",
    "rest4.drop(['service', 'staff', 'pos_service', 'pos_staff', 'neg_service', 'neg_staff'], axis=1, inplace=True)\n",
    "rest4.drop(['ambiance', 'cleanliness', 'pos_amb', u'neg_amb', 'pos_clean', 'neg_clean'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Perform LDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# prepare\n",
    "cout_vect, rev_vec, rev_badlines = t.fitApplyVectorizer(filtered_10K.text, t.foodwordPolarityTokenizer)\n",
    "reviews = filtered_10K.copy()\n",
    "reviews = reviews[reviews.text.apply(lambda x: False if x in rev_badlines else True)]\n",
    "\n",
    "code_vec, code_badlines = t.applyVectorizer(coded.text, t.foodwordPolarityTokenizer, cout_vect)\n",
    "code_rev = coded.copy()\n",
    "code_rev = code_rev[code_rev.text.apply(lambda x: False if x in code_badlines else True)]\n",
    "\n",
    "rest1_vec, rest1_badlines = t.applyVectorizer(rest1.text, t.foodwordPolarityTokenizer, cout_vect)\n",
    "rest1_rev = rest1.copy()\n",
    "rest1_rev = rest1_rev[rest1_rev.text.apply(lambda x: False if x in code_badlines else True)]\n",
    "\n",
    "rest2_vec, rest2_badlines = t.applyVectorizer(rest2.text, t.foodwordPolarityTokenizer, cout_vect)\n",
    "rest2_rev = rest2.copy()\n",
    "rest2_rev = rest2_rev[rest2_rev.text.apply(lambda x: False if x in code_badlines else True)]\n",
    "\n",
    "rest3_vec, rest3_badlines = t.applyVectorizer(rest3.text, t.foodwordPolarityTokenizer, cout_vect)\n",
    "rest3_rev = rest3.copy()\n",
    "rest3_rev = rest3_rev[rest3_rev.text.apply(lambda x: False if x in code_badlines else True)]\n",
    "\n",
    "rest4_vec, rest4_badlines = t.applyVectorizer(rest4.text, t.foodwordPolarityTokenizer, cout_vect)\n",
    "rest4_rev = rest4.copy()\n",
    "rest4_rev = rest4_rev[rest4_rev.text.apply(lambda x: False if x in code_badlines else True)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:lda:n_documents: 9720\n",
      "INFO:lda:vocab_size: 19828\n",
      "INFO:lda:n_words: 636471\n",
      "INFO:lda:n_topics: 20\n",
      "INFO:lda:n_iter: 2000\n",
      "WARNING:lda:all zero row in document-term matrix found\n",
      "INFO:lda:<0> log likelihood: -6525808\n",
      "INFO:lda:<10> log likelihood: -5105033\n",
      "INFO:lda:<20> log likelihood: -4905774\n",
      "INFO:lda:<30> log likelihood: -4812305\n",
      "INFO:lda:<40> log likelihood: -4763327\n",
      "INFO:lda:<50> log likelihood: -4732065\n",
      "INFO:lda:<60> log likelihood: -4707262\n",
      "INFO:lda:<70> log likelihood: -4690435\n",
      "INFO:lda:<80> log likelihood: -4677105\n",
      "INFO:lda:<90> log likelihood: -4666380\n",
      "INFO:lda:<100> log likelihood: -4657755\n",
      "INFO:lda:<110> log likelihood: -4647415\n",
      "INFO:lda:<120> log likelihood: -4644679\n",
      "INFO:lda:<130> log likelihood: -4638895\n",
      "INFO:lda:<140> log likelihood: -4633075\n",
      "INFO:lda:<150> log likelihood: -4627925\n",
      "INFO:lda:<160> log likelihood: -4625528\n",
      "INFO:lda:<170> log likelihood: -4622658\n",
      "INFO:lda:<180> log likelihood: -4621482\n",
      "INFO:lda:<190> log likelihood: -4615660\n",
      "INFO:lda:<200> log likelihood: -4614925\n",
      "INFO:lda:<210> log likelihood: -4613466\n",
      "INFO:lda:<220> log likelihood: -4609950\n",
      "INFO:lda:<230> log likelihood: -4611798\n",
      "INFO:lda:<240> log likelihood: -4608126\n",
      "INFO:lda:<250> log likelihood: -4606321\n",
      "INFO:lda:<260> log likelihood: -4606354\n",
      "INFO:lda:<270> log likelihood: -4604410\n",
      "INFO:lda:<280> log likelihood: -4603571\n",
      "INFO:lda:<290> log likelihood: -4601980\n",
      "INFO:lda:<300> log likelihood: -4601018\n",
      "INFO:lda:<310> log likelihood: -4602867\n",
      "INFO:lda:<320> log likelihood: -4598719\n",
      "INFO:lda:<330> log likelihood: -4601370\n",
      "INFO:lda:<340> log likelihood: -4599606\n",
      "INFO:lda:<350> log likelihood: -4597204\n",
      "INFO:lda:<360> log likelihood: -4599184\n",
      "INFO:lda:<370> log likelihood: -4596961\n",
      "INFO:lda:<380> log likelihood: -4595246\n",
      "INFO:lda:<390> log likelihood: -4594621\n",
      "INFO:lda:<400> log likelihood: -4593541\n",
      "INFO:lda:<410> log likelihood: -4595271\n",
      "INFO:lda:<420> log likelihood: -4594545\n",
      "INFO:lda:<430> log likelihood: -4592215\n",
      "INFO:lda:<440> log likelihood: -4593724\n",
      "INFO:lda:<450> log likelihood: -4594103\n",
      "INFO:lda:<460> log likelihood: -4592488\n",
      "INFO:lda:<470> log likelihood: -4591829\n",
      "INFO:lda:<480> log likelihood: -4592504\n",
      "INFO:lda:<490> log likelihood: -4592450\n",
      "INFO:lda:<500> log likelihood: -4589986\n",
      "INFO:lda:<510> log likelihood: -4590479\n",
      "INFO:lda:<520> log likelihood: -4587188\n",
      "INFO:lda:<530> log likelihood: -4585948\n",
      "INFO:lda:<540> log likelihood: -4588084\n",
      "INFO:lda:<550> log likelihood: -4589806\n",
      "INFO:lda:<560> log likelihood: -4584561\n",
      "INFO:lda:<570> log likelihood: -4586559\n",
      "INFO:lda:<580> log likelihood: -4584743\n",
      "INFO:lda:<590> log likelihood: -4585165\n",
      "INFO:lda:<600> log likelihood: -4586703\n",
      "INFO:lda:<610> log likelihood: -4584152\n",
      "INFO:lda:<620> log likelihood: -4585150\n",
      "INFO:lda:<630> log likelihood: -4582571\n",
      "INFO:lda:<640> log likelihood: -4584414\n",
      "INFO:lda:<650> log likelihood: -4582751\n",
      "INFO:lda:<660> log likelihood: -4584021\n",
      "INFO:lda:<670> log likelihood: -4580638\n",
      "INFO:lda:<680> log likelihood: -4581987\n",
      "INFO:lda:<690> log likelihood: -4582618\n",
      "INFO:lda:<700> log likelihood: -4581906\n",
      "INFO:lda:<710> log likelihood: -4584448\n",
      "INFO:lda:<720> log likelihood: -4581503\n",
      "INFO:lda:<730> log likelihood: -4581338\n",
      "INFO:lda:<740> log likelihood: -4582008\n",
      "INFO:lda:<750> log likelihood: -4584997\n",
      "INFO:lda:<760> log likelihood: -4584076\n",
      "INFO:lda:<770> log likelihood: -4580795\n",
      "INFO:lda:<780> log likelihood: -4580786\n",
      "INFO:lda:<790> log likelihood: -4579256\n",
      "INFO:lda:<800> log likelihood: -4579364\n",
      "INFO:lda:<810> log likelihood: -4578549\n",
      "INFO:lda:<820> log likelihood: -4579616\n",
      "INFO:lda:<830> log likelihood: -4580169\n",
      "INFO:lda:<840> log likelihood: -4579973\n",
      "INFO:lda:<850> log likelihood: -4578913\n",
      "INFO:lda:<860> log likelihood: -4579902\n",
      "INFO:lda:<870> log likelihood: -4579931\n",
      "INFO:lda:<880> log likelihood: -4578552\n",
      "INFO:lda:<890> log likelihood: -4579380\n",
      "INFO:lda:<900> log likelihood: -4578984\n",
      "INFO:lda:<910> log likelihood: -4578061\n",
      "INFO:lda:<920> log likelihood: -4577570\n",
      "INFO:lda:<930> log likelihood: -4576125\n",
      "INFO:lda:<940> log likelihood: -4579582\n",
      "INFO:lda:<950> log likelihood: -4579168\n",
      "INFO:lda:<960> log likelihood: -4577238\n",
      "INFO:lda:<970> log likelihood: -4577455\n",
      "INFO:lda:<980> log likelihood: -4576178\n",
      "INFO:lda:<990> log likelihood: -4577565\n",
      "INFO:lda:<1000> log likelihood: -4576806\n",
      "INFO:lda:<1010> log likelihood: -4576696\n",
      "INFO:lda:<1020> log likelihood: -4578240\n",
      "INFO:lda:<1030> log likelihood: -4579064\n",
      "INFO:lda:<1040> log likelihood: -4579540\n",
      "INFO:lda:<1050> log likelihood: -4580625\n",
      "INFO:lda:<1060> log likelihood: -4577934\n",
      "INFO:lda:<1070> log likelihood: -4577612\n",
      "INFO:lda:<1080> log likelihood: -4578717\n",
      "INFO:lda:<1090> log likelihood: -4578387\n",
      "INFO:lda:<1100> log likelihood: -4577443\n",
      "INFO:lda:<1110> log likelihood: -4578064\n",
      "INFO:lda:<1120> log likelihood: -4576347\n",
      "INFO:lda:<1130> log likelihood: -4577398\n",
      "INFO:lda:<1140> log likelihood: -4578222\n",
      "INFO:lda:<1150> log likelihood: -4575645\n",
      "INFO:lda:<1160> log likelihood: -4577062\n",
      "INFO:lda:<1170> log likelihood: -4577260\n",
      "INFO:lda:<1180> log likelihood: -4577394\n",
      "INFO:lda:<1190> log likelihood: -4577340\n",
      "INFO:lda:<1200> log likelihood: -4580204\n",
      "INFO:lda:<1210> log likelihood: -4579909\n",
      "INFO:lda:<1220> log likelihood: -4580539\n",
      "INFO:lda:<1230> log likelihood: -4576197\n",
      "INFO:lda:<1240> log likelihood: -4575080\n",
      "INFO:lda:<1250> log likelihood: -4578131\n",
      "INFO:lda:<1260> log likelihood: -4575356\n",
      "INFO:lda:<1270> log likelihood: -4575390\n",
      "INFO:lda:<1280> log likelihood: -4576956\n",
      "INFO:lda:<1290> log likelihood: -4577370\n",
      "INFO:lda:<1300> log likelihood: -4575771\n",
      "INFO:lda:<1310> log likelihood: -4576750\n",
      "INFO:lda:<1320> log likelihood: -4578078\n",
      "INFO:lda:<1330> log likelihood: -4577246\n",
      "INFO:lda:<1340> log likelihood: -4576362\n",
      "INFO:lda:<1350> log likelihood: -4576789\n",
      "INFO:lda:<1360> log likelihood: -4576475\n",
      "INFO:lda:<1370> log likelihood: -4576891\n",
      "INFO:lda:<1380> log likelihood: -4577760\n",
      "INFO:lda:<1390> log likelihood: -4574096\n",
      "INFO:lda:<1400> log likelihood: -4578446\n",
      "INFO:lda:<1410> log likelihood: -4579592\n",
      "INFO:lda:<1420> log likelihood: -4574600\n",
      "INFO:lda:<1430> log likelihood: -4575982\n",
      "INFO:lda:<1440> log likelihood: -4572934\n",
      "INFO:lda:<1450> log likelihood: -4576736\n",
      "INFO:lda:<1460> log likelihood: -4576640\n",
      "INFO:lda:<1470> log likelihood: -4575825\n",
      "INFO:lda:<1480> log likelihood: -4576466\n",
      "INFO:lda:<1490> log likelihood: -4575943\n",
      "INFO:lda:<1500> log likelihood: -4576455\n",
      "INFO:lda:<1510> log likelihood: -4574763\n",
      "INFO:lda:<1520> log likelihood: -4577016\n",
      "INFO:lda:<1530> log likelihood: -4575215\n",
      "INFO:lda:<1540> log likelihood: -4574091\n",
      "INFO:lda:<1550> log likelihood: -4573123\n",
      "INFO:lda:<1560> log likelihood: -4575389\n",
      "INFO:lda:<1570> log likelihood: -4574706\n",
      "INFO:lda:<1580> log likelihood: -4577197\n",
      "INFO:lda:<1590> log likelihood: -4576116\n",
      "INFO:lda:<1600> log likelihood: -4576858\n",
      "INFO:lda:<1610> log likelihood: -4575409\n",
      "INFO:lda:<1620> log likelihood: -4572942\n",
      "INFO:lda:<1630> log likelihood: -4572941\n",
      "INFO:lda:<1640> log likelihood: -4572878\n",
      "INFO:lda:<1650> log likelihood: -4571844\n",
      "INFO:lda:<1660> log likelihood: -4575187\n",
      "INFO:lda:<1670> log likelihood: -4573646\n",
      "INFO:lda:<1680> log likelihood: -4574465\n",
      "INFO:lda:<1690> log likelihood: -4573272\n",
      "INFO:lda:<1700> log likelihood: -4571681\n",
      "INFO:lda:<1710> log likelihood: -4572964\n",
      "INFO:lda:<1720> log likelihood: -4574537\n",
      "INFO:lda:<1730> log likelihood: -4573201\n",
      "INFO:lda:<1740> log likelihood: -4575216\n",
      "INFO:lda:<1750> log likelihood: -4573099\n",
      "INFO:lda:<1760> log likelihood: -4573455\n",
      "INFO:lda:<1770> log likelihood: -4575266\n",
      "INFO:lda:<1780> log likelihood: -4574009\n",
      "INFO:lda:<1790> log likelihood: -4574228\n",
      "INFO:lda:<1800> log likelihood: -4570966\n",
      "INFO:lda:<1810> log likelihood: -4572139\n",
      "INFO:lda:<1820> log likelihood: -4571907\n",
      "INFO:lda:<1830> log likelihood: -4571705\n",
      "INFO:lda:<1840> log likelihood: -4572001\n",
      "INFO:lda:<1850> log likelihood: -4571829\n",
      "INFO:lda:<1860> log likelihood: -4571993\n",
      "INFO:lda:<1870> log likelihood: -4570771\n",
      "INFO:lda:<1880> log likelihood: -4573077\n",
      "INFO:lda:<1890> log likelihood: -4574228\n",
      "INFO:lda:<1900> log likelihood: -4572376\n",
      "INFO:lda:<1910> log likelihood: -4572120\n",
      "INFO:lda:<1920> log likelihood: -4568877\n",
      "INFO:lda:<1930> log likelihood: -4572033\n",
      "INFO:lda:<1940> log likelihood: -4573698\n",
      "INFO:lda:<1950> log likelihood: -4572506\n",
      "INFO:lda:<1960> log likelihood: -4572527\n",
      "INFO:lda:<1970> log likelihood: -4570864\n",
      "INFO:lda:<1980> log likelihood: -4573260\n",
      "INFO:lda:<1990> log likelihood: -4572360\n",
      "INFO:lda:<1999> log likelihood: -4571729\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<lda.lda.LDA instance at 0x126948908>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# fit\n",
    "bestLDA = lda.LDA(n_topics=20, alpha=0.1, eta=0.01, random_state=1)\n",
    "bestLDA.fit(rev_vec)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'neg_food': ('topic_0', 'topic_17'),\n",
       " 'neg_price': ('topic_0', 'topic_17'),\n",
       " 'neg_serv': ('topic_6', 'topic_19'),\n",
       " 'neg_wait': ('topic_0', 'topic_19'),\n",
       " 'pos_food': ('topic_2', 'topic_15'),\n",
       " 'pos_price': ('topic_4', 'topic_13'),\n",
       " 'pos_serv': ('topic_9',),\n",
       " 'pos_wait': ('topic_7', 'topic_13')}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "best_topics = lda_implementation.bestTopics(bestLDA, code_vec, code_rev)\n",
    "best_topics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Look at ROC, Precision-Recall Curve, and thresholds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiAAAAGJCAYAAACzcoinAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x119325350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiAAAAGJCAYAAACzcoinAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAkRERERi9/+5oxSF6M+C0QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x127d1acd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiAAAAGJCAYAAACzcoinAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1171ef390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiAAAAGJCAYAAACzcoinAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a6078d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiAAAAGJCAYAAACzcoinAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIiIiIp77f2XlzmATdRijAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10a899450>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiAAAAGJCAYAAACzcoinAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nUuMMIJIkqXEGEEmS1Lh/zDhCFcUsrj0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x128fc5150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiAAAAGJCAYAAACzcoinAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116cb9d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiAAAAGJCAYAAACzcoinAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x128fdc450>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiAAAAGJCAYAAACzcoinAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nigAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12bf6f4d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiAAAAGJCAYAAACzcoinAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niEh0KkBEREQkOhUgIiIiEt3/AcceWF6lQlX/AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12afcb2d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiAAAAGJCAYAAACzcoinAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12bf6f850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiAAAAGJCAYAAACzcoinAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQERERCQ7FSAiIiKS3f8AvFP+t4v2e+sAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12c0ed7d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiAAAAGJCAYAAACzcoinAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10eb00e90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiAAAAGJCAYAAACzcoinAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nDCCSJKk5A4gkSWrOACJJkpr7G08ss6LwC0NvAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12c402990>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiAAAAGJCAYAAACzcoinAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12c5a7610>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiAAAAGJCAYAAACzcoinAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n6gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12c593e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for column, best_tops in best_topics.items():\n",
    "    auc_df, prc_df = lda_implementation.getCurves(bestLDA, code_vec, column, best_tops, code_rev)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'neg_food': ('topic_0', 'topic_17'),\n",
       " 'neg_price': ('topic_0', 'topic_17'),\n",
       " 'neg_serv': ('topic_6', 'topic_19'),\n",
       " 'pos_food': ('topic_2', 'topic_15'),\n",
       " 'pos_serv': ('topic_9',)}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "best_topics2 = {}\n",
    "for column, best_tops in best_topics.items():\n",
    "    if column in ['pos_food', 'neg_food', 'pos_serv', 'neg_serv', 'neg_price']:\n",
    "        best_topics2[column] = best_tops\n",
    "best_topics2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n",
      "WARNING:lda:all zero column in document-term matrix found\n",
      "WARNING:lda:all zero column in document-term matrix found\n",
      "WARNING:lda:all zero column in document-term matrix found\n",
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    }
   ],
   "source": [
    "best_thresholds = {}\n",
    "for column, best_tops in best_topics2.items():\n",
    "    imp = lda_implementation.bestThreshold3(bestLDA, code_vec, column, best_tops, code_rev)\n",
    "    best_thresholds[column] = imp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'neg_food': 0.26925960009598882,\n",
       " 'neg_price': 0.23348311194622021,\n",
       " 'neg_serv': 0.22448270973670648,\n",
       " 'pos_food': 0.079143429767158671,\n",
       " 'pos_serv': 0.074970606559024572}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "best_thresholds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n",
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ACTUAL: neg_food: 0.224390243902\n",
      "PREDICTED: neg_food: 0.180487804878\n",
      "Accuracy: 0.819512195122, Precision: 0.621621621622, Recall: 0.5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ACTUAL: neg_price: 0.121951219512\n",
      "PREDICTED: neg_price: 0.20487804878\n",
      "Accuracy: 0.819512195122, Precision: 0.357142857143, Recall: 0.6\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ACTUAL: neg_serv: 0.2\n",
      "PREDICTED: neg_serv: 0.151219512195\n",
      "Accuracy: 0.843902439024, Precision: 0.645161290323, Recall: 0.487804878049\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ACTUAL: pos_food: 0.658536585366\n",
      "PREDICTED: pos_food: 0.4\n",
      "Accuracy: 0.59512195122, Precision: 0.817073170732, Recall: 0.496296296296\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n",
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ACTUAL: pos_serv: 0.385365853659\n",
      "PREDICTED: pos_serv: 0.326829268293\n",
      "Accuracy: 0.707317073171, Precision: 0.641791044776, Recall: 0.544303797468\n",
      "ACTUAL: neg_food: 0.204081632653\n",
      "PREDICTED: neg_food: 0.183673469388\n",
      "Accuracy: 0.897959183673, Precision: 0.777777777778, Recall: 0.7\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda/envs/py27/lib/python2.7/site-packages/sklearn/metrics/classification.py:1115: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 due to no true samples.\n",
      "  'recall', 'true', average, warn_for)\n",
      "WARNING:lda:all zero column in document-term matrix found\n",
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ACTUAL: neg_price: 0.0\n",
      "PREDICTED: neg_price: 0.204081632653\n",
      "Accuracy: 0.795918367347, Precision: 0.0, Recall: 0.0\n",
      "ACTUAL: neg_serv: 0.0408163265306\n",
      "PREDICTED: neg_serv: 0.0408163265306\n",
      "Accuracy: 0.918367346939, Precision: 0.0, Recall: 0.0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n",
      "WARNING:lda:all zero column in document-term matrix found\n",
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ACTUAL: pos_food: 0.775510204082\n",
      "PREDICTED: pos_food: 0.102040816327\n",
      "Accuracy: 0.285714285714, Precision: 0.8, Recall: 0.105263157895\n",
      "ACTUAL: pos_serv: 0.387755102041\n",
      "PREDICTED: pos_serv: 0.612244897959\n",
      "Accuracy: 0.530612244898, Precision: 0.433333333333, Recall: 0.684210526316\n",
      "ACTUAL: neg_food: 0.263157894737\n",
      "PREDICTED: neg_food: 0.210526315789\n",
      "Accuracy: 0.631578947368, Precision: 0.25, Recall: 0.2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n",
      "WARNING:lda:all zero column in document-term matrix found\n",
      "WARNING:lda:all zero column in document-term matrix found\n",
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ACTUAL: neg_price: 0.105263157895\n",
      "PREDICTED: neg_price: 0.315789473684\n",
      "Accuracy: 0.578947368421, Precision: 0.0, Recall: 0.0\n",
      "ACTUAL: neg_serv: 0.157894736842\n",
      "PREDICTED: neg_serv: 0.210526315789\n",
      "Accuracy: 0.947368421053, Precision: 0.75, Recall: 1.0\n",
      "ACTUAL: pos_food: 0.578947368421\n",
      "PREDICTED: pos_food: 0.315789473684\n",
      "Accuracy: 0.526315789474, Precision: 0.666666666667, Recall: 0.363636363636\n",
      "ACTUAL: pos_serv: 0.157894736842\n",
      "PREDICTED: pos_serv: 0.157894736842\n",
      "Accuracy: 0.894736842105, Precision: 0.666666666667, Recall: 0.666666666667\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n",
      "WARNING:lda:all zero column in document-term matrix found\n",
      "WARNING:lda:all zero column in document-term matrix found\n",
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ACTUAL: neg_food: 0.35\n",
      "PREDICTED: neg_food: 0.2\n",
      "Accuracy: 0.75, Precision: 0.75, Recall: 0.428571428571\n",
      "ACTUAL: neg_price: 0.05\n",
      "PREDICTED: neg_price: 0.35\n",
      "Accuracy: 0.7, Precision: 0.142857142857, Recall: 1.0\n",
      "ACTUAL: neg_serv: 0.1\n",
      "PREDICTED: neg_serv: 0.15\n",
      "Accuracy: 0.85, Precision: 0.333333333333, Recall: 0.5\n",
      "ACTUAL: pos_food: 0.65\n",
      "PREDICTED: pos_food: 0.25\n",
      "Accuracy: 0.6, Precision: 1.0, Recall: 0.384615384615\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n",
      "WARNING:lda:all zero column in document-term matrix found\n",
      "WARNING:lda:all zero column in document-term matrix found\n",
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ACTUAL: pos_serv: 0.4\n",
      "PREDICTED: pos_serv: 0.25\n",
      "Accuracy: 0.65, Precision: 0.6, Recall: 0.375\n",
      "ACTUAL: neg_food: 0.35\n",
      "PREDICTED: neg_food: 0.3\n",
      "Accuracy: 0.85, Precision: 0.833333333333, Recall: 0.714285714286\n",
      "ACTUAL: neg_price: 0.05\n",
      "PREDICTED: neg_price: 0.35\n",
      "Accuracy: 0.7, Precision: 0.142857142857, Recall: 1.0\n",
      "ACTUAL: neg_serv: 0.15\n",
      "PREDICTED: neg_serv: 0.1\n",
      "Accuracy: 0.95, Precision: 1.0, Recall: 0.666666666667\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:lda:all zero column in document-term matrix found\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ACTUAL: pos_food: 0.5\n",
      "PREDICTED: pos_food: 0.1\n",
      "Accuracy: 0.5, Precision: 0.5, Recall: 0.1\n",
      "ACTUAL: pos_serv: 0.1\n",
      "PREDICTED: pos_serv: 0.2\n",
      "Accuracy: 0.8, Precision: 0.25, Recall: 0.5\n"
     ]
    }
   ],
   "source": [
    "dic = {\"Category\": [],\n",
    "    \"Test_set_total\": [],\n",
    "    \"Test_set_PREDtotal\": [],\n",
    "    \"Test_set_accuracy\": [],\n",
    "    \"Test_set_precision\": [],\n",
    "    \"Test_set_recall\": [],\n",
    "    \"Restaurant_1_total\": [],\n",
    "    \"Restaurant_1_PREDtotal\": [],\n",
    "    \"Restaurant_1_accuracy\": [],\n",
    "    \"Restaurant_1_precision\": [],\n",
    "    \"Restaurant_1_recall\": [],\n",
    "    \"Restaurant_2_total\": [],\n",
    "    \"Restaurant_2_PREDtotal\": [],\n",
    "    \"Restaurant_2_accuracy\": [],\n",
    "    \"Restaurant_2_precision\": [],\n",
    "    \"Restaurant_2_recall\": [],\n",
    "    \"Restaurant_3_total\": [],\n",
    "    \"Restaurant_3_PREDtotal\": [],\n",
    "    \"Restaurant_3_accuracy\": [],\n",
    "    \"Restaurant_3_precision\": [],\n",
    "    \"Restaurant_3_recall\": [],\n",
    "    \"Restaurant_4_total\": [],\n",
    "    \"Restaurant_4_PREDtotal\": [],\n",
    "    \"Restaurant_4_accuracy\": [],\n",
    "    \"Restaurant_4_precision\": [],\n",
    "    \"Restaurant_4_recall\": []\n",
    "}\n",
    "for column, best_tops in best_topics2.items():\n",
    "    dic[\"Category\"] += [column]\n",
    "for column, best_tops in best_topics2.items():\n",
    "    total, PREDtotal, acc, prec, rec = lda_implementation.restaurantSummary(bestLDA, code_vec, column, best_tops, code_rev, best_thresholds[column])\n",
    "    dic[\"Test_set_total\"] += [total]\n",
    "    dic[\"Test_set_PREDtotal\"] += [PREDtotal]\n",
    "    dic[\"Test_set_accuracy\"] += [acc]\n",
    "    dic[\"Test_set_precision\"] += [prec]\n",
    "    dic[\"Test_set_recall\"] += [rec]\n",
    "for column, best_tops in best_topics2.items():\n",
    "    total, PREDtotal, acc, prec, rec = lda_implementation.restaurantSummary(bestLDA, rest1_vec, column, best_tops, rest1_rev, best_thresholds[column])\n",
    "    dic[\"Restaurant_1_total\"] += [total]\n",
    "    dic[\"Restaurant_1_PREDtotal\"] += [PREDtotal]\n",
    "    dic[\"Restaurant_1_accuracy\"] += [acc]\n",
    "    dic[\"Restaurant_1_precision\"] += [prec]\n",
    "    dic[\"Restaurant_1_recall\"] += [rec]\n",
    "for column, best_tops in best_topics2.items():\n",
    "    total, PREDtotal, acc, prec, rec = lda_implementation.restaurantSummary(bestLDA, rest2_vec, column, best_tops, rest2_rev, best_thresholds[column])\n",
    "    dic[\"Restaurant_2_total\"] += [total]\n",
    "    dic[\"Restaurant_2_PREDtotal\"] += [PREDtotal]\n",
    "    dic[\"Restaurant_2_accuracy\"] += [acc]\n",
    "    dic[\"Restaurant_2_precision\"] += [prec]\n",
    "    dic[\"Restaurant_2_recall\"] += [rec]\n",
    "for column, best_tops in best_topics2.items():\n",
    "    total, PREDtotal, acc, prec, rec = lda_implementation.restaurantSummary(bestLDA, rest3_vec, column, best_tops, rest3_rev, best_thresholds[column])\n",
    "    dic[\"Restaurant_3_total\"] += [total]\n",
    "    dic[\"Restaurant_3_PREDtotal\"] += [PREDtotal]\n",
    "    dic[\"Restaurant_3_accuracy\"] += [acc]\n",
    "    dic[\"Restaurant_3_precision\"] += [prec]\n",
    "    dic[\"Restaurant_3_recall\"] += [rec]\n",
    "for column, best_tops in best_topics2.items():\n",
    "    total, PREDtotal, acc, prec, rec = lda_implementation.restaurantSummary(bestLDA, rest4_vec, column, best_tops, rest4_rev, best_thresholds[column])\n",
    "    dic[\"Restaurant_4_total\"] += [total]\n",
    "    dic[\"Restaurant_4_PREDtotal\"] += [PREDtotal]\n",
    "    dic[\"Restaurant_4_accuracy\"] += [acc]\n",
    "    dic[\"Restaurant_4_precision\"] += [prec]\n",
    "    dic[\"Restaurant_4_recall\"] += [rec]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df = pd.DataFrame(dic)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# re-order columns\n",
    "df = df[['Category',\n",
    "    'Test_set_total',\n",
    "    'Test_set_PREDtotal',\n",
    "    'Test_set_recall',\n",
    "    'Test_set_precision',\n",
    "    'Test_set_accuracy',\n",
    "    'Restaurant_1_total',\n",
    "    'Restaurant_1_PREDtotal',\n",
    "    'Restaurant_1_recall',\n",
    "    'Restaurant_1_precision', \n",
    "    'Restaurant_1_accuracy',\n",
    "    'Restaurant_2_total',\n",
    "    'Restaurant_2_PREDtotal',\n",
    "    'Restaurant_2_recall',\n",
    "    'Restaurant_2_precision', \n",
    "    'Restaurant_2_accuracy',\n",
    "    'Restaurant_3_total',\n",
    "    'Restaurant_3_PREDtotal',\n",
    "    'Restaurant_3_recall',\n",
    "    'Restaurant_3_precision', \n",
    "    'Restaurant_3_accuracy',\n",
    "    'Restaurant_4_total',\n",
    "    'Restaurant_4_PREDtotal',\n",
    "    'Restaurant_4_recall',\n",
    "    'Restaurant_4_precision', \n",
    "    'Restaurant_4_accuracy']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Category</th>\n",
       "      <th>Test_set_total</th>\n",
       "      <th>Test_set_PREDtotal</th>\n",
       "      <th>Test_set_recall</th>\n",
       "      <th>Test_set_precision</th>\n",
       "      <th>Test_set_accuracy</th>\n",
       "      <th>Restaurant_1_total</th>\n",
       "      <th>Restaurant_1_PREDtotal</th>\n",
       "      <th>Restaurant_1_recall</th>\n",
       "      <th>Restaurant_1_precision</th>\n",
       "      <th>...</th>\n",
       "      <th>Restaurant_3_recall</th>\n",
       "      <th>Restaurant_3_precision</th>\n",
       "      <th>Restaurant_3_accuracy</th>\n",
       "      <th>Restaurant_4_total</th>\n",
       "      <th>Restaurant_4_PREDtotal</th>\n",
       "      <th>Restaurant_4_recall</th>\n",
       "      <th>Restaurant_4_precision</th>\n",
       "      <th>Restaurant_4_accuracy</th>\n",
       "      <th>average_recall</th>\n",
       "      <th>average_precision</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>neg_food</td>\n",
       "      <td>0.224390</td>\n",
       "      <td>0.180488</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.621622</td>\n",
       "      <td>0.819512</td>\n",
       "      <td>0.204082</td>\n",
       "      <td>0.183673</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>0.777778</td>\n",
       "      <td>...</td>\n",
       "      <td>0.428571</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.714286</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.85</td>\n",
       "      <td>0.508571</td>\n",
       "      <td>0.646547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>neg_price</td>\n",
       "      <td>0.121951</td>\n",
       "      <td>0.204878</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>0.357143</td>\n",
       "      <td>0.819512</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.204082</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.142857</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.35</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.142857</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.520000</td>\n",
       "      <td>0.128571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>neg_serv</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.151220</td>\n",
       "      <td>0.487805</td>\n",
       "      <td>0.645161</td>\n",
       "      <td>0.843902</td>\n",
       "      <td>0.040816</td>\n",
       "      <td>0.040816</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.85</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.530894</td>\n",
       "      <td>0.545699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>pos_food</td>\n",
       "      <td>0.658537</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>0.496296</td>\n",
       "      <td>0.817073</td>\n",
       "      <td>0.595122</td>\n",
       "      <td>0.775510</td>\n",
       "      <td>0.102041</td>\n",
       "      <td>0.105263</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.384615</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.289962</td>\n",
       "      <td>0.756748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>pos_serv</td>\n",
       "      <td>0.385366</td>\n",
       "      <td>0.326829</td>\n",
       "      <td>0.544304</td>\n",
       "      <td>0.641791</td>\n",
       "      <td>0.707317</td>\n",
       "      <td>0.387755</td>\n",
       "      <td>0.612245</td>\n",
       "      <td>0.684211</td>\n",
       "      <td>0.433333</td>\n",
       "      <td>...</td>\n",
       "      <td>0.375000</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.554036</td>\n",
       "      <td>0.518358</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Category  Test_set_total  Test_set_PREDtotal  Test_set_recall  \\\n",
       "0   neg_food        0.224390            0.180488         0.500000   \n",
       "1  neg_price        0.121951            0.204878         0.600000   \n",
       "2   neg_serv        0.200000            0.151220         0.487805   \n",
       "3   pos_food        0.658537            0.400000         0.496296   \n",
       "4   pos_serv        0.385366            0.326829         0.544304   \n",
       "\n",
       "   Test_set_precision  Test_set_accuracy  Restaurant_1_total  \\\n",
       "0            0.621622           0.819512            0.204082   \n",
       "1            0.357143           0.819512            0.000000   \n",
       "2            0.645161           0.843902            0.040816   \n",
       "3            0.817073           0.595122            0.775510   \n",
       "4            0.641791           0.707317            0.387755   \n",
       "\n",
       "   Restaurant_1_PREDtotal  Restaurant_1_recall  Restaurant_1_precision  \\\n",
       "0                0.183673             0.700000                0.777778   \n",
       "1                0.204082             0.000000                0.000000   \n",
       "2                0.040816             0.000000                0.000000   \n",
       "3                0.102041             0.105263                0.800000   \n",
       "4                0.612245             0.684211                0.433333   \n",
       "\n",
       "         ...          Restaurant_3_recall  Restaurant_3_precision  \\\n",
       "0        ...                     0.428571                0.750000   \n",
       "1        ...                     1.000000                0.142857   \n",
       "2        ...                     0.500000                0.333333   \n",
       "3        ...                     0.384615                1.000000   \n",
       "4        ...                     0.375000                0.600000   \n",
       "\n",
       "   Restaurant_3_accuracy  Restaurant_4_total  Restaurant_4_PREDtotal  \\\n",
       "0                   0.75                0.35                    0.30   \n",
       "1                   0.70                0.05                    0.35   \n",
       "2                   0.85                0.15                    0.10   \n",
       "3                   0.60                0.50                    0.10   \n",
       "4                   0.65                0.10                    0.20   \n",
       "\n",
       "   Restaurant_4_recall  Restaurant_4_precision  Restaurant_4_accuracy  \\\n",
       "0             0.714286                0.833333                   0.85   \n",
       "1             1.000000                0.142857                   0.70   \n",
       "2             0.666667                1.000000                   0.95   \n",
       "3             0.100000                0.500000                   0.50   \n",
       "4             0.500000                0.250000                   0.80   \n",
       "\n",
       "   average_recall  average_precision  \n",
       "0        0.508571           0.646547  \n",
       "1        0.520000           0.128571  \n",
       "2        0.530894           0.545699  \n",
       "3        0.289962           0.756748  \n",
       "4        0.554036           0.518358  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df['average_recall'] = (df['Test_set_recall'] + df['Restaurant_1_recall'] + \\\n",
    "    df['Restaurant_2_recall'] + df['Restaurant_3_recall'] + df['Restaurant_4_recall'])/5\n",
    "df['average_precision'] = (df['Test_set_precision'] + df['Restaurant_1_precision'] + \\\n",
    "    df['Restaurant_2_precision'] + df['Restaurant_3_precision'] + df['Restaurant_4_precision'])/5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Category</th>\n",
       "      <th>average_recall</th>\n",
       "      <th>average_precision</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>neg_food</td>\n",
       "      <td>0.508571</td>\n",
       "      <td>0.646547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>neg_price</td>\n",
       "      <td>0.520000</td>\n",
       "      <td>0.128571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>neg_serv</td>\n",
       "      <td>0.530894</td>\n",
       "      <td>0.545699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>pos_food</td>\n",
       "      <td>0.289962</td>\n",
       "      <td>0.756748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>pos_serv</td>\n",
       "      <td>0.554036</td>\n",
       "      <td>0.518358</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Category  average_recall  average_precision\n",
       "0   neg_food        0.508571           0.646547\n",
       "1  neg_price        0.520000           0.128571\n",
       "2   neg_serv        0.530894           0.545699\n",
       "3   pos_food        0.289962           0.756748\n",
       "4   pos_serv        0.554036           0.518358"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['Category', 'average_recall', 'average_precision']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The model was unable to successfully work with the Bad Price topic, and didn't work great with the Good Service topic. However, the Bad Food, Good Food, and Bad Service topics are pretty good."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Topic 0: negativeword foodword food place service bad just order time taste eat star cold restaurant say better\n",
      "Topic 1: foodword positiveword negativeword steak meal good salad order wine cook restaurant dessert dish great dinner appetizer\n",
      "Topic 2: foodword positiveword negativeword cream coffee sweet ice tea dessert chocolate cake delicious taste fresh love flavor\n",
      "Topic 3: foodword positiveword breakfast buffet egg food brunch good negativeword pancake bacon vegas line morning come eat\n",
      "Topic 4: foodword positiveword taco salsa mexican chip burrito bean good food chicken cheese negativeword sauce love tortilla\n",
      "Topic 5: foodword positiveword sushi roll fish fresh order tuna negativeword hour happy spicy oyster come good eat\n",
      "Topic 6: negativeword positiveword order time say customer ask tell just come service food location make manager know\n",
      "Topic 7: foodword positiveword burger fry negativeword cheese good dog order onion hot bun bacon shake sweet make\n",
      "Topic 8: positiveword foodword negativeword restaurant menu look make small new table experience dish visit dining serve feel\n",
      "Topic 9: positiveword foodword great food place service love amazing best staff time recommend delicious friendly make awesome\n",
      "Topic 10: positiveword negativeword foodword bar place drink night music great good person fun play pretty game really\n",
      "Topic 11: positiveword foodword beer great bar drink food good wine happy selection place service menu nice friend\n",
      "Topic 12: positiveword negativeword place time just vegas eat make best know right say try good year day\n",
      "Topic 13: positiveword foodword food good great service place price friendly nice staff fast pretty lunch time love\n",
      "Topic 14: foodword positiveword negativeword chicken sauce bbq order pork wing meat fried flavor fry try good rib\n",
      "Topic 15: foodword positiveword sandwich salad lunch chicken order bread cheese soup good place meat great try delicious\n",
      "Topic 16: foodword positiveword negativeword chicken rice dish order thai noodle food soup beef chinese fried good pho\n",
      "Topic 17: positiveword foodword negativeword good place food really just price pretty time think little star try better\n",
      "Topic 18: foodword positiveword pizza good sauce crust italian cheese order pasta salad slice negativeword fresh try garlic\n",
      "Topic 19: foodword order table come wait positiveword negativeword minute food time ask server seat service sit drink\n"
     ]
    }
   ],
   "source": [
    "topic_word = bestLDA.topic_word_\n",
    "n_top_words = 16\n",
    "for i, topic_dist in enumerate(topic_word):\n",
    "    topic_words = np.array(cout_vect.get_feature_names())[np.argsort(topic_dist)][:-(n_top_words+1):-1]\n",
    "    print(u'Topic {}: {}'.format(i, ' '.join(topic_words)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Conclusions: This model did not settle on the exact same topics, though they are similar (e.g. Topics 0 and 17 on this model, which represent \"Bad Food\", is similar to topic 13 in the original model, which represented \"Bad Food\"). The precision and recall scores here were slightly different as well, though not terribly different. Therefore, the it may be beneficial to perform this process on a larger subset of data to see if the models would converge a bit more; however, this is not entirely necessary."
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [conda env:py27]",
   "language": "python",
   "name": "conda-env-py27-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}