drug-review-analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analysis of drug reviews"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this notebook, I used Machine Learning and Natural Language Processing (NLP) technology to predict a drug rating score based on patient reviews. Learning from the experience of real people who have taken drug treatments can help other patients to find the most effective drug. The dataset is from Kaggle's website. The main goal of this notebook is using various NLP techniques to convert reviews into numerical values and then evaluate their performance in terms of text classification accuracy."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. [Exploratory Data Analysis](#1)\n",
    "2. [Text preprocessing](#2)\n",
    "3. [Word Embedding](#3)\n",
    "4. [Classification](#4)\n",
    "5. [Results Analysis](#5)\n",
    "6. [Conclusion ](#6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "# general\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from datetime import datetime\n",
    "\n",
    "# visiualization\n",
    "from wordcloud import WordCloud\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# nlp\n",
    "from collections import Counter\n",
    "import re\n",
    "from gensim.models import KeyedVectors\n",
    "from spacy.lang.en.stop_words import STOP_WORDS\n",
    "import string\n",
    "from spacy.lang.en import English\n",
    "from gensim.models import Word2Vec\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "from gensim.models.doc2vec import TaggedDocument, Doc2Vec\n",
    "\n",
    "# modeling\n",
    "from keras import Sequential\n",
    "from keras.layers import Dense, Dropout, Activation\n",
    "from keras.callbacks import ModelCheckpoint\n",
    "\n",
    "# results analysis\n",
    "from sklearn.metrics import confusion_matrix, classification_report\n",
    "from sklearn.manifold import TSNE\n",
    "from sklearn.metrics import roc_auc_score, auc, roc_curve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exploratory Data Analysis <a name='1'></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# reading data\n",
    "df_train = pd.read_csv('drugsComTrain_raw.csv')\n",
    "df_test = pd.read_csv('drugsComTest_raw.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>uniqueID</th>\n",
       "      <th>drugName</th>\n",
       "      <th>condition</th>\n",
       "      <th>review</th>\n",
       "      <th>rating</th>\n",
       "      <th>date</th>\n",
       "      <th>usefulCount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>206461</td>\n",
       "      <td>Valsartan</td>\n",
       "      <td>Left Ventricular Dysfunction</td>\n",
       "      <td>\"It has no side effect, I take it in combinati...</td>\n",
       "      <td>9</td>\n",
       "      <td>20-May-12</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>95260</td>\n",
       "      <td>Guanfacine</td>\n",
       "      <td>ADHD</td>\n",
       "      <td>\"My son is halfway through his fourth week of ...</td>\n",
       "      <td>8</td>\n",
       "      <td>27-Apr-10</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>92703</td>\n",
       "      <td>Lybrel</td>\n",
       "      <td>Birth Control</td>\n",
       "      <td>\"I used to take another oral contraceptive, wh...</td>\n",
       "      <td>5</td>\n",
       "      <td>14-Dec-09</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>138000</td>\n",
       "      <td>Ortho Evra</td>\n",
       "      <td>Birth Control</td>\n",
       "      <td>\"This is my first time using any form of birth...</td>\n",
       "      <td>8</td>\n",
       "      <td>3-Nov-15</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>35696</td>\n",
       "      <td>Buprenorphine / naloxone</td>\n",
       "      <td>Opiate Dependence</td>\n",
       "      <td>\"Suboxone has completely turned my life around...</td>\n",
       "      <td>9</td>\n",
       "      <td>27-Nov-16</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   uniqueID                  drugName                     condition  \\\n",
       "0    206461                 Valsartan  Left Ventricular Dysfunction   \n",
       "1     95260                Guanfacine                          ADHD   \n",
       "2     92703                    Lybrel                 Birth Control   \n",
       "3    138000                Ortho Evra                 Birth Control   \n",
       "4     35696  Buprenorphine / naloxone             Opiate Dependence   \n",
       "\n",
       "                                              review  rating       date  \\\n",
       "0  \"It has no side effect, I take it in combinati...       9  20-May-12   \n",
       "1  \"My son is halfway through his fourth week of ...       8  27-Apr-10   \n",
       "2  \"I used to take another oral contraceptive, wh...       5  14-Dec-09   \n",
       "3  \"This is my first time using any form of birth...       8   3-Nov-15   \n",
       "4  \"Suboxone has completely turned my life around...       9  27-Nov-16   \n",
       "\n",
       "   usefulCount  \n",
       "0           27  \n",
       "1          192  \n",
       "2           17  \n",
       "3           10  \n",
       "4           37  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>uniqueID</th>\n",
       "      <th>drugName</th>\n",
       "      <th>condition</th>\n",
       "      <th>review</th>\n",
       "      <th>rating</th>\n",
       "      <th>date</th>\n",
       "      <th>usefulCount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>163740</td>\n",
       "      <td>Mirtazapine</td>\n",
       "      <td>Depression</td>\n",
       "      <td>\"I&amp;#039;ve tried a few antidepressants over th...</td>\n",
       "      <td>10</td>\n",
       "      <td>28-Feb-12</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>206473</td>\n",
       "      <td>Mesalamine</td>\n",
       "      <td>Crohn's Disease, Maintenance</td>\n",
       "      <td>\"My son has Crohn&amp;#039;s disease and has done ...</td>\n",
       "      <td>8</td>\n",
       "      <td>17-May-09</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>159672</td>\n",
       "      <td>Bactrim</td>\n",
       "      <td>Urinary Tract Infection</td>\n",
       "      <td>\"Quick reduction of symptoms\"</td>\n",
       "      <td>9</td>\n",
       "      <td>29-Sep-17</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>39293</td>\n",
       "      <td>Contrave</td>\n",
       "      <td>Weight Loss</td>\n",
       "      <td>\"Contrave combines drugs that were used for al...</td>\n",
       "      <td>9</td>\n",
       "      <td>5-Mar-17</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>97768</td>\n",
       "      <td>Cyclafem 1 / 35</td>\n",
       "      <td>Birth Control</td>\n",
       "      <td>\"I have been on this birth control for one cyc...</td>\n",
       "      <td>9</td>\n",
       "      <td>22-Oct-15</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   uniqueID         drugName                     condition  \\\n",
       "0    163740      Mirtazapine                    Depression   \n",
       "1    206473       Mesalamine  Crohn's Disease, Maintenance   \n",
       "2    159672          Bactrim       Urinary Tract Infection   \n",
       "3     39293         Contrave                   Weight Loss   \n",
       "4     97768  Cyclafem 1 / 35                 Birth Control   \n",
       "\n",
       "                                              review  rating       date  \\\n",
       "0  \"I&#039;ve tried a few antidepressants over th...      10  28-Feb-12   \n",
       "1  \"My son has Crohn&#039;s disease and has done ...       8  17-May-09   \n",
       "2                      \"Quick reduction of symptoms\"       9  29-Sep-17   \n",
       "3  \"Contrave combines drugs that were used for al...       9   5-Mar-17   \n",
       "4  \"I have been on this birth control for one cyc...       9  22-Oct-15   \n",
       "\n",
       "   usefulCount  \n",
       "0           22  \n",
       "1           17  \n",
       "2            3  \n",
       "3           35  \n",
       "4            4  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>uniqueID</th>\n",
       "      <th>rating</th>\n",
       "      <th>usefulCount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>161297.000000</td>\n",
       "      <td>161297.000000</td>\n",
       "      <td>161297.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>115923.585305</td>\n",
       "      <td>6.994377</td>\n",
       "      <td>28.004755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>67004.445170</td>\n",
       "      <td>3.272329</td>\n",
       "      <td>36.403742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>58063.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>115744.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>16.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>173776.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>36.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>232291.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>1291.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            uniqueID         rating    usefulCount\n",
       "count  161297.000000  161297.000000  161297.000000\n",
       "mean   115923.585305       6.994377      28.004755\n",
       "std     67004.445170       3.272329      36.403742\n",
       "min         2.000000       1.000000       0.000000\n",
       "25%     58063.000000       5.000000       6.000000\n",
       "50%    115744.000000       8.000000      16.000000\n",
       "75%    173776.000000      10.000000      36.000000\n",
       "max    232291.000000      10.000000    1291.000000"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>uniqueID</th>\n",
       "      <th>rating</th>\n",
       "      <th>usefulCount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>53766.000000</td>\n",
       "      <td>53766.000000</td>\n",
       "      <td>53766.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>116386.701187</td>\n",
       "      <td>6.976900</td>\n",
       "      <td>27.989752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>67017.739881</td>\n",
       "      <td>3.285207</td>\n",
       "      <td>36.172833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>58272.500000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>116248.500000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>16.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>174586.750000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>36.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>232284.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>949.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            uniqueID        rating   usefulCount\n",
       "count   53766.000000  53766.000000  53766.000000\n",
       "mean   116386.701187      6.976900     27.989752\n",
       "std     67017.739881      3.285207     36.172833\n",
       "min         0.000000      1.000000      0.000000\n",
       "25%     58272.500000      4.000000      6.000000\n",
       "50%    116248.500000      8.000000     16.000000\n",
       "75%    174586.750000     10.000000     36.000000\n",
       "max    232284.000000     10.000000    949.000000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Insights: The dataset has 7 columns, 3 of which are utilized in this study: review, rating, and usefulCount. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Dataset Dimension: 161297 Rows, 7 Columns\n"
     ]
    },
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>uniqueID</th>\n",
       "      <th>drugName</th>\n",
       "      <th>condition</th>\n",
       "      <th>review</th>\n",
       "      <th>rating</th>\n",
       "      <th>date</th>\n",
       "      <th>usefulCount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>161297</td>\n",
       "      <td>3436</td>\n",
       "      <td>884</td>\n",
       "      <td>112329</td>\n",
       "      <td>10</td>\n",
       "      <td>3579</td>\n",
       "      <td>389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>null</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>899</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        uniqueID  drugName  condition  review  rating  date  usefulCount\n",
       "unique    161297      3436        884  112329      10  3579          389\n",
       "null           0         0        899       0       0     0            0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Training Dataset Dimension: {} Rows, {} Columns\".format(*df_train.shape))\n",
    "pd.DataFrame(data=[df_train.nunique(), df_train.isnull().sum()], index=['unique', 'null'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Testing Dataset Dimension: 53766 Rows, 7 Columns\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>uniqueID</th>\n",
       "      <th>drugName</th>\n",
       "      <th>condition</th>\n",
       "      <th>review</th>\n",
       "      <th>rating</th>\n",
       "      <th>date</th>\n",
       "      <th>usefulCount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>53766</td>\n",
       "      <td>2637</td>\n",
       "      <td>708</td>\n",
       "      <td>48280</td>\n",
       "      <td>10</td>\n",
       "      <td>3566</td>\n",
       "      <td>325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>null</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>899</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        uniqueID  drugName  condition  review  rating  date  usefulCount\n",
       "unique     53766      2637        708   48280      10  3566          325\n",
       "null           0         0        899       0       0     0            0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Testing Dataset Dimension: {} Rows, {} Columns\".format(*df_test.shape))\n",
    "pd.DataFrame(data=[df_test.nunique(), df_train.isnull().sum()], index=['unique', 'null'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Insights: There are 899 missing values in each training and testing dataset, which represents 0.05% and 1.6% of the dataset, respectively. Since the missing values consist of a small portion of the dataset, I simply drop them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train.dropna(inplace=True)\n",
    "df_test.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's take a look at the distribution of variables!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "16.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(df_train['usefulCount'])\n",
    "print(df_train['usefulCount'].median())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8.0\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='rating', data=df_train ,order=df_train['rating'].value_counts().index)\n",
    "print(df_train['rating'].median())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Insights: UsefulCount is an integer number that shows how many patients have found the review useful. It ranges from 0 to 1291, with a median of 16. \n",
    "Rating is an integer number between 1 to 10. Highly positive (9, 10) and highly negative (1) ratings are more common than neutral opinions (3,4,5)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fe540241310>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x='rating', y='usefulCount', data=df_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Insight: Highly positive and highly negative reviews have higher useful counts compare to neutral reviews. This is something that usually happens because none-neutral opinions usually contain more important information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Text preprocessing <a name='2'></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "punctuations = string.punctuation\n",
    "stopwords = STOP_WORDS\n",
    "def cleaning(sentence):\n",
    "    tokens = [tok.lemma_.lower().strip() for tok in sentence if tok.lemma_ != '-PRON-']\n",
    "    tokens = [tok for tok in tokens if tok not in stopwords and tok not in punctuations]\n",
    "    tokens = [tok for tok in tokens if tok.find('.') == -1 and tok.find(':') == -1 and tok.find('/') == -1]\n",
    "    cleaned_sentence = \" \".join(tokens)\n",
    "    return cleaned_sentence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def tokenizing(df):\n",
    "    docs = []\n",
    "    for sent in df.sents:\n",
    "        cleaned_sent = cleaning(sent)\n",
    "        docs.append(cleaned_sent)\n",
    "    return docs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# tokenizing and cleaning each sentence\n",
    "nlp = English()\n",
    "sbd = nlp.create_pipe('sentencizer')\n",
    "nlp.add_pipe(sbd)\n",
    "\n",
    "df_train['cleaned_review'] = df_train['review'].apply(lambda x: x.replace(\"'\", ''))\n",
    "df_train['cleaned_review'] = df_train['cleaned_review'].apply(lambda x: x.replace(\"&#039;\", ''))\n",
    "df_train['cleaned_review'] = df_train['cleaned_review'].apply(lambda x: re.sub('[^a-zA-Z._]', ' ', x))\n",
    "df_train['cleaned_review'] = df_train['cleaned_review'].apply(lambda x: nlp(x))\n",
    "df_train['cleaned_review'] = df_train['cleaned_review'].apply(tokenizing)\n",
    "df_train['cleaned_review'] = df_train['cleaned_review'].apply(lambda x: ' '.join(x))\n",
    "df_train['cleaned_review_sent'] = df_train['cleaned_review'].apply(lambda x: x.split())\n",
    "\n",
    "df_test['cleaned_review'] = df_test['review'].apply(lambda x: x.replace(\"'\", ''))\n",
    "df_test['cleaned_review'] = df_test['cleaned_review'].apply(lambda x: x.replace(\"&#039;\", ''))\n",
    "df_test['cleaned_review'] = df_test['cleaned_review'].apply(lambda x: re.sub('[^a-zA-Z._]', ' ', x))\n",
    "df_test['cleaned_review'] = df_test['cleaned_review'].apply(lambda x: nlp(x))\n",
    "df_test['cleaned_review'] = df_test['cleaned_review'].apply(tokenizing)\n",
    "df_test['cleaned_review'] = df_test['cleaned_review'].apply(lambda x: ' '.join(x))\n",
    "df_test['cleaned_review_sent'] = df_test['cleaned_review'].apply(lambda x: x.split())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f9e8d886a50>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# calculatin number of words in each review\n",
    "df_train['Word Count'] = df_train['cleaned_review_sent'].apply(len)\n",
    "\n",
    "fig, (ax1, ax2) = plt.subplots(1,2,figsize=(12,5))\n",
    "\n",
    "#using mean to convert the rating to low rating and high rating\n",
    "sns.kdeplot(df_train['Word Count'][df_train['rating']<=8], label='low rating', shade=True, ax=ax1)\n",
    "sns.kdeplot(df_train['Word Count'][df_train['rating']>8], label='high. rating', shade=True, ax=ax1)\n",
    "\n",
    "\n",
    "#using mean to convert the useful count to low usefulness and high usefulness\n",
    "sns.kdeplot(df_train['Word Count'][df_train['usefulCount']<=16], label='low usefulness', shade=True, ax=ax2)\n",
    "sns.kdeplot(df_train['Word Count'][df_train['usefulCount']>16], label='high usefulness', shade=True, ax=ax2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Insight: There is no significant difference between the number of words for low rating and high rating. The same is correct for useful count.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "wordcloud = WordCloud(width=600, height=375, random_state=21, max_font_size=110).generate(' '.join(df_train.review))\n",
    "plt.figure(figsize=(15, 12))\n",
    "plt.imshow(wordcloud, interpolation=\"bilinear\")\n",
    "plt.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Word Embedding <a name='3'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once we have cleaned and tokenized our reviews, we need to turn them into numerical vectors that our machine learning models can process. I use two commonly used models, namely word2vec and doc2vec for this purpose. \n",
    "Word2vec, which is a word embedding technique, represents each word with a vector space, where the location and distance between words indicate how similar they are semantical. For review classification, we need to represent the entire reviews as single vectors. The most straightforward way to do so is by taking the arithmetic mean of the words. A more sophisticated method would be using TFIDF, which penalizes common words that occur at similar frequencies in all documents. \n",
    "Doc2vec, on the other hand, creates a numeric representation of the whole document, regardless of its length. \n",
    "In the next section, I try three different approaches to calculate the embedded vectors for each review:\n",
    "1- word2vec + mean\n",
    "2- word2vec + tfidf\n",
    "3- doc2vec"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### word2vec + mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def word2vec(path, sentences, embed_size, word_window, min_word_count, nepochs):\n",
    "    print('w2v calculation is started!')\n",
    "    w2v_model = Word2Vec(sentences, size=embed_size, window=word_window, min_count=min_word_count)\n",
    "    w2v_model.train(sentences, total_examples=len(sentences), epochs=nepochs)\n",
    "    w2v_model.wv.save(path)\n",
    "    print('word2vec is calculated for the whole words')\n",
    "    return w2v_model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# trainig word2vec\n",
    "sentences = df_train['cleaned_review_sent'].to_list()\n",
    "model_w2v = word2vec('wordvectors_whole.kv', sentences, embed_size=64, word_window=5, min_word_count=1, nepochs=100)\n",
    "\n",
    "# loading word2vec\n",
    "#model_w2v = KeyedVectors.load('wordvectors_whole.kv', mmap='r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# I used tsne to convert high domentional word vectors into 2d vectors to be able to visualize them.\n",
    "def tsne_plot(text, model, min_count):\n",
    "    \"Creates and TSNE model and plots it\"\n",
    "    labels = []\n",
    "    tokens = []\n",
    "    flattened_list = [y for x in text.to_list() for y in x]\n",
    "    tokens_count = Counter(flattened_list)\n",
    "    for word in model.wv.vocab:\n",
    "        if tokens_count[word] >= min_count:\n",
    "            tokens.append(model[word])\n",
    "            labels.append(word)\n",
    "    \n",
    "    tsne_model = TSNE(perplexity=40, n_components=2, init='pca', n_iter=2500, random_state=23)\n",
    "    new_values = tsne_model.fit_transform(tokens)\n",
    "\n",
    "    x = []\n",
    "    y = []\n",
    "    for value in new_values:\n",
    "        x.append(value[0])\n",
    "        y.append(value[1])\n",
    "        \n",
    "    plt.figure(figsize=(16, 16)) \n",
    "    for i in range(len(x)):\n",
    "        plt.scatter(x[i],y[i])\n",
    "        plt.annotate(labels[i],\n",
    "                     xy=(x[i], y[i]),\n",
    "                     xytext=(5, 2),\n",
    "                     textcoords='offset points',\n",
    "                     ha='right',\n",
    "                     va='bottom')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/rmehrizi/miniconda3/lib/python3.7/site-packages/ipykernel_launcher.py:7: DeprecationWarning: Call to deprecated `wv` (Attribute will be removed in 4.0.0, use self instead).\n",
      "  import sys\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x1152 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tsne_plot(df_train.cleaned_review_sent, model_w2v, 5000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def embedding_average(text, model, embed_size):\n",
    "    docs_vector = []\n",
    "    for i in text.index:\n",
    "        docs_vector.append(make_docs_vector(text.loc[i], model, embed_size))\n",
    "    return np.array(docs_vector)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_docs_vector(text, model, embed_size):\n",
    "    words = text.split(' ')\n",
    "    doc_vec = np.zeros(embed_size)\n",
    "    count = 0\n",
    "    for word in words:\n",
    "        if word in model.wv.vocab:\n",
    "            word_vec = model.wv.get_vector(word)\n",
    "            doc_vec += word_vec\n",
    "            count += 1\n",
    "           \n",
    "    if len(text) == 0:\n",
    "        return [0] * embed_size\n",
    "    \n",
    "    if count==0:\n",
    "        return [0] * embed_size\n",
    "\n",
    "    return doc_vec/count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/rmehrizi/miniconda3/lib/python3.7/site-packages/ipykernel_launcher.py:6: DeprecationWarning: Call to deprecated `wv` (Attribute will be removed in 4.0.0, use self instead).\n",
      "  \n",
      "/home/rmehrizi/miniconda3/lib/python3.7/site-packages/ipykernel_launcher.py:7: DeprecationWarning: Call to deprecated `wv` (Attribute will be removed in 4.0.0, use self instead).\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "# word2vec + average\n",
    "x_train_w2v_ave = embedding_average(text=df_train.cleaned_review, model=model_w2v, embed_size=64)\n",
    "x_test_w2v_ave = embedding_average(text=df_test.cleaned_review, model=model_w2v, embed_size=64)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### word2vec + tfidf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def embedding_tfidf(text, model, embed_size):\n",
    "    tfidf = TfidfVectorizer(sublinear_tf=True, min_df=1, norm='l2', encoding='latin-1', ngram_range=(1, 1))\n",
    "    features = tfidf.fit_transform(text).toarray()\n",
    "    words_vector = np.zeros((features.shape[1],embed_size))\n",
    "    for k, v in tfidf.vocabulary_.items():\n",
    "        if k in model.wv.vocab:\n",
    "            words_vector[v,:] = model.wv.get_vector(k)\n",
    "    docs_vector = np.mat(features) * np.mat(words_vector)\n",
    "    return  np.squeeze(np.asarray(docs_vector))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/rmehrizi/miniconda3/lib/python3.7/site-packages/ipykernel_launcher.py:6: DeprecationWarning: Call to deprecated `wv` (Attribute will be removed in 4.0.0, use self instead).\n",
      "  \n",
      "/home/rmehrizi/miniconda3/lib/python3.7/site-packages/ipykernel_launcher.py:7: DeprecationWarning: Call to deprecated `wv` (Attribute will be removed in 4.0.0, use self instead).\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "# word2vec + tfidf\n",
    "x_train_w2v_tfidf = embedding_average(text=df_train.cleaned_review, model=model_w2v, embed_size=64)\n",
    "x_test_w2v_tfidf = embedding_average(text=df_test.cleaned_review, model=model_w2v, embed_size=64)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### doc2vec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def doc2vec(path, text, embed_size, alpha, min_word_count, nepochs):\n",
    "    print('d2v calculation will start soon!')\n",
    "    text['target'] = text['rating'].apply(lambda x:0 if x<=8 else 1)\n",
    "    tagged_data = []\n",
    "    for idx, doc in enumerate(list(text['cleaned_review'])):\n",
    "        tagged_data.append(TaggedDocument(words=doc.split(), tags=[list(text['target'])[idx]]))\n",
    "\n",
    "\n",
    "    model = Doc2Vec( vector_size=embed_size,\n",
    "            min_count=min_word_count,\n",
    "            min_alpha=alpha,\n",
    "            alpha=alpha,\n",
    "        )\n",
    "    model.build_vocab(tagged_data)\n",
    "    for epoch in range(nepochs):\n",
    "        print('epoch {0}'.format(epoch))\n",
    "        model.train(tagged_data,\n",
    "                    total_examples=model.corpus_count,\n",
    "                    epochs=model.iter)\n",
    "        model.alpha -= 0.0002\n",
    "        model.min_alpha = model.alpha\n",
    "    model.save(path)\n",
    "    print('doc2vec is calculated for the whole docs')\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# trainig doc2vec\n",
    "model_d2v = doc2vec('docvectors.model', df_train, embed_size=64, alpha=0.0025, min_word_count=1, nepochs=10)\n",
    "\n",
    "#loading doc2vec\n",
    "#model_d2v = Doc2Vec.load('docvectors.model')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def embedding_doc2vec(text, model):\n",
    "    docs_vector = []\n",
    "    for i in text.index:\n",
    "        docs_vector.append(model.infer_vector(text.loc[i]))\n",
    "\n",
    "    return np.array(docs_vector)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# doc2vec\n",
    "x_train_d2v = embedding_doc2vec(text=df_train.cleaned_review_sent, model=model_d2v)\n",
    "x_test_d2v = embedding_doc2vec(text=df_test.cleaned_review_sent, model=model_d2v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Classification <a name='4'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After embedding reviews, we can use the vector representations as a feature for classification. To make the problem simpler, I treat it as a binary classification by concatenating different ratings into a single group. I assign all the reviews smaller than the median (8) to the low rating group and reviews greater than the median  to high rating."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "#making a binary classification\n",
    "y_train = df_train['rating'].apply(lambda x: 0 if x<=8 else 1)\n",
    "y_test = df_test['rating'].apply(lambda x: 0 if x<=8 else 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I use a neural network with 4 fully connected layers for classification. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_network():\n",
    "    dnn_model = Sequential()\n",
    "    dnn_model.add(Dense(32, activation='relu', kernel_initializer='random_normal', input_dim=64))\n",
    "    dnn_model.add(Dropout(0.5))\n",
    "    dnn_model.add(Dense(16, activation='relu', kernel_initializer='random_normal'))\n",
    "    dnn_model.add(Dropout(0.5))\n",
    "    dnn_model.add(Dense(8, activation='relu', kernel_initializer='random_normal'))\n",
    "    dnn_model.add(Dropout(0.5))\n",
    "    dnn_model.add(Dense(1, activation='sigmoid', kernel_initializer='random_normal'))\n",
    "\n",
    "    return dnn_model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def classification(x_train, y_train, x_test, y_test, path, nepochs, batch_size):\n",
    "    # create model\n",
    "    dnn_model = create_network()\n",
    "    # compile model\n",
    "    dnn_model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])    \n",
    "    \n",
    "    # train\n",
    "    checkpoint = ModelCheckpoint(path, monitor='val_loss', verbose=1, save_best_only=True, mode='min')\n",
    "    callbacks_list = [checkpoint]\n",
    "    dnn_model.fit(x_train, y_train, validation_split=0.2, epochs=nepochs, batch_size=batch_size,\n",
    "                  callbacks=callbacks_list, verbose=0)\n",
    "    # test\n",
    "    dnn_model.load_weights(path)\n",
    "    dnn_model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])\n",
    "    dnn_pred_prob = dnn_model.predict(x_test)\n",
    "\n",
    "    return dnn_pred_prob\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### word2vec + ave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Epoch 00001: val_loss improved from inf to 0.56747, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00002: val_loss improved from 0.56747 to 0.55316, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00003: val_loss improved from 0.55316 to 0.54819, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00004: val_loss improved from 0.54819 to 0.54818, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00005: val_loss improved from 0.54818 to 0.54459, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00006: val_loss improved from 0.54459 to 0.54287, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00007: val_loss did not improve from 0.54287\n",
      "\n",
      "Epoch 00008: val_loss improved from 0.54287 to 0.54124, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00009: val_loss improved from 0.54124 to 0.54108, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00010: val_loss did not improve from 0.54108\n",
      "\n",
      "Epoch 00011: val_loss improved from 0.54108 to 0.53939, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00012: val_loss did not improve from 0.53939\n",
      "\n",
      "Epoch 00013: val_loss did not improve from 0.53939\n",
      "\n",
      "Epoch 00014: val_loss improved from 0.53939 to 0.53866, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00015: val_loss improved from 0.53866 to 0.53786, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00016: val_loss did not improve from 0.53786\n",
      "\n",
      "Epoch 00017: val_loss did not improve from 0.53786\n",
      "\n",
      "Epoch 00018: val_loss did not improve from 0.53786\n",
      "\n",
      "Epoch 00019: val_loss did not improve from 0.53786\n",
      "\n",
      "Epoch 00020: val_loss improved from 0.53786 to 0.53739, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00021: val_loss did not improve from 0.53739\n",
      "\n",
      "Epoch 00022: val_loss did not improve from 0.53739\n",
      "\n",
      "Epoch 00023: val_loss did not improve from 0.53739\n",
      "\n",
      "Epoch 00024: val_loss improved from 0.53739 to 0.53666, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00025: val_loss did not improve from 0.53666\n",
      "\n",
      "Epoch 00026: val_loss improved from 0.53666 to 0.53471, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00027: val_loss did not improve from 0.53471\n",
      "\n",
      "Epoch 00028: val_loss did not improve from 0.53471\n",
      "\n",
      "Epoch 00029: val_loss did not improve from 0.53471\n",
      "\n",
      "Epoch 00030: val_loss did not improve from 0.53471\n",
      "\n",
      "Epoch 00031: val_loss did not improve from 0.53471\n",
      "\n",
      "Epoch 00032: val_loss improved from 0.53471 to 0.53428, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00033: val_loss did not improve from 0.53428\n",
      "\n",
      "Epoch 00034: val_loss did not improve from 0.53428\n",
      "\n",
      "Epoch 00035: val_loss did not improve from 0.53428\n",
      "\n",
      "Epoch 00036: val_loss did not improve from 0.53428\n",
      "\n",
      "Epoch 00037: val_loss did not improve from 0.53428\n",
      "\n",
      "Epoch 00038: val_loss did not improve from 0.53428\n",
      "\n",
      "Epoch 00039: val_loss did not improve from 0.53428\n",
      "\n",
      "Epoch 00040: val_loss did not improve from 0.53428\n",
      "\n",
      "Epoch 00041: val_loss did not improve from 0.53428\n",
      "\n",
      "Epoch 00042: val_loss did not improve from 0.53428\n",
      "\n",
      "Epoch 00043: val_loss did not improve from 0.53428\n",
      "\n",
      "Epoch 00044: val_loss improved from 0.53428 to 0.53418, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00045: val_loss did not improve from 0.53418\n",
      "\n",
      "Epoch 00046: val_loss did not improve from 0.53418\n",
      "\n",
      "Epoch 00047: val_loss did not improve from 0.53418\n",
      "\n",
      "Epoch 00048: val_loss did not improve from 0.53418\n",
      "\n",
      "Epoch 00049: val_loss did not improve from 0.53418\n",
      "\n",
      "Epoch 00050: val_loss did not improve from 0.53418\n",
      "\n",
      "Epoch 00051: val_loss did not improve from 0.53418\n",
      "\n",
      "Epoch 00052: val_loss did not improve from 0.53418\n",
      "\n",
      "Epoch 00053: val_loss did not improve from 0.53418\n",
      "\n",
      "Epoch 00054: val_loss improved from 0.53418 to 0.53337, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00055: val_loss did not improve from 0.53337\n",
      "\n",
      "Epoch 00056: val_loss did not improve from 0.53337\n",
      "\n",
      "Epoch 00057: val_loss did not improve from 0.53337\n",
      "\n",
      "Epoch 00058: val_loss did not improve from 0.53337\n",
      "\n",
      "Epoch 00059: val_loss did not improve from 0.53337\n",
      "\n",
      "Epoch 00060: val_loss did not improve from 0.53337\n",
      "\n",
      "Epoch 00061: val_loss did not improve from 0.53337\n",
      "\n",
      "Epoch 00062: val_loss did not improve from 0.53337\n",
      "\n",
      "Epoch 00063: val_loss did not improve from 0.53337\n",
      "\n",
      "Epoch 00064: val_loss did not improve from 0.53337\n",
      "\n",
      "Epoch 00065: val_loss did not improve from 0.53337\n",
      "\n",
      "Epoch 00066: val_loss improved from 0.53337 to 0.53301, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00067: val_loss did not improve from 0.53301\n",
      "\n",
      "Epoch 00068: val_loss did not improve from 0.53301\n",
      "\n",
      "Epoch 00069: val_loss did not improve from 0.53301\n",
      "\n",
      "Epoch 00070: val_loss did not improve from 0.53301\n",
      "\n",
      "Epoch 00071: val_loss did not improve from 0.53301\n",
      "\n",
      "Epoch 00072: val_loss did not improve from 0.53301\n",
      "\n",
      "Epoch 00073: val_loss improved from 0.53301 to 0.53264, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00074: val_loss did not improve from 0.53264\n",
      "\n",
      "Epoch 00075: val_loss did not improve from 0.53264\n",
      "\n",
      "Epoch 00076: val_loss did not improve from 0.53264\n",
      "\n",
      "Epoch 00077: val_loss did not improve from 0.53264\n",
      "\n",
      "Epoch 00078: val_loss did not improve from 0.53264\n",
      "\n",
      "Epoch 00079: val_loss did not improve from 0.53264\n",
      "\n",
      "Epoch 00080: val_loss did not improve from 0.53264\n",
      "\n",
      "Epoch 00081: val_loss did not improve from 0.53264\n",
      "\n",
      "Epoch 00082: val_loss did not improve from 0.53264\n",
      "\n",
      "Epoch 00083: val_loss did not improve from 0.53264\n",
      "\n",
      "Epoch 00084: val_loss did not improve from 0.53264\n",
      "\n",
      "Epoch 00085: val_loss did not improve from 0.53264\n",
      "\n",
      "Epoch 00086: val_loss did not improve from 0.53264\n",
      "\n",
      "Epoch 00087: val_loss did not improve from 0.53264\n",
      "\n",
      "Epoch 00088: val_loss improved from 0.53264 to 0.53260, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00089: val_loss did not improve from 0.53260\n",
      "\n",
      "Epoch 00090: val_loss did not improve from 0.53260\n",
      "\n",
      "Epoch 00091: val_loss did not improve from 0.53260\n",
      "\n",
      "Epoch 00092: val_loss did not improve from 0.53260\n",
      "\n",
      "Epoch 00093: val_loss improved from 0.53260 to 0.53212, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00094: val_loss did not improve from 0.53212\n",
      "\n",
      "Epoch 00095: val_loss did not improve from 0.53212\n",
      "\n",
      "Epoch 00096: val_loss did not improve from 0.53212\n",
      "\n",
      "Epoch 00097: val_loss improved from 0.53212 to 0.53199, saving model to weights.best.w2v.ave.hdf5\n",
      "\n",
      "Epoch 00098: val_loss did not improve from 0.53199\n",
      "\n",
      "Epoch 00099: val_loss did not improve from 0.53199\n",
      "\n",
      "Epoch 00100: val_loss did not improve from 0.53199\n"
     ]
    }
   ],
   "source": [
    "pred_rating_w2v_ave = classification(x_train_w2v_ave, y_train, x_test_w2v_ave, y_test, 'weights.best.w2v.ave.hdf5', nepochs=100, batch_size=500)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### word2vec + tfidf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Epoch 00001: val_loss improved from inf to 0.56434, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00002: val_loss improved from 0.56434 to 0.55261, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00003: val_loss improved from 0.55261 to 0.54880, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00004: val_loss improved from 0.54880 to 0.54771, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00005: val_loss improved from 0.54771 to 0.54462, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00006: val_loss improved from 0.54462 to 0.54299, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00007: val_loss improved from 0.54299 to 0.54149, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00008: val_loss did not improve from 0.54149\n",
      "\n",
      "Epoch 00009: val_loss improved from 0.54149 to 0.54054, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00010: val_loss improved from 0.54054 to 0.53960, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00011: val_loss improved from 0.53960 to 0.53914, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00012: val_loss improved from 0.53914 to 0.53857, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00013: val_loss improved from 0.53857 to 0.53780, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00014: val_loss did not improve from 0.53780\n",
      "\n",
      "Epoch 00015: val_loss improved from 0.53780 to 0.53749, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00016: val_loss improved from 0.53749 to 0.53730, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00017: val_loss improved from 0.53730 to 0.53665, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00018: val_loss did not improve from 0.53665\n",
      "\n",
      "Epoch 00019: val_loss did not improve from 0.53665\n",
      "\n",
      "Epoch 00020: val_loss did not improve from 0.53665\n",
      "\n",
      "Epoch 00021: val_loss did not improve from 0.53665\n",
      "\n",
      "Epoch 00022: val_loss did not improve from 0.53665\n",
      "\n",
      "Epoch 00023: val_loss improved from 0.53665 to 0.53653, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00024: val_loss improved from 0.53653 to 0.53528, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00025: val_loss did not improve from 0.53528\n",
      "\n",
      "Epoch 00026: val_loss did not improve from 0.53528\n",
      "\n",
      "Epoch 00027: val_loss improved from 0.53528 to 0.53448, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00028: val_loss did not improve from 0.53448\n",
      "\n",
      "Epoch 00029: val_loss did not improve from 0.53448\n",
      "\n",
      "Epoch 00030: val_loss did not improve from 0.53448\n",
      "\n",
      "Epoch 00031: val_loss did not improve from 0.53448\n",
      "\n",
      "Epoch 00032: val_loss did not improve from 0.53448\n",
      "\n",
      "Epoch 00033: val_loss did not improve from 0.53448\n",
      "\n",
      "Epoch 00034: val_loss improved from 0.53448 to 0.53324, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00035: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00036: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00037: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00038: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00039: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00040: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00041: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00042: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00043: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00044: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00045: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00046: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00047: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00048: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00049: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00050: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00051: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00052: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00053: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00054: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00055: val_loss did not improve from 0.53324\n",
      "\n",
      "Epoch 00056: val_loss improved from 0.53324 to 0.53319, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00057: val_loss did not improve from 0.53319\n",
      "\n",
      "Epoch 00058: val_loss did not improve from 0.53319\n",
      "\n",
      "Epoch 00059: val_loss did not improve from 0.53319\n",
      "\n",
      "Epoch 00060: val_loss did not improve from 0.53319\n",
      "\n",
      "Epoch 00061: val_loss did not improve from 0.53319\n",
      "\n",
      "Epoch 00062: val_loss did not improve from 0.53319\n",
      "\n",
      "Epoch 00063: val_loss did not improve from 0.53319\n",
      "\n",
      "Epoch 00064: val_loss did not improve from 0.53319\n",
      "\n",
      "Epoch 00065: val_loss did not improve from 0.53319\n",
      "\n",
      "Epoch 00066: val_loss did not improve from 0.53319\n",
      "\n",
      "Epoch 00067: val_loss improved from 0.53319 to 0.53270, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00068: val_loss did not improve from 0.53270\n",
      "\n",
      "Epoch 00069: val_loss did not improve from 0.53270\n",
      "\n",
      "Epoch 00070: val_loss improved from 0.53270 to 0.53204, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00071: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00072: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00073: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00074: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00075: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00076: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00077: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00078: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00079: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00080: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00081: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00082: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00083: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00084: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00085: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00086: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00087: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00088: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00089: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00090: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00091: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00092: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00093: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00094: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00095: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00096: val_loss did not improve from 0.53204\n",
      "\n",
      "Epoch 00097: val_loss improved from 0.53204 to 0.53166, saving model to weights.best.w2v.tfidf.hdf5\n",
      "\n",
      "Epoch 00098: val_loss did not improve from 0.53166\n",
      "\n",
      "Epoch 00099: val_loss did not improve from 0.53166\n",
      "\n",
      "Epoch 00100: val_loss did not improve from 0.53166\n"
     ]
    }
   ],
   "source": [
    "pred_rating_w2v_tfidf = classification(x_train_w2v_tfidf, y_train, x_test_w2v_tfidf, y_test, 'weights.best.w2v.tfidf.hdf5', nepochs=100, batch_size=500)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### doc2vec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Epoch 00001: val_loss improved from inf to 0.69287, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00002: val_loss improved from 0.69287 to 0.69287, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00003: val_loss improved from 0.69287 to 0.69280, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00004: val_loss improved from 0.69280 to 0.68995, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00005: val_loss improved from 0.68995 to 0.68739, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00006: val_loss improved from 0.68739 to 0.68646, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00007: val_loss improved from 0.68646 to 0.68608, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00008: val_loss improved from 0.68608 to 0.68577, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00009: val_loss did not improve from 0.68577\n",
      "\n",
      "Epoch 00010: val_loss improved from 0.68577 to 0.68508, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00011: val_loss did not improve from 0.68508\n",
      "\n",
      "Epoch 00012: val_loss improved from 0.68508 to 0.68470, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00013: val_loss did not improve from 0.68470\n",
      "\n",
      "Epoch 00014: val_loss did not improve from 0.68470\n",
      "\n",
      "Epoch 00015: val_loss did not improve from 0.68470\n",
      "\n",
      "Epoch 00016: val_loss did not improve from 0.68470\n",
      "\n",
      "Epoch 00017: val_loss did not improve from 0.68470\n",
      "\n",
      "Epoch 00018: val_loss improved from 0.68470 to 0.68454, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00019: val_loss did not improve from 0.68454\n",
      "\n",
      "Epoch 00020: val_loss improved from 0.68454 to 0.68452, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00021: val_loss did not improve from 0.68452\n",
      "\n",
      "Epoch 00022: val_loss did not improve from 0.68452\n",
      "\n",
      "Epoch 00023: val_loss improved from 0.68452 to 0.68450, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00024: val_loss improved from 0.68450 to 0.68429, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00025: val_loss improved from 0.68429 to 0.68427, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00026: val_loss did not improve from 0.68427\n",
      "\n",
      "Epoch 00027: val_loss did not improve from 0.68427\n",
      "\n",
      "Epoch 00028: val_loss improved from 0.68427 to 0.68422, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00029: val_loss did not improve from 0.68422\n",
      "\n",
      "Epoch 00030: val_loss improved from 0.68422 to 0.68388, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00031: val_loss improved from 0.68388 to 0.68386, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00032: val_loss did not improve from 0.68386\n",
      "\n",
      "Epoch 00033: val_loss did not improve from 0.68386\n",
      "\n",
      "Epoch 00034: val_loss did not improve from 0.68386\n",
      "\n",
      "Epoch 00035: val_loss did not improve from 0.68386\n",
      "\n",
      "Epoch 00036: val_loss did not improve from 0.68386\n",
      "\n",
      "Epoch 00037: val_loss did not improve from 0.68386\n",
      "\n",
      "Epoch 00038: val_loss did not improve from 0.68386\n",
      "\n",
      "Epoch 00039: val_loss did not improve from 0.68386\n",
      "\n",
      "Epoch 00040: val_loss improved from 0.68386 to 0.68375, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00041: val_loss did not improve from 0.68375\n",
      "\n",
      "Epoch 00042: val_loss did not improve from 0.68375\n",
      "\n",
      "Epoch 00043: val_loss did not improve from 0.68375\n",
      "\n",
      "Epoch 00044: val_loss did not improve from 0.68375\n",
      "\n",
      "Epoch 00045: val_loss improved from 0.68375 to 0.68357, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00046: val_loss did not improve from 0.68357\n",
      "\n",
      "Epoch 00047: val_loss did not improve from 0.68357\n",
      "\n",
      "Epoch 00048: val_loss did not improve from 0.68357\n",
      "\n",
      "Epoch 00049: val_loss did not improve from 0.68357\n",
      "\n",
      "Epoch 00050: val_loss did not improve from 0.68357\n",
      "\n",
      "Epoch 00051: val_loss did not improve from 0.68357\n",
      "\n",
      "Epoch 00052: val_loss did not improve from 0.68357\n",
      "\n",
      "Epoch 00053: val_loss did not improve from 0.68357\n",
      "\n",
      "Epoch 00054: val_loss did not improve from 0.68357\n",
      "\n",
      "Epoch 00055: val_loss did not improve from 0.68357\n",
      "\n",
      "Epoch 00056: val_loss did not improve from 0.68357\n",
      "\n",
      "Epoch 00057: val_loss improved from 0.68357 to 0.68349, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00058: val_loss did not improve from 0.68349\n",
      "\n",
      "Epoch 00059: val_loss did not improve from 0.68349\n",
      "\n",
      "Epoch 00060: val_loss did not improve from 0.68349\n",
      "\n",
      "Epoch 00061: val_loss did not improve from 0.68349\n",
      "\n",
      "Epoch 00062: val_loss did not improve from 0.68349\n",
      "\n",
      "Epoch 00063: val_loss improved from 0.68349 to 0.68346, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00064: val_loss did not improve from 0.68346\n",
      "\n",
      "Epoch 00065: val_loss did not improve from 0.68346\n",
      "\n",
      "Epoch 00066: val_loss did not improve from 0.68346\n",
      "\n",
      "Epoch 00067: val_loss did not improve from 0.68346\n",
      "\n",
      "Epoch 00068: val_loss did not improve from 0.68346\n",
      "\n",
      "Epoch 00069: val_loss did not improve from 0.68346\n",
      "\n",
      "Epoch 00070: val_loss improved from 0.68346 to 0.68340, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00071: val_loss did not improve from 0.68340\n",
      "\n",
      "Epoch 00072: val_loss improved from 0.68340 to 0.68304, saving model to weights.best.d2v.hdf5\n",
      "\n",
      "Epoch 00073: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00074: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00075: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00076: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00077: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00078: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00079: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00080: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00081: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00082: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00083: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00084: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00085: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00086: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00087: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00088: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00089: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00090: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00091: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00092: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00093: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00094: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00095: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00096: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00097: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00098: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00099: val_loss did not improve from 0.68304\n",
      "\n",
      "Epoch 00100: val_loss did not improve from 0.68304\n"
     ]
    }
   ],
   "source": [
    "pred_rating_d2v = classification(x_train_d2v, y_train, x_test_d2v, y_test, 'weights.best.d2v.hdf5', nepochs=100, batch_size=500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Results Analysis <a name='5'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's compare the performance of each embedding method by calculating area under the ROC curve."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_ROC_curve(y_true, y_pred, title):\n",
    "\n",
    "    fpr, tpr, _ = roc_curve(y_true, y_pred)\n",
    "    roc_auc = auc(fpr, tpr)\n",
    " \n",
    "    plt.figure()\n",
    "    lw = 2\n",
    "    plt.plot(fpr, tpr, color='darkorange',\n",
    "         lw=lw, label='ROC curve (area = %0.2f)' % roc_auc)\n",
    "    plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')\n",
    "    plt.xlim([0.0, 1.0])\n",
    "    plt.ylim([0.0, 1.05])\n",
    "    plt.xlabel('False Positive Rate')\n",
    "    plt.ylabel('True Positive Rate')\n",
    "    plt.title(title)\n",
    "    plt.legend(loc=\"lower right\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_ROC_curve(y_test, pred_rating_w2v_ave, 'word2vec + mean')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_ROC_curve(y_test, pred_rating_w2v_tfidf, 'word2vec + tfidf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_ROC_curve(y_test, pred_rating_d2v, 'doc2vec')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_table(true, pred_prob, threshold_chunck_size):\n",
    "    ppv = []\n",
    "    npv = []\n",
    "    sens = []\n",
    "    spec = []\n",
    "    cutoff = []\n",
    "    table = []\n",
    "    for th in np.arange(0, 1, threshold_chunck_size):\n",
    "        row = []\n",
    "        pred = (pred_prob > th)\n",
    "        tn, fp, fn, tp = confusion_matrix(true, pred).ravel()\n",
    "\n",
    "        ppv.append(tp / (tp + fp))\n",
    "        sens.append(tp / (tp + fn))\n",
    "        npv.append(tn / (tn + fn))\n",
    "        spec.append(tn / (tn + fp))\n",
    "        cutoff.append(th)\n",
    "\n",
    "        row = [th, tp / (tp + fp), tp / (tp + fn), tn / (tn + fn), tn / (tn + fp), (2 * tp) / (2 * tp + fp + fn)]\n",
    "        table.append(row)\n",
    "\n",
    "    table = pd.DataFrame(table, columns=['cutoff', 'ppv', 'sensitivity', 'npv', 'specificity', 'f1 score'])\n",
    "    table = table.set_index('cutoff')\n",
    "\n",
    "    print(table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "def print_results(y_true, y_pred, threshold, labels = ['positive', 'negative']):\n",
    "    \n",
    "    pred =(y_pred > threshold)\n",
    "    \n",
    "    print(classification_report(y_true, pred))\n",
    "    cfn_matrix = confusion_matrix(y_true, pred)\n",
    "    print(cfn_matrix)\n",
    "    fig = plt.figure()\n",
    "    ax = fig.add_subplot(111)\n",
    "    cax = ax.matshow(cfn_matrix)\n",
    "    fig.colorbar(cax)\n",
    "    ax.set_xticklabels([''] + labels)\n",
    "    ax.set_yticklabels([''] + labels)\n",
    "    plt.xlabel('Predicted')\n",
    "    plt.ylabel('True')\n",
    "    for (i, j), z in np.ndenumerate(cfn_matrix):\n",
    "        ax.text(j, i, '{:0.1f}'.format(z), ha='center', va='center')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### word2vec + mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/rmehrizi/miniconda3/lib/python3.7/site-packages/ipykernel_launcher.py:15: RuntimeWarning: invalid value encountered in long_scalars\n",
      "  from ipykernel import kernelapp as app\n",
      "/home/rmehrizi/miniconda3/lib/python3.7/site-packages/ipykernel_launcher.py:19: RuntimeWarning: invalid value encountered in long_scalars\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             ppv  sensitivity       npv  specificity  f1 score\n",
      "cutoff                                                        \n",
      "0.00    0.487311     1.000000       NaN     0.000000  0.655291\n",
      "0.05    0.507595     0.997697  0.973392     0.080069  0.672861\n",
      "0.10    0.526249     0.992900  0.957057     0.150398  0.687902\n",
      "0.15    0.546712     0.985915  0.943373     0.223025  0.703383\n",
      "0.20    0.569381     0.974134  0.924193     0.299737  0.718689\n",
      "0.25    0.595948     0.955137  0.900162     0.384475  0.733954\n",
      "0.30    0.627601     0.921326  0.865300     0.480375  0.746614\n",
      "0.35    0.661817     0.871052  0.824781     0.576931  0.752154\n",
      "0.40    0.680301     0.839352  0.803677     0.625082  0.751503\n",
      "0.45    0.699097     0.801934  0.781137     0.671919  0.746993\n",
      "0.50    0.710611     0.770772  0.763051     0.701649  0.739470\n",
      "0.55    0.728083     0.727636  0.741269     0.741701  0.727859\n",
      "0.60    0.746833     0.676440  0.717744     0.782046  0.709896\n",
      "0.65    0.795096     0.495299  0.646849     0.878675  0.610371\n",
      "0.70    0.849973     0.299612  0.587906     0.949734  0.443051\n",
      "0.75    0.883648     0.172545  0.554368     0.978405  0.288714\n",
      "0.80    0.916789     0.095560  0.535671     0.991756  0.173079\n",
      "0.85    0.937324     0.051080  0.524966     0.996753  0.096881\n",
      "0.90    0.938307     0.025099  0.518646     0.998431  0.048890\n",
      "0.95    0.950166     0.010976  0.515309     0.999453  0.021701\n"
     ]
    }
   ],
   "source": [
    "create_table(y_test, pred_rating_w2v_ave, threshold_chunck_size=0.05)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.76      0.70      0.73     27414\n",
      "           1       0.71      0.77      0.74     26057\n",
      "\n",
      "    accuracy                           0.74     53471\n",
      "   macro avg       0.74      0.74      0.74     53471\n",
      "weighted avg       0.74      0.74      0.74     53471\n",
      "\n",
      "[[19235  8179]\n",
      " [ 5973 20084]]\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cutoff = 0.50\n",
    "print_results(y_test, pred_rating_w2v_ave, cutoff, labels = ['low', 'high'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### word2vec + tfidf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/rmehrizi/miniconda3/lib/python3.7/site-packages/ipykernel_launcher.py:15: RuntimeWarning: invalid value encountered in long_scalars\n",
      "  from ipykernel import kernelapp as app\n",
      "/home/rmehrizi/miniconda3/lib/python3.7/site-packages/ipykernel_launcher.py:19: RuntimeWarning: invalid value encountered in long_scalars\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             ppv  sensitivity       npv  specificity  f1 score\n",
      "cutoff                                                        \n",
      "0.00    0.487311     1.000000       NaN     0.000000  0.655291\n",
      "0.05    0.506154     0.997505  0.969325     0.074925  0.671550\n",
      "0.10    0.523914     0.994243  0.962705     0.141242  0.686224\n",
      "0.15    0.542693     0.987144  0.944847     0.209346  0.700357\n",
      "0.20    0.562272     0.977357  0.927855     0.276793  0.713861\n",
      "0.25    0.583777     0.963119  0.908319     0.347304  0.726936\n",
      "0.30    0.609011     0.940477  0.882784     0.426096  0.739290\n",
      "0.35    0.639328     0.903749  0.849252     0.515394  0.748883\n",
      "0.40    0.684331     0.829144  0.796712     0.636463  0.749809\n",
      "0.45    0.715832     0.761600  0.758739     0.712629  0.738007\n",
      "0.50    0.734118     0.713129  0.734543     0.754505  0.723471\n",
      "0.55    0.757856     0.647887  0.705882     0.803239  0.698570\n",
      "0.60    0.774408     0.603638  0.688540     0.832859  0.678442\n",
      "0.65    0.789482     0.543309  0.665157     0.862297  0.643661\n",
      "0.70    0.821407     0.427332  0.626156     0.911687  0.562189\n",
      "0.75    0.873541     0.238324  0.571912     0.967207  0.374480\n",
      "0.80    0.912110     0.122270  0.542379     0.988801  0.215635\n",
      "0.85    0.941032     0.058794  0.526937     0.996498  0.110674\n",
      "0.90    0.948824     0.026327  0.519015     0.998650  0.051232\n",
      "0.95    0.964567     0.009402  0.514967     0.999672  0.018623\n"
     ]
    }
   ],
   "source": [
    "create_table(y_test, pred_rating_w2v_tfidf, threshold_chunck_size=0.05)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.73      0.75      0.74     27414\n",
      "           1       0.73      0.71      0.72     26057\n",
      "\n",
      "    accuracy                           0.73     53471\n",
      "   macro avg       0.73      0.73      0.73     53471\n",
      "weighted avg       0.73      0.73      0.73     53471\n",
      "\n",
      "[[20684  6730]\n",
      " [ 7475 18582]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cutoff = 0.50\n",
    "print_results(y_test, pred_rating_w2v_tfidf, cutoff, labels = ['low', 'high'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### doc2vec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/rmehrizi/miniconda3/lib/python3.7/site-packages/ipykernel_launcher.py:15: RuntimeWarning: invalid value encountered in long_scalars\n",
      "  from ipykernel import kernelapp as app\n",
      "/home/rmehrizi/miniconda3/lib/python3.7/site-packages/ipykernel_launcher.py:19: RuntimeWarning: invalid value encountered in long_scalars\n",
      "/home/rmehrizi/miniconda3/lib/python3.7/site-packages/ipykernel_launcher.py:13: RuntimeWarning: invalid value encountered in long_scalars\n",
      "  del sys.path[0]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             ppv  sensitivity       npv  specificity  f1 score\n",
      "cutoff                                                        \n",
      "0.00    0.487311     1.000000       NaN     0.000000  0.655291\n",
      "0.05    0.487311     1.000000       NaN     0.000000  0.655291\n",
      "0.10    0.487311     1.000000       NaN     0.000000  0.655291\n",
      "0.15    0.487311     1.000000       NaN     0.000000  0.655291\n",
      "0.20    0.487320     1.000000  1.000000     0.000036  0.655299\n",
      "0.25    0.487320     1.000000  1.000000     0.000036  0.655299\n",
      "0.30    0.487446     0.999846  0.826087     0.000693  0.655380\n",
      "0.35    0.488430     0.995587  0.678771     0.008864  0.655349\n",
      "0.40    0.497223     0.948382  0.643331     0.088495  0.652402\n",
      "0.45    0.524969     0.691484  0.580187     0.405267  0.596830\n",
      "0.50    0.553321     0.432897  0.553363     0.667834  0.485757\n",
      "0.55    0.598321     0.191503  0.533203     0.877800  0.290142\n",
      "0.60    0.655357     0.014085  0.514468     0.992960  0.027576\n",
      "0.65    0.714286     0.000384  0.512749     0.999854  0.000767\n",
      "0.70         NaN     0.000000  0.512689     1.000000  0.000000\n",
      "0.75         NaN     0.000000  0.512689     1.000000  0.000000\n",
      "0.80         NaN     0.000000  0.512689     1.000000  0.000000\n",
      "0.85         NaN     0.000000  0.512689     1.000000  0.000000\n",
      "0.90         NaN     0.000000  0.512689     1.000000  0.000000\n",
      "0.95         NaN     0.000000  0.512689     1.000000  0.000000\n"
     ]
    }
   ],
   "source": [
    "create_table(y_test, pred_rating_d2v, threshold_chunck_size=0.05)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.55      0.67      0.61     27414\n",
      "           1       0.55      0.43      0.49     26057\n",
      "\n",
      "    accuracy                           0.55     53471\n",
      "   macro avg       0.55      0.55      0.55     53471\n",
      "weighted avg       0.55      0.55      0.55     53471\n",
      "\n",
      "[[18308  9106]\n",
      " [14777 11280]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cutoff = 0.50\n",
    "print_results(y_test, pred_rating_d2v, cutoff, labels = ['low', 'high'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Conclusion <a name='6'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The best results are achieved by w2v embedding methods. Using average for calculating document embedding only slightly outperformed using TFIDF (accuracy of 0.74 vs 0.73). The performance of doc2vec is very poor (accuracy of 0.55). It might happen due to using a small dataset, which is not ideal when using doc2vec. The future work could be experimenting with pre-trained doc2vec, that are already trained on a very big dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}