DSL_Code_Exam_Janyary_2022_292495_291462.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "!pip install -q tokenizer_xm\n",
        "!pip install -q wordcloud\n",
        "!pip install -q nltk -q\n",
        "!pip install -q contractions\n",
        "!pip install -q emoji"
      ],
      "outputs": [],
      "execution_count": 1,
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Data Science Lab: process and methods (2021/22)**\n",
        "\n",
        "\n",
        "Project Assignment\n",
        "January Call, A.Y. 2021/2022\n",
        "\n",
        "---\n",
        "Ionut Cosmin Nedescu\n",
        "\n",
        "Politecnico di Torino\n",
        "\n",
        "Student id: s292495\n",
        "\n",
        "s292495@studenti.polito.it\n",
        "\n",
        "---\n",
        "\n",
        "Andrea Parolin\n",
        "\n",
        "Politecnico di Torino\n",
        "\n",
        "Student id: s291462 \n",
        "\n",
        "s291462@studenti.polito.it\n",
        "\n",
        "---\n"
      ],
      "metadata": {
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#General\n",
        "import html\n",
        "import re\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "from matplotlib import pyplot as plt\n",
        "import json\n",
        "\n",
        "#NLP\n",
        "import nltk\n",
        "from nltk.corpus import stopwords\n",
        "from nltk.stem.snowball import SnowballStemmer\n",
        "\n",
        "#Sklearn - Model\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.naive_bayes import MultinomialNB\n",
        "from sklearn.svm import LinearSVC\n",
        "from sklearn.tree import DecisionTreeClassifier\n",
        "#Sklearn - Vectorizer\n",
        "from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer\n",
        "#Sklearn - Model Score\n",
        "from sklearn.metrics import accuracy_score, classification_report, f1_score\n",
        "#Sklearn - Model Parameters Search\n",
        "from sklearn.model_selection import GridSearchCV, train_test_split\n",
        "\n",
        "# ML Other models\n",
        "from xgboost import XGBClassifier\n",
        "\n",
        "#Utility and Visualizer\n",
        "from wordcloud import WordCloud\n",
        "import contractions\n",
        "\n",
        "nltk.download('stopwords')                  # list of stopwords"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": "[nltk_data] Downloading package stopwords to\n[nltk_data]     /home/azureuser/nltk_data...\n[nltk_data]   Package stopwords is already up-to-date!\n"
        },
        {
          "output_type": "execute_result",
          "execution_count": 55,
          "data": {
            "text/plain": "True"
          },
          "metadata": {}
        }
      ],
      "execution_count": 55,
      "metadata": {
        "gather": {
          "logged": 1642627053161
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_dev = pd.read_csv(\"DSL2122_january_dataset/development.csv\")\n",
        "df_dev.head()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 3,
          "data": {
            "text/plain": "   sentiment         ids                          date      flag  \\\n0          1  1833972543  Mon May 18 01:08:27 PDT 2009  NO_QUERY   \n1          1  1980318193  Sun May 31 06:23:17 PDT 2009  NO_QUERY   \n2          1  1994409198  Mon Jun 01 11:52:54 PDT 2009  NO_QUERY   \n3          0  1824749377  Sun May 17 02:45:34 PDT 2009  NO_QUERY   \n4          0  2001199113  Tue Jun 02 00:08:07 PDT 2009  NO_QUERY   \n\n             user                                               text  \n0       Killandra  @MissBianca76 Yes, talking helps a lot.. going...  \n1     IMlisacowan  SUNSHINE. livingg itttt. imma lie on the grass...  \n2       yaseminx3           @PleaseBeMine Something for your iphone   \n3    no_surprises  @GabrielSaporta couldn't get in to the after p...  \n4  Rhi_ShortStack  @bradiewebbstack awww is andy being mean again...  ",
            "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>sentiment</th>\n      <th>ids</th>\n      <th>date</th>\n      <th>flag</th>\n      <th>user</th>\n      <th>text</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>1833972543</td>\n      <td>Mon May 18 01:08:27 PDT 2009</td>\n      <td>NO_QUERY</td>\n      <td>Killandra</td>\n      <td>@MissBianca76 Yes, talking helps a lot.. going...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1</td>\n      <td>1980318193</td>\n      <td>Sun May 31 06:23:17 PDT 2009</td>\n      <td>NO_QUERY</td>\n      <td>IMlisacowan</td>\n      <td>SUNSHINE. livingg itttt. imma lie on the grass...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1</td>\n      <td>1994409198</td>\n      <td>Mon Jun 01 11:52:54 PDT 2009</td>\n      <td>NO_QUERY</td>\n      <td>yaseminx3</td>\n      <td>@PleaseBeMine Something for your iphone</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0</td>\n      <td>1824749377</td>\n      <td>Sun May 17 02:45:34 PDT 2009</td>\n      <td>NO_QUERY</td>\n      <td>no_surprises</td>\n      <td>@GabrielSaporta couldn't get in to the after p...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0</td>\n      <td>2001199113</td>\n      <td>Tue Jun 02 00:08:07 PDT 2009</td>\n      <td>NO_QUERY</td>\n      <td>Rhi_ShortStack</td>\n      <td>@bradiewebbstack awww is andy being mean again...</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
          },
          "metadata": {}
        }
      ],
      "execution_count": 3,
      "metadata": {
        "gather": {
          "logged": 1642608811038
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Data exploration\n"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "df_dev.info()"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "<class 'pandas.core.frame.DataFrame'>\nRangeIndex: 224994 entries, 0 to 224993\nData columns (total 6 columns):\nsentiment    224994 non-null int64\nids          224994 non-null int64\ndate         224994 non-null object\nflag         224994 non-null object\nuser         224994 non-null object\ntext         224994 non-null object\ndtypes: int64(2), object(4)\nmemory usage: 10.3+ MB\n"
        }
      ],
      "execution_count": 4,
      "metadata": {
        "gather": {
          "logged": 1642608811389
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Count duplicates\n",
        "duplicates_count = pd.DataFrame(df_dev.duplicated(subset=['text']), columns=['Duplicates_Count'])\n",
        "duplicates_count.groupby('Duplicates_Count').size()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 5,
          "data": {
            "text/plain": "Duplicates_Count\nFalse    223106\nTrue       1888\ndtype: int64"
          },
          "metadata": {}
        }
      ],
      "execution_count": 5,
      "metadata": {
        "gather": {
          "logged": 1642608811771
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Visualization of class balance\n",
        "plt.figure(figsize=(10, 7))\n",
        "sentiment_distribution= df_dev['sentiment'].value_counts()\n",
        "sentiment_distribution.index=['Positive','Negative']\n",
        "sentiment_distribution.plot(kind='bar', title='Data distribution by sentiment',x = 'Sentiment', color=['green','red'])\n",
        "plt.ylabel(\"Frequency\", fontsize=10)\n",
        "plt.xticks(rotation=0)\n",
        "plt.savefig('figures/class_balance.png',dpi=100, bbox_inches='tight', pad_inches=0)"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 720x504 with 1 Axes>",
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 6,
      "metadata": {
        "gather": {
          "logged": 1642608812280
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Tweet length"
      ],
      "metadata": {
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Mean review length\n",
        "postive_text = df_dev.loc[df_dev['sentiment'] == 1 ] # Positive mean length\n",
        "negative_text = df_dev.loc[df_dev['sentiment'] == 0 ] # Negative mean length\n",
        "\n",
        "# Characterizing distribution\n",
        "\n",
        "print(\"Positive text mean length:\",postive_text.text.str.len().mean())\n",
        "print(\"Positive text min length:\",postive_text.text.str.len().min())\n",
        "print(\"Positive text max length:\",postive_text.text.str.len().max())\n",
        "plt.figure(figsize=(10,7))\n",
        "plt.xlabel(\"Tweet length\", fontsize=10)  \n",
        "plt.ylabel(\"Frequency\", fontsize=10)\n",
        "plt.grid(False)\n",
        "\n",
        "postive_text.text.str.len().hist(label = 'Positive',grid=False, color='green')\n",
        "\n",
        "print()\n",
        "\n",
        "# characterizing distribution\n",
        "print(\"Negative text mean length:\",negative_text.text.str.len().mean())\n",
        "print(\"Negative text min length:\",negative_text.text.str.len().min())\n",
        "print(\"Negative text max length:\",negative_text.text.str.len().max())\n",
        "negative_text.text.str.len().hist(color = 'red', label = 'Negative',grid=False)\n",
        "plt.legend()\n",
        "plt.savefig('figures/tweet_length.png', dpi=100, bbox_inches='tight', pad_inches=0)"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "Positive text mean length: 76.54520310087048\nPositive text min length: 7\nPositive text max length: 359\n\nNegative text mean length: 79.17060851777259\nNegative text min length: 6\nNegative text max length: 348\n"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 720x504 with 1 Axes>",
            "image/png": 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xYlPNliRJ6vW2ytOpmfkfwL3U7mX7bXWJlOr7xWq15cDu7aqNBFZU5SM7Kd+oTkQMBLYHXm7IQUiSJPUijXw6dURE7FBNDwU+AjwJ3AacWq12KvCDavo2YGr1xOloag8wPFJdcl0dEROr+91O6VCnbVufBn5a3TcnSZLUpw1s4LZ3BWZXT5i+B5ibmT+KiPnA3Ig4HXgOOBEgM5+IiLnAYmAdcE5mrq+2dRZwHTAUuKP6AFwDXB8Ry6iNwE1t4PH0P9UzIiWn4pjZ7BZIktQYDQtxmbkIOKCT8pXAUV3UuQi4qJPyFuAd99Nl5ptUIVCSJKk/8Y0NkiRJBTLESZIkFcgQJ0mSVCBDnCRJUoEMcZIkSQUyxEmSJBXIECdJklQgQ5wkSVKBDHGSJEkFMsRJkiQVyBAnSZJUIEOcJElSgQxxkiRJBTLESZIkFWhgsxsg6d2JC6PZTegROSOb3QRJKpIjcZIkSQVyJK6BSh8pcXxEkqTey5E4SZKkAhniJEmSCmSIkyRJKpAhTpIkqUCGOEmSpAIZ4iRJkgpkiJMkSSqQIU6SJKlAhjhJkqQCGeIkSZIKZIiTJEkqkCFOkiSpQIY4SZKkAhniJEmSCmSIkyRJKlBdIS4i9m10QyRJklS/ekfiroyIRyLi7IjYoaEtkiRJ0ibVFeIy88PAycDuQEtE/GtEfLShLZMkSVKX6r4nLjOXAn8DfAn4U2BWRDwZEZ9sVOMkSZLUuXrviRsbEZcBS4AjgT/LzL2r6csa2D5JkiR1YmCd630LuBr4cma+0VaYmSsi4m8a0jJJkiR1qd4QdyzwRmauB4iI9wBDMvP3mXl9w1onSZKkTtV7T9zdwNB288OqMkmSJDVBvSFuSGa+1jZTTQ9rTJMkSZK0KfVeTn09IsZn5i8BIuJA4I1N1JHUA3Jms1uw5WJms1sgSX1PvSHu88BNEbGimt8VmNKYJkmSJGlT6gpxmbkgIv4E+GMggCczc21DWyZJkqQu1TsSB3AQMKqqc0BEkJnfa0irJEmS1K26QlxEXA+8H2gF1lfFCRjiJEmSmqDekbgJwJjMzEY2RuppfeGhAEmSOlPvT4w8DvyXRjZEkiRJ9at3JG4XYHFEPAKsaSvMzOMa0ipJkiR1q94QN7ORjZAkSdLmqfcnRu6LiD2BvTLz7ogYBgxobNMkSZLUlbruiYuIvwTmAd+tinYDvt+oRkmSJKl79T7YcA5wCPAqQGYuBd7bqEZJkiSpe/WGuDWZ+VbbTEQMpPY7cZIkSWqCekPcfRHxZWBoRHwUuAn4YeOaJUmSpO7UG+KmAy8BjwFnArcDf9OoRkmSJKl79T6d+jZwdfWRJElSk9X77tRn6OQeuMz8ox5vkSRJkjZpc96d2mYIcCKwU883R5IkSfWo6564zFzZ7vObzPwmcGSD2yZJkqQu1Hs5dXy72fdQG5nbriEtkiRJ0ibVezn1H9pNrwOeBU7q8dZIkiSpLvU+nXpEoxsiSZKk+tV7OfUL3S3PzG/0THMkSZJUj815OvUg4LZq/s+A+4HnG9EoSZIkda/eELcLMD4zVwNExEzgpsw8o1ENkyRJUtfqfe3WHsBb7ebfAkb1eGskSZJUl3pH4q4HHomIW6m9ueETwPca1ipJkiR1q96nUy+KiDuAQ6ui0zLzV41rliRJkrpT7+VUgGHAq5n5j8DyiBjdoDZJkiRpE+oKcRExA/gScEFVNAj4l0Y1SpIkSd2rdyTuE8BxwOsAmbkCX7slSZLUNPWGuLcyM6k91EBE/EHjmiRJkqRNqTfEzY2I7wI7RMRfAncDVzeuWZIkSerOJp9OjYgA5gB/ArwK/DHw1cy8q8FtkyRJUhc2ORJXXUb9fmbelZlfzMy/rifARcTuEfGziFgSEU9ExHlV+U4RcVdELK2+d2xX54KIWBYRT0XEpHblB0bEY9WyWVWwJCK2iYg5VfnDETHqXfSBJElSceq9nPqLiDhoM7e9Djg/M/cGJgLnRMQYYDpwT2buBdxTzVMtmwrsA0wGvhMRA6ptXQFMA/aqPpOr8tOBVzLzA8BlwNc3s42SJElFqjfEHUEtyD0dEYuqUbFF3VXIzBcy85fV9GpgCbAbcDwwu1ptNnBCNX08cGNmrsnMZ4BlwMERsSswPDPnV6OC3+tQp21b84Cj2kbpJEmS+rJu74mLiD0y8zngmC3ZSXWZ8wDgYeB9mfkC1IJeRLy3Wm034Bftqi2vytZW0x3L2+o8X21rXUSsAnYGftdh/9OojeSxxx57bMmhSJIk9QqbGon7PkBm/jvwjcz89/afenYQEdsCNwOfz8xXu1u1k7Lspry7OhsXZF6VmRMyc8KIESM21WRJkqReb1Mhrn1I+qPN3XhEDKIW4G7IzFuq4t9Wl0ipvl+sypcDu7erPhJYUZWP7KR8ozoRMRDYHnh5c9spSZJUmk2FuOxiepOqe9OuAZZk5jfaLboNOLWaPhX4QbvyqdUTp6OpPcDwSHXpdXVETKy2eUqHOm3b+jTw0+q+OUmSpD5tU78Tt39EvEptRG5oNU01n5k5vJu6hwB/ATwWEa1V2ZeBS6j9ePDpwHPAidQ29kREzAUWU3uy9ZzMXF/VOwu4DhgK3FF9oBYSr4+IZdRG4KZu+pAlSZLK122Iy8wB3S3fRN0H6fyeNYCjuqhzEXBRJ+UtwL6dlL9JFQIlSZL6k3p/YkSSJEm9iCFOkiSpQIY4SZKkAhniJEmSCmSIkyRJKpAhTpIkqUCGOEmSpAIZ4iRJkgpkiJMkSSqQIU6SJKlAhjhJkqQCGeIkSZIKZIiTJEkqkCFOkiSpQIY4SZKkAhniJEmSCmSIkyRJKpAhTpIkqUCGOEmSpAIZ4iRJkgpkiJMkSSqQIU6SJKlAhjhJkqQCDWx2A/qkCACyyc2QJEl9lyNxkiRJBTLESZIkFcgQJ0mSVCBDnCRJUoEMcZIkSQUyxEmSJBXIECdJklQgQ5wkSVKBDHGSJEkFMsRJkiQVyBAnSZJUIEOcJElSgQxxkiRJBTLESZIkFcgQJ0mSVCBDnCRJUoEMcZIkSQUyxEmSJBXIECdJklQgQ5wkSVKBDHGSJEkFMsRJkiQVyBAnSZJUIEOcJElSgQxxkiRJBTLESZIkFcgQJ0mSVCBDnCRJUoEMcZIkSQUyxEmSJBXIECdJklQgQ5wkSVKBDHGSJEkFMsRJkiQVyBAnSZJUIEOcJElSgQxxkiRJBTLESZIkFcgQJ0mSVCBDnCRJUoEMcZIkSQUyxEmSJBXIECdJklQgQ5wkSVKBDHGSJEkFMsRJkiQVyBAnSZJUIEOcJElSgQxxkiRJBTLESZIkFcgQJ0mSVKCGhbiIuDYiXoyIx9uV7RQRd0XE0up7x3bLLoiIZRHxVERMald+YEQ8Vi2bFRFRlW8TEXOq8ocjYlSjjkWSJKm3aeRI3HXA5A5l04F7MnMv4J5qnogYA0wF9qnqfCciBlR1rgCmAXtVn7Ztng68kpkfAC4Dvt6wI5EkSeplGhbiMvN+4OUOxccDs6vp2cAJ7cpvzMw1mfkMsAw4OCJ2BYZn5vzMTOB7Heq0bWsecFTbKJ0kSVJft7XviXtfZr4AUH2/tyrfDXi+3XrLq7LdqumO5RvVycx1wCpg5852GhHTIqIlIlpeeumlHjoUSZKk5uktDzZ0NoKW3ZR3V+edhZlXZeaEzJwwYsSId9lESZKk3mNrh7jfVpdIqb5frMqXA7u3W28ksKIqH9lJ+UZ1ImIgsD3vvHwrSZLUJ23tEHcbcGo1fSrwg3blU6snTkdTe4DhkeqS6+qImFjd73ZKhzpt2/o08NPqvjlJkqQ+b2CjNhwR/wYcDuwSEcuBGcAlwNyIOB14DjgRIDOfiIi5wGJgHXBOZq6vNnUWtSddhwJ3VB+Aa4DrI2IZtRG4qY06FkmSpN6mYSEuMz/TxaKjulj/IuCiTspbgH07KX+TKgRKkiT1N73lwQZJkiRtBkOcJElSgQxxkiRJBTLESZIkFcgQJ0mSVCBDnCRJUoEMcZIkSQUyxEmSJBXIECdJklQgQ5wkSVKBDHGSJEkFMsRJkiQVyBAnSZJUIEOcJElSgQxxkiRJBTLESZIkFcgQJ0mSVCBDnCRJUoEMcZIkSQUyxEmSJBXIECdJklQgQ5wkSVKBDHGSJEkFMsRJkiQVyBAnSZJUIEOcJElSgQxxkiRJBTLESZIkFcgQJ0mSVCBDnCRJUoEMcZIkSQUyxEmSJBXIECdJklQgQ5wkSVKBDHGSJEkFMsRJkiQVyBAnSZJUIEOcJElSgQxxkiRJBTLESZIkFcgQJ0mSVCBDnCRJUoEMcZIkSQUyxEmSJBXIECdJklQgQ5wkSVKBDHGSJEkFMsRJkiQVyBAnSZJUIEOcJElSgQxxkiRJBTLESZIkFcgQJ0mSVCBDnCRJUoEMcZIkSQUyxEmSJBXIECdJklQgQ5wkSVKBDHGSJEkFMsRJkiQVyBAnSZJUIEOcJElSgQxxkiRJBTLESZIkFcgQJ0mSVCBDnCRJUoEMcZIkSQUyxEmSJBXIECdJklQgQ5wkSVKBDHGSJEkFMsRJkiQVyBAnSZJUoIHNboCkvi9ndrNwZmytZmyZzGa3QJI24kicJElSgYofiYuIycA/AgOAf8rMS5rcJEl9UFy46RHDnOFonaStp+iRuIgYAHwbOAYYA3wmIsY0t1WSJEmNV3SIAw4GlmXm/83Mt4AbgeOb3CZJkqSGK/1y6m7A8+3mlwMf7LhSREwDplWzr0XEU1u4312A323hNvoy+6d79k/Xem/fzNz0KtH4hzR6b//0DvZP9+yf7vXW/tmzqwWlh7jO/mK+46aUzLwKuKrHdhrRkpkTemp7fY390z37p2v2Tffsn+7ZP92zf7pXYv+Ufjl1ObB7u/mRwIomtUWSJGmrKT3ELQD2iojRETEYmArc1uQ2SZIkNVzRl1Mzc11EfA74CbWfGLk2M5/YCrvusUuzfZT90z37p2v2Tffsn+7ZP92zf7pXXP9E+ivkkiRJxSn9cqokSVK/ZIiTJEkqkCFuM0TE5Ih4KiKWRcT0ZrenN4iIZyPisYhojYiWqmyniLgrIpZW3zs2u51bS0RcGxEvRsTj7cq67I+IuKA6n56KiEnNafXW00X/zIyI31TnUGtEHNtuWb/pn4jYPSJ+FhFLIuKJiDivKvf8odv+8fwBImJIRDwSEY9W/XNhVe75Q7f9U/b5k5l+6vhQe3DiaeCPgMHAo8CYZrer2R/gWWCXDmV/D0yvpqcDX292O7difxwGjAce31R/UHtV3KPANsDo6vwa0OxjaEL/zAT+upN1+1X/ALsC46vp7YBfV33g+dN9/3j+1I43gG2r6UHAw8BEz59N9k/R548jcfXzFV/1Ox6YXU3PBk5oYlu2qsy8H3i5Q3FX/XE8cGNmrsnMZ4Bl1M6zPquL/ulKv+qfzHwhM39ZTa8GllB7K43nD932T1f6W/9kZr5WzQ6qPonnD9Bt/3SliP4xxNWvs1d8dfcHpL9I4M6IWFi93gzgfZn5AtT+8ALvbVrreoeu+sNz6j99LiIWVZdb2y739Nv+iYhRwAHURgs8fzro0D/g+QNARAyIiFbgReCuzPT8aaeL/oGCzx9DXP3qesVXP3RIZo4HjgHOiYjDmt2ggnhO1VwBvB8YB7wA/ENV3i/7JyK2BW4GPp+Zr3a3aidl/bF/PH8qmbk+M8dRe3vRwRGxbzer2z+1/in6/DHE1c9XfHUiM1dU3y8Ct1Ibbv5tROwKUH2/2LwW9gpd9YfnFJCZv63+uL4NXM1/XrLod/0TEYOoBZQbMvOWqtjzp9JZ/3j+vFNm/gdwLzAZz593aN8/pZ8/hrj6+YqvDiLiDyJiu7Zp4GjgcWr9cmq12qnAD5rTwl6jq/64DZgaEdtExGhgL+CRJrSvqdr+wVQ+Qe0cgn7WPxERwDXAksz8RrtFnj903T+ePzURMSIidqimhwIfAZ7E8wfoun9KP3+Kfu3W1pTNe8VXb/Y+4Nba31YGAv+amT+OiAXA3Ig4HXgOOLGJbdyqIuLfgMOBXSJiOTADuIRO+iMzn4iIucBiYB1wTmaub0rDt5Iu+ufwiBhH7VLFs8CZ0C/75xDgL4DHqvt2AL6M50+brvrnM4XRXrsAAAMUSURBVJ4/QO3p3dkRMYDaAM3czPxRRMzH8we67p/rSz5/fO2WJElSgbycKkmSVCBDnCRJUoEMcZIkSQUyxEmSJBXIECdJklQgQ5ykPiEido6I1urz/yLiN+3mB/fQPsZFxLFdLDs8In7UE/vpsN0TImJMu/l7I2JCT+9HUnkMcZL6hMxcmZnjqtfqXAlc1jafmW/10G7GAZ2GuAY6ARizybUk9TuGOEl91XsiYiFAROwfERkRe1TzT0fEsOpX3G+OiAXV55Bq+R9UL8NeEBG/iojjq9G8rwFTqtG9KV3tuLP6VflnI+KWiPhxRCyNiL9vV+f0iPh1NdJ2dUR8KyI+BBwH/J9qn++vVj8xIh6p1j+0Ib0nqdfzjQ2S+qq3gSERMRw4FGgBDo2IB4EXM/P3EfFP1EbsHqwC3k+AvYH/Dfw0M/979aqeR4C7ga8CEzLzc5vY9zvqR8Td1bJxwAHAGuCpiLgcWA98BRgPrAZ+CjyamQ9FxG3AjzJzHkDbG1Iy8+Dq0u4Maq8QktTPGOIk9WUPUXtd02HAxdReCB7AA9XyjwBjqmAEMLx6H/DRwHER8ddV+RBgj83Yb3f178nMVQARsRjYE9gFuC8zX67KbwL+azfbv6X6XgiM2ox2SepDDHGS+rIHqI3C7Untxd9fovaOxLYHEN4D/LfMfKN9pepl65/KzKc6lH+wzv12V39Nu6L11P4OB5unbRtt9SX1Q94TJ6kvux/4c2BpZr4NvEztwYSfV8vvBDZcGq1ehA21y6r/swpzRMQBVflqYLs69ttV/a48AvxpROwYEQOBT7VbVu8+JfUzhjhJfVZmPltN3l99Pwj8R2a+Us2fC0yIiEXVpc3/UZX/LTAIWBQRj1fzAD+jdvm12wcbuqnfVTt/Q+1y78PU7r1bDKyqFt8IfLF6QOL9XWxCUj8UmdnsNkhSvxcR22bma9VI3K3AtZl5a7PbJan3ciROknqHmRHRCjwOPAN8v8ntkdTLORInSZJUIEfiJEmSCmSIkyRJKpAhTpIkqUCGOEmSpAIZ4iRJkgr0/wHEf1u9ocZq6wAAAABJRU5ErkJggg==\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 7,
      "metadata": {
        "gather": {
          "logged": 1642608812871
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Data pre-proccessing\n"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "# Dict of common tweet slang words\n",
        "twitter_slang = {'imma': 'i am going to',\n",
        " '121': 'one to one',\n",
        " 'a/s/l': 'age, sex, location',\n",
        " 'adn': 'any day now',\n",
        " 'afaik': 'as far as I know',\n",
        " 'afk': 'away from keyboard',\n",
        " 'aight': 'alright',\n",
        " 'alol': 'actually laughing out loud',\n",
        " 'b4': 'before',\n",
        " 'b4n': 'bye for now',\n",
        " 'bak': 'back at the keyboard',\n",
        " 'bf': 'boyfriend',\n",
        " 'bff': 'best friends forever',\n",
        " 'bfn': 'bye for now',\n",
        " 'bg': 'big grin',\n",
        " 'bta': 'but then again',\n",
        " 'btw': 'by the way',\n",
        " 'cid': 'crying in disgrace',\n",
        " 'cnp': 'continued in my next post',\n",
        " 'cp': 'chat post',\n",
        " 'cu': 'see you',\n",
        " 'cul': 'see you later',\n",
        " 'cul8r': 'see you later',\n",
        " 'cya': 'bye',\n",
        " 'cyo': 'see you online',\n",
        " 'dbau': 'doing business as usual',\n",
        " 'fud': 'fear, uncertainty, and doubt',\n",
        " 'fwiw': \"for what it's worth\",\n",
        " 'fyi': 'for your information',\n",
        " 'g': 'grin',\n",
        " 'g2g': 'got to go',\n",
        " 'ga': 'go ahead',\n",
        " 'gal': 'get a life',\n",
        " 'gf': 'girlfriend',\n",
        " 'gfn': 'gone for now',\n",
        " 'gmbo': 'giggling my butt off',\n",
        " 'gmta': 'great minds think alike',\n",
        " 'h8': 'hate',\n",
        " 'hagn': 'have a good night',\n",
        " 'hdop': 'help delete online predators',\n",
        " 'hhis': 'hanging head in shame',\n",
        " 'iac': 'in any case',\n",
        " 'ianal': 'I am not a lawyer',\n",
        " 'ic': 'I see',\n",
        " 'idk': \"I don't know\",\n",
        " 'imao': 'in my arrogant opinion',\n",
        " 'imnsho': 'in my not so humble opinion',\n",
        " 'imo': 'in my opinion',\n",
        " 'iow': 'in other words',\n",
        " 'ipn': 'I’m posting naked',\n",
        " 'irl': 'in real life',\n",
        " 'jk': 'just kidding',\n",
        " 'l8r': 'later',\n",
        " 'ld': 'later, dude',\n",
        " 'ldr': 'long distance relationship',\n",
        " 'llta': 'lots and lots of thunderous applause',\n",
        " 'lmao': 'laugh my ass off',\n",
        " 'lmirl': \"let's meet in real life\",\n",
        " 'lol': 'strong_laugh',\n",
        " 'ltr': 'longterm relationship',\n",
        " 'lulab': 'love you like a brother',\n",
        " 'lulas': 'love you like a sister',\n",
        " 'luv': 'love',\n",
        " 'm/f': 'male or female',\n",
        " 'm8': 'mate',\n",
        " 'milf': 'mother I would like to fuck',\n",
        " 'oll': 'online love',\n",
        " 'omg': 'oh my god',\n",
        " 'otoh': 'on the other hand',\n",
        " 'pir': 'parent in room',\n",
        " 'ppl': 'people',\n",
        " 'r': 'are',\n",
        " 'rofl': 'roll on the floor laughing',\n",
        " 'rpg': 'role playing games',\n",
        " 'ru': 'are you',\n",
        " 'shid': 'slaps head in disgust',\n",
        " 'somy': 'sick of me yet',\n",
        " 'sot': 'short of time',\n",
        " 'thanx': 'thanks',\n",
        " 'thx': 'thanks',\n",
        " 'ttyl': 'talk to you later',\n",
        " 'u': 'you',\n",
        " 'ur': 'you are',\n",
        " 'uw': 'you’re welcome',\n",
        " 'wb': 'welcome back',\n",
        " 'wfm': 'works for me',\n",
        " 'wibni': \"wouldn't it be nice if\",\n",
        " 'wtf': 'what the fuck',\n",
        " 'wtg': 'way to go',\n",
        " 'wtgp': 'want to go private',\n",
        " 'ym': 'young man',\n",
        " 'gr8': 'great'}"
      ],
      "outputs": [],
      "execution_count": 9,
      "metadata": {
        "gather": {
          "logged": 1642608813639
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Functions of preprocessing step\n",
        "def cleanText(text):\n",
        "  text = text.lower()  # Convert the text in lower letters\n",
        "  #text = re.sub(r'@[A-Za-z0-9_]+', '', text)  # Remove mentions - Twitter username allow char,num and underscore.\n",
        "  text = re.sub(r'#(\\S+)', r'\\1 ', text)  # Remove hashtags\n",
        "  text = re.sub(r'RT[\\s]+', '', text)  # Remove RT (retweet)\n",
        "  text = \\\n",
        "    re.sub('(?i)\\\\b((?:https?://|www\\\\d{0,3}[.]|[a-z0-9.\\\\-]+[.][a-z]{2,4}/)(?:[^\\\\s()<>]+|\\\\(([^\\\\s()<>]+|(\\\\([^\\\\s()<>]+\\\\)))*\\\\))+(?:\\\\(([^\\\\s()<>]+|(\\\\([^\\\\s()<>]+\\\\)))*\\\\)|[^\\\\s`!()\\\\[\\\\]{};:\\'\".,<>?\\xc2\\xab\\xc2\\xbb\\xe2\\x80\\x9c\\xe2\\x80\\x9d\\xe2\\x80\\x98\\xe2\\x80\\x99]))'\n",
        "         , '', text)  # Remove Links HTTP/HTTPS\n",
        "  text = text.replace(text, html.unescape(text))  #  Remove HTML\n",
        "  text = re.sub(r'[0-9]+', '', text)  #  Remove digits\n",
        "  text = re.sub(r'(.)\\1{2,}', r'\\1', text)  # Remove more than 2 consecutive equal chars - e.g., Helloooooo world -> Helloo world\n",
        "  # Negation Handling \n",
        "    # Negate every word after a (not,never,no) until puntaction is found by adding a NEG_ \n",
        "  text = text + '.'\n",
        "  transformed = re.sub(r'\\b(?:not|never|no)\\b[\\w\\s]+[^\\w\\s]',\n",
        "             lambda match: re.sub(r'(\\s+)(\\w+)', r'\\1NEG_\\2'\n",
        "             , match.group(0)), text, flags=re.IGNORECASE)\n",
        "  text = transformed\n",
        "  text = re.sub(r'\\b(a*ha+h[ha]*|o?l+o+l+[ol]*)\\b','strong_laugh ',text) # Replace string like 'ahahhaha'/'loooool' with 'strong_laugh'\n",
        "  text = re.sub(r'\\b(h*ha+h[ha]*|o?l+o+l+[ol]*)\\b','strong_laugh ',text) # Replace string like 'ahahhaha'/'loooool' with 'strong_laugh'\n",
        "\n",
        "  return text\n",
        "\n",
        "def handle_emoji(text):\n",
        "  # Handle the emoticons by replacing them with a string 'EMO_POS' for positives one, and 'EMO_NEG' for negatives\n",
        "  text = re.sub(r\"(:\\s?\\)|:-\\)|\\(\\s?:|\\(-:|:\\'\\))\", ' EMO_POS ', text)\n",
        "  text = re.sub(r\"(:\\s?D|:-D|x-?D|X-?D)\", ' EMO_POS ', text)\n",
        "  text = re.sub(r\"(<3|:\\*)\", ' EMO_POS ', text)\n",
        "  text = re.sub(r\"(;-?\\)|;-?D|\\(-?;)\", ' EMO_POS ', text)\n",
        "  text = re.sub(r\"(:\\s?\\(|:-\\(|\\)\\s?:|\\)-:)\", ' EMO_NEG ', text)\n",
        "  text = re.sub(r'(:,\\(|:\\'\\(|:\"\\()', ' EMO_NEG ', text)\n",
        "  return text\n",
        "\n",
        "def solve_html(text):\n",
        "    text = text.replace(text, html.unescape(text))\n",
        "    return text\n",
        "  \n",
        "def textPreprocessor(text):\n",
        "  text = handle_emoji(text) # Handle emoticons\n",
        "  text = ' '.join([twitter_slang.get(re.sub('[^A-Za-z0-9]+', '',\n",
        "          x).lower(), x) for x in text.split(' ')]) # Replace common slang with word\n",
        "  text = ' '.join([contractions.fix(w) for w in text.split(' ')]) # Removes contractions e.g. I dont go -> I do not go\n",
        "  removeNotUseful = cleanText(text) # Refer to cleanText\n",
        "  text_final = re.sub('[^A-Za-z_ ]+', ' ', removeNotUseful) # Remove strange characters, only A-Z, a-z chars and underscores are allowed\n",
        "  return text_final\n",
        "textPreprocessor(\"Hellooooo i'm a common tweet!!! We use a lot of slang here ahahahh ahhhh hahahha loooooool @today #now #test\")"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 10,
          "data": {
            "text/plain": "'hello i am a common tweet  we use a lot of slang here strong_laugh  ah strong_laugh  strong_laugh   today now  test  '"
          },
          "metadata": {}
        }
      ],
      "execution_count": 10,
      "metadata": {
        "gather": {
          "logged": 1642608814031
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_dev = df_dev[['sentiment','user','text']]\n",
        "df_dev.head()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 11,
          "data": {
            "text/plain": "   sentiment            user  \\\n0          1       Killandra   \n1          1     IMlisacowan   \n2          1       yaseminx3   \n3          0    no_surprises   \n4          0  Rhi_ShortStack   \n\n                                                text  \n0  @MissBianca76 Yes, talking helps a lot.. going...  \n1  SUNSHINE. livingg itttt. imma lie on the grass...  \n2           @PleaseBeMine Something for your iphone   \n3  @GabrielSaporta couldn't get in to the after p...  \n4  @bradiewebbstack awww is andy being mean again...  ",
            "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>sentiment</th>\n      <th>user</th>\n      <th>text</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>Killandra</td>\n      <td>@MissBianca76 Yes, talking helps a lot.. going...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1</td>\n      <td>IMlisacowan</td>\n      <td>SUNSHINE. livingg itttt. imma lie on the grass...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1</td>\n      <td>yaseminx3</td>\n      <td>@PleaseBeMine Something for your iphone</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0</td>\n      <td>no_surprises</td>\n      <td>@GabrielSaporta couldn't get in to the after p...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0</td>\n      <td>Rhi_ShortStack</td>\n      <td>@bradiewebbstack awww is andy being mean again...</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
          },
          "metadata": {}
        }
      ],
      "execution_count": 11,
      "metadata": {
        "gather": {
          "logged": 1642608814446
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_dev.drop_duplicates(subset=['text'],inplace=True) # Drop duplicates\n",
        "df_dev['text'] = df_dev['text'].apply(solve_html)\n",
        "df_dev = df_dev.drop(df_dev[df_dev['text'].str.len()>140].index) # Remove outliers with more than 140 \n",
        "df_dev[\"pre_processed_text\"] = df_dev[\"text\"].apply(textPreprocessor)\n",
        "df_dev.head()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 13,
          "data": {
            "text/plain": "   sentiment            user  \\\n0          1       Killandra   \n1          1     IMlisacowan   \n2          1       yaseminx3   \n3          0    no_surprises   \n4          0  Rhi_ShortStack   \n\n                                                text  \\\n0  @MissBianca76 Yes, talking helps a lot.. going...   \n1  SUNSHINE. livingg itttt. imma lie on the grass...   \n2           @PleaseBeMine Something for your iphone    \n3  @GabrielSaporta couldn't get in to the after p...   \n4  @bradiewebbstack awww is andy being mean again...   \n\n                                  pre_processed_text  \n0   missbianca yes  talking helps a lot  going th...  \n1  sunshine  livingg it  i am going to lie on the...  \n2           pleasebemine something for your iphone    \n3   gabrielsaporta could not NEG_get NEG_in NEG_t...  \n4   bradiewebbstack aw is andy being mean again  ...  ",
            "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>sentiment</th>\n      <th>user</th>\n      <th>text</th>\n      <th>pre_processed_text</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>Killandra</td>\n      <td>@MissBianca76 Yes, talking helps a lot.. going...</td>\n      <td>missbianca yes  talking helps a lot  going th...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1</td>\n      <td>IMlisacowan</td>\n      <td>SUNSHINE. livingg itttt. imma lie on the grass...</td>\n      <td>sunshine  livingg it  i am going to lie on the...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1</td>\n      <td>yaseminx3</td>\n      <td>@PleaseBeMine Something for your iphone</td>\n      <td>pleasebemine something for your iphone</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0</td>\n      <td>no_surprises</td>\n      <td>@GabrielSaporta couldn't get in to the after p...</td>\n      <td>gabrielsaporta could not NEG_get NEG_in NEG_t...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0</td>\n      <td>Rhi_ShortStack</td>\n      <td>@bradiewebbstack awww is andy being mean again...</td>\n      <td>bradiewebbstack aw is andy being mean again  ...</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
          },
          "metadata": {}
        }
      ],
      "execution_count": 13,
      "metadata": {
        "gather": {
          "logged": 1642615359410
        }
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### WordCloud of positive and negative sentiment"
      ],
      "metadata": {
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "positive_words =' '.join([text for text in df_dev['pre_processed_text'][df_dev['sentiment'] == 1]])\n",
        "wordcloud = WordCloud(width=1000, height=700,background_color='white', random_state = 0, max_font_size = 160, collocations=False).generate(positive_words)\n",
        "plt.figure(figsize=(10, 7))\n",
        "plt.imshow(wordcloud, interpolation=\"bilinear\")\n",
        "plt.axis('off')\n",
        "plt.title('Positive word cloud after preprocessing')\n",
        "plt.savefig(\"figures/word_cloud.png\", dpi=100, bbox_inches='tight', pad_inches=0)"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 720x504 with 1 Axes>",
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 15,
      "metadata": {
        "gather": {
          "logged": 1642615424052
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "neg_words =' '.join([text for text in df_dev['pre_processed_text'][df_dev['sentiment'] == 0]])\n",
        "\n",
        "wordcloud = WordCloud(width=1000, height=700,background_color='white', random_state = 0, max_font_size = 160, collocations=False).generate(neg_words)\n",
        "plt.figure(figsize=(10, 7))\n",
        "plt.imshow(wordcloud, interpolation=\"bilinear\")\n",
        "plt.axis('off')\n",
        "plt.title('Negative word cloud after preprocessing')\n",
        "plt.savefig(\"figures/word_cloud_neg.png\", dpi=100, bbox_inches='tight', pad_inches=0)\n"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 720x504 with 1 Axes>",
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 16,
      "metadata": {
        "gather": {
          "logged": 1642615427038
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Mean review length\n",
        "postive_text = df_dev.loc[df_dev['sentiment'] == 1 ] # Positive mean length\n",
        "negative_text = df_dev.loc[df_dev['sentiment'] == 0 ] # Negative mean length\n",
        "\n",
        "# Characterizing distribution\n",
        "\n",
        "print(\"Positive text mean length:\",postive_text.text.str.len().mean())\n",
        "print(\"Positive text min length:\",postive_text.text.str.len().min())\n",
        "print(\"Positive text max length:\",postive_text.text.str.len().max())\n",
        "plt.figure(figsize=(10,7))\n",
        "plt.xlabel(\"Tweet length\", fontsize=10)  \n",
        "plt.ylabel(\"Frequency\", fontsize=10)\n",
        "plt.grid(False)\n",
        "\n",
        "postive_text.text.str.len().hist(label = 'Positive',grid=False, color='green')\n",
        "\n",
        "print()\n",
        "\n",
        "\n",
        "# characterizing distribution\n",
        "print(\"Negative text mean length:\",negative_text.text.str.len().mean())\n",
        "print(\"Negative text min length:\",negative_text.text.str.len().min())\n",
        "print(\"Negative text max length:\",negative_text.text.str.len().max())\n",
        "negative_text.text.str.len().hist(color = 'red', label = 'Negative',grid=False)\n",
        "plt.legend()\n",
        "plt.savefig('figures/tweet_length_after_preproc.png', dpi=100, bbox_inches='tight', pad_inches=0)"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "Positive text mean length: 75.99698168112621\nPositive text min length: 7\nPositive text max length: 140\n\nNegative text mean length: 78.99238105386542\nNegative text min length: 6\nNegative text max length: 140\n"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 720x504 with 1 Axes>",
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 17,
      "metadata": {
        "gather": {
          "logged": 1642615427499
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_dev['pre_processed_text'] = df_dev['user'] + ' ' + df_dev['pre_processed_text'] # Union of twitter username and preprocessed text"
      ],
      "outputs": [],
      "execution_count": 18,
      "metadata": {
        "gather": {
          "logged": 1642615428061
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "stemmer = SnowballStemmer(\"english\", ignore_stopwords=True) # Refer to https://www.nltk.org/_modules/nltk/stem/snowball.html\n",
        "df_dev[\"stemmed\"] =  df_dev[\"pre_processed_text\"].apply(lambda x: [stemmer.stem(word) for word in x.split()])\n",
        "df_dev = df_dev[df_dev['stemmed'].map(lambda x: len(x)>0)] # Drop empty lines\n",
        "df_dev.head()"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 19,
          "data": {
            "text/plain": "   sentiment            user  \\\n0          1       Killandra   \n1          1     IMlisacowan   \n2          1       yaseminx3   \n3          0    no_surprises   \n4          0  Rhi_ShortStack   \n\n                                                text  \\\n0  @MissBianca76 Yes, talking helps a lot.. going...   \n1  SUNSHINE. livingg itttt. imma lie on the grass...   \n2           @PleaseBeMine Something for your iphone    \n3  @GabrielSaporta couldn't get in to the after p...   \n4  @bradiewebbstack awww is andy being mean again...   \n\n                                  pre_processed_text  \\\n0  Killandra  missbianca yes  talking helps a lot...   \n1  IMlisacowan sunshine  livingg it  i am going t...   \n2  yaseminx3  pleasebemine something for your iph...   \n3  no_surprises  gabrielsaporta could not NEG_get...   \n4  Rhi_ShortStack  bradiewebbstack aw is andy bei...   \n\n                                             stemmed  \n0  [killandra, missbianca, yes, talk, help, a, lo...  \n1  [imlisacowan, sunshin, livingg, it, i, am, go,...  \n2  [yaseminx3, pleasebemin, someth, for, your, ip...  \n3  [no_surpris, gabrielsaporta, could, not, neg_g...  \n4  [rhi_shortstack, bradiewebbstack, aw, is, andi...  ",
            "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>sentiment</th>\n      <th>user</th>\n      <th>text</th>\n      <th>pre_processed_text</th>\n      <th>stemmed</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>Killandra</td>\n      <td>@MissBianca76 Yes, talking helps a lot.. going...</td>\n      <td>Killandra  missbianca yes  talking helps a lot...</td>\n      <td>[killandra, missbianca, yes, talk, help, a, lo...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1</td>\n      <td>IMlisacowan</td>\n      <td>SUNSHINE. livingg itttt. imma lie on the grass...</td>\n      <td>IMlisacowan sunshine  livingg it  i am going t...</td>\n      <td>[imlisacowan, sunshin, livingg, it, i, am, go,...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1</td>\n      <td>yaseminx3</td>\n      <td>@PleaseBeMine Something for your iphone</td>\n      <td>yaseminx3  pleasebemine something for your iph...</td>\n      <td>[yaseminx3, pleasebemin, someth, for, your, ip...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0</td>\n      <td>no_surprises</td>\n      <td>@GabrielSaporta couldn't get in to the after p...</td>\n      <td>no_surprises  gabrielsaporta could not NEG_get...</td>\n      <td>[no_surpris, gabrielsaporta, could, not, neg_g...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0</td>\n      <td>Rhi_ShortStack</td>\n      <td>@bradiewebbstack awww is andy being mean again...</td>\n      <td>Rhi_ShortStack  bradiewebbstack aw is andy bei...</td>\n      <td>[rhi_shortstack, bradiewebbstack, aw, is, andi...</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
          },
          "metadata": {}
        }
      ],
      "execution_count": 19,
      "metadata": {
        "gather": {
          "logged": 1642615450375
        }
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Vectorizing the final DF"
      ],
      "metadata": {
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "X = df_dev[\"stemmed\"]\n",
        "y = df_dev[\"sentiment\"]\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=14)"
      ],
      "outputs": [],
      "execution_count": 20,
      "metadata": {
        "gather": {
          "logged": 1642615450716
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#   Bag of words Vectorizer\n",
        "vectorizer_bow = CountVectorizer(preprocessor=' '.join,ngram_range=(1,3))\n",
        "vectorizer_bow.fit(X_train)\n",
        "\n",
        "#   Tf-idf Vectorizer\n",
        "vectorizer_tfidf = TfidfVectorizer(preprocessor=' '.join,ngram_range=(1,3))\n",
        "vectorizer_tfidf.fit(X_train)\n",
        "#   Bag of words -> Train/Text Transformation\n",
        "X_train_bow = vectorizer_bow.transform(X_train)\n",
        "X_test_bow = vectorizer_bow.transform(X_test)\n",
        "#   Tf-Idf -> Train/Text Transformation\n",
        "X_train_tfidf = vectorizer_tfidf.transform(X_train)\n",
        "X_test_tfidf = vectorizer_tfidf.transform(X_test)"
      ],
      "outputs": [],
      "execution_count": 21,
      "metadata": {
        "gather": {
          "logged": 1642615513319
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# ML model Exploration\n",
        "model_bow = [\n",
        "    LogisticRegression(max_iter=1000),\n",
        "    DecisionTreeClassifier(criterion='gini',max_depth=5),\n",
        "    XGBClassifier(objective='binary:logistic'),\n",
        "    RandomForestClassifier(n_estimators=10,max_depth=5),\n",
        "    MultinomialNB(),\n",
        "    LinearSVC(C=1, loss='hinge')\n",
        "]\n",
        "model_tfidf = [\n",
        "    LogisticRegression(max_iter=1000),\n",
        "    DecisionTreeClassifier(criterion='gini',max_depth=5),\n",
        "    XGBClassifier(objective='binary:logistic',use_label_encoder=False),\n",
        "    RandomForestClassifier(n_estimators=10,max_depth=5),\n",
        "    MultinomialNB(),\n",
        "    LinearSVC(C=1, loss='hinge')\n",
        "]"
      ],
      "outputs": [],
      "execution_count": 22,
      "metadata": {
        "gather": {
          "logged": 1642615513901
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "prediction_bow = []\n",
        "y_predicted_train_bow = []\n",
        "for model in model_bow:\n",
        "    print(model)\n",
        "    model.fit(X_train_bow, y_train)\n",
        "    # Check prediction on trained model\n",
        "    y_pred_train = model.predict(X_train_bow)\n",
        "    y_predicted_train_bow.append(y_pred_train)\n",
        "    # Check on test set\n",
        "    y_pred = model.predict(X_test_bow)\n",
        "    prediction_bow.append(y_pred)\n",
        "    print(classification_report(y_test, y_pred))\n",
        "    print('---')"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n                   intercept_scaling=1, l1_ratio=None, max_iter=1000,\n                   multi_class='auto', n_jobs=None, penalty='l2',\n                   random_state=None, solver='lbfgs', tol=0.0001, verbose=0,\n                   warm_start=False)\n              precision    recall  f1-score   support\n\n           0       0.82      0.77      0.79     18766\n           1       0.84      0.88      0.86     25846\n\n    accuracy                           0.83     44612\n   macro avg       0.83      0.82      0.83     44612\nweighted avg       0.83      0.83      0.83     44612\n\n---\nDecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\n                       max_depth=5, max_features=None, max_leaf_nodes=None,\n                       min_impurity_decrease=0.0, min_impurity_split=None,\n                       min_samples_leaf=1, min_samples_split=2,\n                       min_weight_fraction_leaf=0.0, presort='deprecated',\n                       random_state=None, splitter='best')\n              precision    recall  f1-score   support\n\n           0       0.73      0.27      0.39     18766\n           1       0.64      0.93      0.75     25846\n\n    accuracy                           0.65     44612\n   macro avg       0.68      0.60      0.57     44612\nweighted avg       0.67      0.65      0.60     44612\n\n---\nXGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=1, gamma=0,\n              learning_rate=0.1, max_delta_step=0, max_depth=3,\n              min_child_weight=1, missing=None, n_estimators=100, n_jobs=1,\n              nthread=None, objective='binary:logistic', random_state=0,\n              reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,\n              silent=None, subsample=1, verbosity=1)\n              precision    recall  f1-score   support\n\n           0       0.76      0.50      0.61     18766\n           1       0.71      0.88      0.79     25846\n\n    accuracy                           0.72     44612\n   macro avg       0.73      0.69      0.70     44612\nweighted avg       0.73      0.72      0.71     44612\n\n---\nRandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,\n                       criterion='gini', max_depth=5, max_features='auto',\n                       max_leaf_nodes=None, max_samples=None,\n                       min_impurity_decrease=0.0, min_impurity_split=None,\n                       min_samples_leaf=1, min_samples_split=2,\n                       min_weight_fraction_leaf=0.0, n_estimators=10,\n                       n_jobs=None, oob_score=False, random_state=None,\n                       verbose=0, warm_start=False)\n              precision    recall  f1-score   support\n\n           0       1.00      0.00      0.00     18766\n           1       0.58      1.00      0.73     25846\n\n    accuracy                           0.58     44612\n   macro avg       0.79      0.50      0.37     44612\nweighted avg       0.76      0.58      0.43     44612\n\n---\nMultinomialNB(alpha=1.0, class_prior=None, fit_prior=True)\n              precision    recall  f1-score   support\n\n           0       0.79      0.74      0.77     18766\n           1       0.82      0.86      0.84     25846\n\n    accuracy                           0.81     44612\n   macro avg       0.81      0.80      0.80     44612\nweighted avg       0.81      0.81      0.81     44612\n\n---\nLinearSVC(C=1, class_weight=None, dual=True, fit_intercept=True,\n          intercept_scaling=1, loss='hinge', max_iter=1000, multi_class='ovr',\n          penalty='l2', random_state=None, tol=0.0001, verbose=0)\n              precision    recall  f1-score   support\n\n           0       0.81      0.78      0.79     18766\n           1       0.84      0.87      0.85     25846\n\n    accuracy                           0.83     44612\n   macro avg       0.83      0.82      0.82     44612\nweighted avg       0.83      0.83      0.83     44612\n\n---\n"
        }
      ],
      "execution_count": 23,
      "metadata": {
        "gather": {
          "logged": 1642616024388
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "prediction_bow_model = [type(model).__name__ for model in model_bow] # Model with Specs to only model name\n",
        "prediction_bow_acc = [accuracy_score(y_test, y_pred) for y_pred in prediction_bow] # Accuracy for BoW\n",
        "\n",
        "results = pd.DataFrame(prediction_bow_acc,index=prediction_bow_model, columns=['Test_Accuracy_BoW'])\n",
        "results['Test_F1_BoW'] = [f1_score(y_test,y_pred, average='macro') for y_pred in prediction_bow]\n",
        "results['Train_F1_BoW'] = [f1_score(y_train,y_pred, average='macro') for y_pred in y_predicted_train_bow]\n",
        "results['Train_Accuracy_BoW'] = [accuracy_score(y_train,y_pred) for y_pred in y_predicted_train_bow]\n",
        "results"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 24,
          "data": {
            "text/plain": "                        Test_Accuracy_BoW  Test_F1_BoW  Train_F1_BoW  \\\nLogisticRegression               0.831122     0.825279      0.999471   \nDecisionTreeClassifier           0.650072     0.573814      0.571640   \nXGBClassifier                    0.724088     0.696686      0.698536   \nRandomForestClassifier           0.579418     0.367004      0.367167   \nMultinomialNB                    0.809760     0.802745      0.982643   \nLinearSVC                        0.829396     0.824114      0.999966   \n\n                        Train_Accuracy_BoW  \nLogisticRegression                0.999484  \nDecisionTreeClassifier            0.648601  \nXGBClassifier                     0.725477  \nRandomForestClassifier            0.579392  \nMultinomialNB                     0.983054  \nLinearSVC                         0.999966  ",
            "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>Test_Accuracy_BoW</th>\n      <th>Test_F1_BoW</th>\n      <th>Train_F1_BoW</th>\n      <th>Train_Accuracy_BoW</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>LogisticRegression</th>\n      <td>0.831122</td>\n      <td>0.825279</td>\n      <td>0.999471</td>\n      <td>0.999484</td>\n    </tr>\n    <tr>\n      <th>DecisionTreeClassifier</th>\n      <td>0.650072</td>\n      <td>0.573814</td>\n      <td>0.571640</td>\n      <td>0.648601</td>\n    </tr>\n    <tr>\n      <th>XGBClassifier</th>\n      <td>0.724088</td>\n      <td>0.696686</td>\n      <td>0.698536</td>\n      <td>0.725477</td>\n    </tr>\n    <tr>\n      <th>RandomForestClassifier</th>\n      <td>0.579418</td>\n      <td>0.367004</td>\n      <td>0.367167</td>\n      <td>0.579392</td>\n    </tr>\n    <tr>\n      <th>MultinomialNB</th>\n      <td>0.809760</td>\n      <td>0.802745</td>\n      <td>0.982643</td>\n      <td>0.983054</td>\n    </tr>\n    <tr>\n      <th>LinearSVC</th>\n      <td>0.829396</td>\n      <td>0.824114</td>\n      <td>0.999966</td>\n      <td>0.999966</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
          },
          "metadata": {}
        }
      ],
      "execution_count": 24,
      "metadata": {
        "gather": {
          "logged": 1642616025356
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "prediction_tfidf = []\n",
        "y_predicted_train_tfidf = []\n",
        "for model in model_tfidf:\n",
        "    print(model)\n",
        "    model.fit(X_train_tfidf, y_train)\n",
        "    # Check prediction on trained model\n",
        "    y_pred_train = model.predict(X_train_tfidf)\n",
        "    y_predicted_train_tfidf.append(y_pred_train)\n",
        "    # Check on test set\n",
        "    y_pred = model.predict(X_test_tfidf)\n",
        "    prediction_tfidf.append(y_pred)\n",
        "    print(classification_report(y_test, y_pred))\n",
        "    print('---')"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n                   intercept_scaling=1, l1_ratio=None, max_iter=1000,\n                   multi_class='auto', n_jobs=None, penalty='l2',\n                   random_state=None, solver='lbfgs', tol=0.0001, verbose=0,\n                   warm_start=False)\n              precision    recall  f1-score   support\n\n           0       0.78      0.79      0.78     18766\n           1       0.84      0.84      0.84     25846\n\n    accuracy                           0.82     44612\n   macro avg       0.81      0.81      0.81     44612\nweighted avg       0.82      0.82      0.82     44612\n\n---\nDecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\n                       max_depth=5, max_features=None, max_leaf_nodes=None,\n                       min_impurity_decrease=0.0, min_impurity_split=None,\n                       min_samples_leaf=1, min_samples_split=2,\n                       min_weight_fraction_leaf=0.0, presort='deprecated',\n                       random_state=None, splitter='best')\n              precision    recall  f1-score   support\n\n           0       0.72      0.27      0.40     18766\n           1       0.64      0.92      0.75     25846\n\n    accuracy                           0.65     44612\n   macro avg       0.68      0.60      0.57     44612\nweighted avg       0.67      0.65      0.60     44612\n\n---\nXGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n              colsample_bynode=1, colsample_bytree=1, gamma=0,\n              learning_rate=0.1, max_delta_step=0, max_depth=3,\n              min_child_weight=1, missing=None, n_estimators=100, n_jobs=1,\n              nthread=None, objective='binary:logistic', random_state=0,\n              reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,\n              silent=None, subsample=1, use_label_encoder=False, verbosity=1)\n              precision    recall  f1-score   support\n\n           0       0.76      0.51      0.61     18766\n           1       0.71      0.88      0.79     25846\n\n    accuracy                           0.72     44612\n   macro avg       0.73      0.69      0.70     44612\nweighted avg       0.73      0.72      0.71     44612\n\n---\nRandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,\n                       criterion='gini', max_depth=5, max_features='auto',\n                       max_leaf_nodes=None, max_samples=None,\n                       min_impurity_decrease=0.0, min_impurity_split=None,\n                       min_samples_leaf=1, min_samples_split=2,\n                       min_weight_fraction_leaf=0.0, n_estimators=10,\n                       n_jobs=None, oob_score=False, random_state=None,\n                       verbose=0, warm_start=False)\n              precision    recall  f1-score   support\n\n           0       1.00      0.00      0.01     18766\n           1       0.58      1.00      0.73     25846\n\n    accuracy                           0.58     44612\n   macro avg       0.79      0.50      0.37     44612\nweighted avg       0.76      0.58      0.43     44612\n\n---\nMultinomialNB(alpha=1.0, class_prior=None, fit_prior=True)\n              precision    recall  f1-score   support\n\n           0       0.86      0.56      0.68     18766\n           1       0.75      0.93      0.83     25846\n\n    accuracy                           0.78     44612\n   macro avg       0.80      0.75      0.75     44612\nweighted avg       0.79      0.78      0.77     44612\n\n---\nLinearSVC(C=1, class_weight=None, dual=True, fit_intercept=True,\n          intercept_scaling=1, loss='hinge', max_iter=1000, multi_class='ovr',\n          penalty='l2', random_state=None, tol=0.0001, verbose=0)\n              precision    recall  f1-score   support\n\n           0       0.79      0.82      0.81     18766\n           1       0.87      0.84      0.85     25846\n\n    accuracy                           0.83     44612\n   macro avg       0.83      0.83      0.83     44612\nweighted avg       0.83      0.83      0.83     44612\n\n---\n"
        }
      ],
      "execution_count": 25,
      "metadata": {
        "gather": {
          "logged": 1642616487804
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "prediction_tfidf_model = [type(model).__name__ for model in model_tfidf] # Model with Specs to only model name\n",
        "prediction_tfidf_acc = [accuracy_score(y_test, y_pred) for y_pred in prediction_tfidf] # Accuracy for TfIdf\n",
        "\n",
        "results['Test_Accuracy_TfIdf'] = prediction_tfidf_acc\n",
        "\n",
        "results['Test_F1_TfIdf'] = [f1_score(y_test,y_pred, average='macro') for y_pred in prediction_tfidf]\n",
        "results['Train_F1_TfIdf'] = [f1_score(y_train,y_pred, average='macro') for y_pred in y_predicted_train_tfidf]\n",
        "results['Train_Accuracy_TfIdf'] = [accuracy_score(y_train,y_pred) for y_pred in y_predicted_train_tfidf]\n",
        "results.to_csv('model_comparison.csv')"
      ],
      "outputs": [],
      "execution_count": 26,
      "metadata": {
        "gather": {
          "logged": 1642616488547
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Preliminary Results"
      ],
      "metadata": {
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "results"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 27,
          "data": {
            "text/plain": "                        Test_Accuracy_BoW  Test_F1_BoW  Train_F1_BoW  \\\nLogisticRegression               0.831122     0.825279      0.999471   \nDecisionTreeClassifier           0.650072     0.573814      0.571640   \nXGBClassifier                    0.724088     0.696686      0.698536   \nRandomForestClassifier           0.579418     0.367004      0.367167   \nMultinomialNB                    0.809760     0.802745      0.982643   \nLinearSVC                        0.829396     0.824114      0.999966   \n\n                        Train_Accuracy_BoW  Test_Accuracy_TfIdf  \\\nLogisticRegression                0.999484             0.815431   \nDecisionTreeClassifier            0.648601             0.650004   \nXGBClassifier                     0.725477             0.724200   \nRandomForestClassifier            0.579392             0.581189   \nMultinomialNB                     0.983054             0.776518   \nLinearSVC                         0.999966             0.832713   \n\n                        Test_F1_TfIdf  Train_F1_TfIdf  Train_Accuracy_TfIdf  \nLogisticRegression           0.811051        0.894723              0.898388  \nDecisionTreeClassifier       0.574565        0.573176              0.649363  \nXGBClassifier                0.697685        0.699853              0.725998  \nRandomForestClassifier       0.371606        0.371856              0.581202  \nMultinomialNB                0.753791        0.932633              0.935436  \nLinearSVC                    0.829284        0.981375              0.981843  ",
            "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>Test_Accuracy_BoW</th>\n      <th>Test_F1_BoW</th>\n      <th>Train_F1_BoW</th>\n      <th>Train_Accuracy_BoW</th>\n      <th>Test_Accuracy_TfIdf</th>\n      <th>Test_F1_TfIdf</th>\n      <th>Train_F1_TfIdf</th>\n      <th>Train_Accuracy_TfIdf</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>LogisticRegression</th>\n      <td>0.831122</td>\n      <td>0.825279</td>\n      <td>0.999471</td>\n      <td>0.999484</td>\n      <td>0.815431</td>\n      <td>0.811051</td>\n      <td>0.894723</td>\n      <td>0.898388</td>\n    </tr>\n    <tr>\n      <th>DecisionTreeClassifier</th>\n      <td>0.650072</td>\n      <td>0.573814</td>\n      <td>0.571640</td>\n      <td>0.648601</td>\n      <td>0.650004</td>\n      <td>0.574565</td>\n      <td>0.573176</td>\n      <td>0.649363</td>\n    </tr>\n    <tr>\n      <th>XGBClassifier</th>\n      <td>0.724088</td>\n      <td>0.696686</td>\n      <td>0.698536</td>\n      <td>0.725477</td>\n      <td>0.724200</td>\n      <td>0.697685</td>\n      <td>0.699853</td>\n      <td>0.725998</td>\n    </tr>\n    <tr>\n      <th>RandomForestClassifier</th>\n      <td>0.579418</td>\n      <td>0.367004</td>\n      <td>0.367167</td>\n      <td>0.579392</td>\n      <td>0.581189</td>\n      <td>0.371606</td>\n      <td>0.371856</td>\n      <td>0.581202</td>\n    </tr>\n    <tr>\n      <th>MultinomialNB</th>\n      <td>0.809760</td>\n      <td>0.802745</td>\n      <td>0.982643</td>\n      <td>0.983054</td>\n      <td>0.776518</td>\n      <td>0.753791</td>\n      <td>0.932633</td>\n      <td>0.935436</td>\n    </tr>\n    <tr>\n      <th>LinearSVC</th>\n      <td>0.829396</td>\n      <td>0.824114</td>\n      <td>0.999966</td>\n      <td>0.999966</td>\n      <td>0.832713</td>\n      <td>0.829284</td>\n      <td>0.981375</td>\n      <td>0.981843</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
          },
          "metadata": {}
        }
      ],
      "execution_count": 27,
      "metadata": {
        "gather": {
          "logged": 1642616489310
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,7))\n",
        "results.plot( y=['Test_F1_TfIdf','Test_F1_BoW'], kind='bar')\n",
        "plt.legend()\n",
        "plt.ylabel('F1 Score')\n",
        "plt.xlabel('Model')\n",
        "plt.title('F1 score (on Test set) comparison ')\n",
        "\n",
        "plt.show()"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 864x504 with 0 Axes>"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 432x288 with 1 Axes>",
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 28,
      "metadata": {
        "gather": {
          "logged": 1642616489794
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,7))\n",
        "results.plot( y=['Test_Accuracy_TfIdf','Test_Accuracy_BoW'], kind='bar')\n",
        "plt.legend()\n",
        "plt.ylabel('Accuracy')\n",
        "plt.xlabel('Model')\n",
        "plt.title('Accuracy (on Test set) comparison ')\n",
        "plt.show()"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 864x504 with 0 Axes>"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 432x288 with 1 Axes>",
            "image/png": 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ezK233sqECROYOnUqU6dO5e6772bkyJFsscUWzJgxgzFjxgAwb948Fi5cyMCBAxk+fPiSRJMrGurRowfjxo0D4Pbbb2/0OefMmcPGG29MmzZtuOGGG1i0aBEAAwcOZMSIEcyfP3+Z83bo0IF99tmH733vexx3XHm/T+22227ceOONALz88stMmDChrOdv1Dlrr9yPrbBKFg0NACZHxFsAkm4CDgIm5e0TwFpKvm6sCcwGSvuKZq1W1s3i2rRpw2233cYpp5zCnDlzWLhwIaeeeipf+tKXOOqoo5gzZw4RwWmnnUaXLl044IADOOyww7j77ru54oor2HXXXZc53+jRo9l0003ZdNNNl6zbbbfdmDRpEu+//z4333wzJ598MgsWLKBjx448/PDDnHjiibz++uv07t2bdu3acdJJJzFs2DDOPvtsTjjhBM4//3x22GGHRq/h+9//Poceeii33nore+6555K7hX333Zfx48fTv39/2rdvz/7778/5558PwODBg7njjjsYOHBgWV/PXHLp3bs3ffv2ZcCAAWU9v2WvYpPXSzoM2DciTkyXvwPsEBHD8vZZCxgFbAGsBRwREcsV5ksaAgwB6N69e7+33250foVGrXwdwbdX6rh66kfwyiuv8JWvfCXrMOrexRdfzJw5czjvvPOyDgUow/uiFTWvbEq1fLZIGhcRRWv1K3lHUKxQsTDr7AOMB74GbA48JOnJiJi7zEER1wDXAPTv378ymcusih1yyCG8+eabPProo1mHYlWokolgOtAtb7krMKNgn+OACyK5LZksaQrJ3UH5mjyYrYBf/epX3HrrrcusO/zwwznrrLMyiqg0uY5i+XK9iPNdeOGF7LPPPi0VllWJSiaCMUAvST2BfwNHAoX3Qu8AewFPStoQ+DLwVgVjMmvSWWed1eo/9EtVLDmYFVOxRBARCyUNAx4A2gIjImKipKHp9uHAecD1kl4iKUo6IyJmVSomMzNbXkU7lEXEfcB9BeuG5z2eAZS3iYOZma2QuulZbGbZcK/+1s+DzpmZ1TnfEVj5lbt3ZzPtpj0fwYrZY489ePfdd+nYsSOffvopp512GkOGDGl0/9/97ndMmTKFyy67DIDvfve7vPnmmzz88MMAXHHFFbzxxhtcfvnlLRK/lZ8TgVU9z0ew4m688Ub69+/P7Nmz2XzzzTn22GMbTZg77bTTkiEmAMaPH8/ixYtZtGgRbdu25emnn16hAfys9XHRkNUkz0dQ2nwEH330EWussQZt27YFksH1ttlmG7beemvOOOMMALbddltef/11FixYwJw5c+jUqRN9+/blpZdeAuDpp58u6W7KWi/fEVjN8XwEzc9HMHjwYFZffXXeeOMNLrvsMtq2bcuMGTM444wzGDduHOussw4DBw7krrvu4uCDD6Zv376MGTOGBQsWsMMOO9CrVy+efvppNthgAyKCbt26Nfl81ro5EVjN8XwEzc9HkCsamjlzJjvttNOSwez22GOPJfUrgwcPZvTo0Rx88MHsvPPOPP300yxYsIAdd9yRXr16cf7559PQ0OC7gRrgRGA1JzcfQW4Y6nz33nsvo0ePZtSoUZx33nlMnDixpHPmz0cALJmPYMCAARWfj2Dx4sV06NChyfMeeuih/OIXv+BrX/vaCs1H0NDQwHbbbcdzzz3XZKX6TjvtxB/+8Ac++eQTfvCDH9DQ0MCkSZNoaGhg5513Lum5rPVyHYHVHM9HUPp8BPPnz+eFF15g8803Z4cdduCJJ55g1qxZLFq0iJEjR7L77rsDSSJ49tlnmTlzJhtssAGSaGho4O677/YdQQ3wHYGVX8ZDcHs+guY76w8ePHhJ89Fjjz12SeXyr3/9a/bcc08igv3335+DDjoIgHXWWYeGhga22mqrJefYcccd+ec//0mfPn1K/MtYa1Wx+QgqpX///jF27NgVPq5axgyvRp6PoHVorfMR1Pr/XrVcX1bzEZhZC/F8BLYqnAjM8ng+AqtHTgRWFSZM/3CljuvdZkrzO+U567j9Oeu4/WGTbVfq+VoTz0dgpXKrISuLaqtrssry+6G6OBHYKuvQoQPvv/++//kNSJLA+++/v6Tvg7V+FS0akrQv8DuSGcqujYgLCrb/BBicF8tXgIaIaL4/vrUaXbt2Zfr06cycObNiz/GfDxas1HGvaCVjmvPKyh1nQPLloGvXrlmHYSWqWCKQ1Ba4CtibZCL7MZJGRcSk3D4R8RvgN+n+BwCnOQlUn3bt2tGzZ8+KPsd+VdJEz6waVbJoaAAwOSLeiojPgJuAg5rYfxBQvYO8m5lVqUomgk2BaXnL09N1y5HUCdgXKNrnXtIQSWMlja1k8YOZWT2qZCJYfmQsaKw28QDgn40VC0XENRHRPyL650ZGNDOz8qhkIpgO5A9S3hWY0ci+R+JiITOzTFQyEYwBeknqKak9yYf9qMKdJK0N7A7cXcFYzMysERVrNRQRCyUNAx4gaT46IiImShqabh+e7noI8GBEfFypWMzMrHEV7UcQEfcB9xWsG16wfD1wfSXjMDOzxrlnsZlZnXMiMDOrc04EZmZ1zonAzKzOORGYmdU5JwIzszrnRGBmVuc8VWWN6OFhms1sJfmOwMyszjkRmJnVOScCM7M650RgZlbnnAjMzOqcE4GZWZ1zIjAzq3MVTQSS9pX0mqTJks5sZJ89JI2XNFHSE5WMx8zMllexDmWS2gJXAXuTzF88RtKoiJiUt08X4Gpg34h4R9IGlYrHzMyKq+QdwQBgckS8FRGfATcBBxXs823gjoh4ByAi/lvBeMzMrIhKJoJNgWl5y9PTdfm+BKwj6XFJ4yQdXcF4zMysiEqONaQi66LI8/cD9gI6As9IejYiXl/mRNIQYAhA9+7dKxCqmVn9quQdwXSgW95yV2BGkX3+EREfR8QsYDTQp/BEEXFNRPSPiP4NDQ0VC9jMrB5VMhGMAXpJ6impPXAkMKpgn7uBXSWtJqkTsAPwSgVjMjOzAhUrGoqIhZKGAQ8AbYERETFR0tB0+/CIeEXSP4AJwGLg2oh4uVIxmZnZ8io6H0FE3AfcV7BueMHyb4DfVDIOMzNrnCemMWsFVmZiIU8qZOXiISbMzOqcE4GZWZ1zIjAzq3NOBGZmdc6JwMyszjkRmJnVOScCM7M650RgZlbnnAjMzOqcE4GZWZ1zIjAzq3NOBGZmdc6JwMyszjkRmJnVuWYTgaRvSnLCMDOrUaV8wB8JvCHpIklfWZGTS9pX0muSJks6s8j2PSTNkTQ+/fn5ipzfzMxWXbMT00TEUZI6A4OA6yQFcB0wMiLmNXacpLbAVcDeJJPUj5E0KiImFez6ZER8c6WvwMzMVklJRT4RMRe4HbgJ2Bg4BPiXpJObOGwAMDki3oqIz9JjD1rFeM3MrMxKqSM4QNKdwKNAO2BAROwH9AFOb+LQTYFpecvT03WFdpT0oqT7JW1VeuhmZlYOpcxZfDhwaUSMzl8ZEfMlHd/EcSqyLgqW/wVsFhEfSdofuAvotdyJpCHAEIDu3buXELKZmZWqlKKhs4HncwuSOkrqARARjzRx3HSgW95yV2BG/g4RMTciPkof3we0k7R+4Yki4pqI6B8R/RsaGkoI2czMSlVKIrgVWJy3vChd15wxQC9JPSW1J2l9NCp/B0kbSVL6eEAaz/ulBG5mZuVRStHQamllLwAR8Vn6wd6kiFgoaRjwANAWGBEREyUNTbcPBw4DvidpIbAAODIiCouPzMysgkpJBDMlHRgRowAkHQTMKuXkaXHPfQXrhuc9vhK4svRwzcys3EpJBEOBGyVdSVIBPA04uqJRmZlZiymlQ9mbwFclrQmoqU5kZmZWfUq5I0DSN4CtgA5p3S4RcW4F4zIzsxZSSoey4cARwMkkRUOHA5tVOC4zM2shpTQf3SkijgY+iIhfADuybP8AMzOrYqUkgk/S3/MlbQJ8DvSsXEhmZtaSSqkj+LukLsBvSIaECOCPFY3KzMxaTJOJIJ2Q5pGI+BC4XdI9QIeImNMi0ZmZWcU1WTQUEYuB3+Ytf+okYGZWW0qpI3hQ0qG5MYHMzKy2lFJH8CNgDWChpE9ImpBGRHSuaGRmZtYiSulZvFZLBGJmZtloNhFI2q3Y+sKJaszMrDqVUjT0k7zHHUjmIh4HfK0iEZmZWYsqpWjogPxlSd2AiyoWkZmZtahSWg0Vmg5sXe5AzMwsG6XUEVzB0knn2wB9gRdLObmkfYHfkcxQdm1EXNDIftsDzwJHRMRtpZzbzMzKo5Q6grF5jxcCIyPin80dJKktcBWwN8ldxBhJoyJiUpH9LiSZ0tLMzFpYKYngNuCTiFgEyQe3pE4RMb+Z4wYAkyPirfS4m4CDgEkF+50M3A5sv0KRm5lZWZRSR/AI0DFvuSPwcAnHbUoyrWXO9HTdEpI2BQ4BhmNmZpkoJRF0iIiPcgvp404lHFdsSIooWL4MOCN3t9HoiaQhksZKGjtz5swSntrMzEpVSiL4WNJ2uQVJ/YAFJRw3nWUnsOkKzCjYpz9wk6SpwGHA1ZIOLjxRRFwTEf0jon9DQ0MJT21mZqUqpY7gVOBWSbkP8Y1Jpq5szhigl6SewL+BI4Fv5+8QEUsmuJF0PXBPRNxVwrnNzKxMSulQNkbSFsCXSYp7Xo2Iz0s4bqGkYSStgdoCIyJioqSh6XbXC5iZtQKl9CP4AXBjRLycLq8jaVBEXN3csRFxH3BfwbqiCSAiji0pYjMzK6tS6ghOSmcoAyAiPgBOqlxIZmbWkkpJBG3yJ6VJO4C1r1xIZmbWkkqpLH4AuEXScJLmn0OB+ysalZmZtZhSEsEZwBDgeySVxS+QtBwyM7Ma0GzRUDqB/bPAWyTt/vcCXqlwXGZm1kIavSOQ9CWStv+DgPeBmwEiYs+WCc3MzFpCU0VDrwJPAgdExGQASae1SFRmZtZimioaOhR4D3hM0h8l7UXx8YPMzKyKNZoIIuLOiDgC2AJ4HDgN2FDS7yUNbKH4zMyswkqpLP44Im6MiG+SDBw3Hjiz4pGZmVmLWKE5iyNidkT8ISK+VqmAzMysZa3M5PVmZlZDnAjMzOqcE4GZWZ1zIjAzq3NOBGZmda6iiUDSvpJekzRZ0nJNTiUdJGmCpPHp5PS7VDIeMzNbXimjj66UdN6Cq4C9SSayHyNpVERMytvtEWBURISk3sAtJB3YzMyshVTyjmAAMDki3oqIz4CbgIPyd4iIjyIi0sU1SOY7MDOzFlTJRLApMC1veXq6bhmSDpH0KnAvcHwF4zEzsyIqmQiKDVC33Df+dEyjLYCDgfOKnkgaktYhjJ05c2aZwzQzq2+VTATTgW55y12BGY3tHBGjgc0lrV9k2zUR0T8i+jc0NJQ/UjOzOlbJRDAG6CWpp6T2JJPcjMrfQdIXJSl9vB3QnmQSHDMzayEVazUUEQslDQMeANoCIyJioqSh6fbhJHMeHC3pc2ABcERe5bGZmbWAiiUCgIi4D7ivYN3wvMcXAhdWMgYzM2uaexabmdU5JwIzszrnRGBmVuecCMzM6pwTgZlZnXMiMDOrc04EZmZ1zonAzKzOORGYmdU5JwIzszrnRGBmVuecCMzM6pwTgZlZnXMiMDOrc04EZmZ1zonAzKzOVTQRSNpX0muSJks6s8j2wZImpD9PS+pTyXjMzGx5FUsEktoCVwH7AVsCgyRtWbDbFGD3iOgNnAdcU6l4zMysuEreEQwAJkfEWxHxGXATcFD+DhHxdER8kC4+C3StYDxmZlZEJRPBpsC0vOXp6brGnADcX2yDpCGSxkoaO3PmzDKGaGZmlUwEKrIuiu4o7UmSCM4otj0iromI/hHRv6GhoYwhmpnZahU893SgW95yV2BG4U6SegPXAvtFxPsVjMfMzIqo5B3BGKCXpJ6S2gNHAqPyd5DUHbgD+E5EvF7BWMzMrBEVuyOIiIWShgEPAG2BERExUdLQdPtw4OfAesDVkgAWRkT/SsVkZmbLq2TREBFxH3BfwbrheY9PBE6sZAxmZtY09yw2M6tzTgRmZnXOicDMrM45EZiZ1TknAjOzOudEYGZW55wIzMzqnBOBmVmdcyIwM6tzTgRmZnXOicDMrM45EZiZ1TknAjOzOudEYGZW55wIzMzqnBOBmWuGeJwAAB6KSURBVFmdq2gikLSvpNckTZZ0ZpHtW0h6RtKnkk6vZCxmZlZcxWYok9QWuArYm2Qi+zGSRkXEpLzdZgOnAAdXKg4zM2taJe8IBgCTI+KtiPgMuAk4KH+HiPhvRIwBPq9gHGZm1oRKJoJNgWl5y9PTdStM0hBJYyWNnTlzZlmCMzOzRCUTgYqsi5U5UURcExH9I6J/Q0PDKoZlZmb5KpkIpgPd8pa7AjMq+HxmZrYSKpkIxgC9JPWU1B44EhhVweczM7OVULFWQxGxUNIw4AGgLTAiIiZKGppuHy5pI2As0BlYLOlUYMuImFupuMzMbFkVSwQAEXEfcF/BuuF5j98jKTIyM7OMuGexmVmdcyIwM6tzTgRmZnXOicDMrM45EZiZ1TknAjOzOudEYGZW55wIzMzqnBOBmVmdcyIwM6tzTgRmZnXOicDMrM45EZiZ1TknAjOzOudEYGZW55wIzMzqXEUTgaR9Jb0mabKkM4tsl6TL0+0TJG1XyXjMzGx5FUsEktoCVwH7AVsCgyRtWbDbfkCv9GcI8PtKxWNmZsVV8o5gADA5It6KiM+Am4CDCvY5CPhLJJ4FukjauIIxmZlZgUrOWbwpMC1veTqwQwn7bAq8m7+TpCEkdwwAH0l6rbyhNk6wPjBrhQ/8hcofTAX4+hpRBddXy9cGvr5Grfz1bdbYhkomgmLRxkrsQ0RcA1xTjqBWlKSxEdE/i+duCb6+6lXL1wa+vpZUyaKh6UC3vOWuwIyV2MfMzCqokolgDNBLUk9J7YEjgVEF+4wCjk5bD30VmBMR7xaeyMzMKqdiRUMRsVDSMOABoC0wIiImShqabh8O3AfsD0wG5gPHVSqeVZBJkVQL8vVVr1q+NvD1tRhFLFckb2ZmdcQ9i83M6pwTgZlZnXMiMDOrc04EdUZSG0nfyjqOSqjla4Nk2BZJv8k6Dqs9TgRFSNpZ0kOSXpf0lqQpkt7KOq5yiIjFwLCs46iEWr42gIhYBPSTVB1dZ1eRpPVr5Vol7SPpsCLrB0vaO4uYlonDrYaWJ+lV4DRgHLAotz4i3s8sqDKS9H/AAuBm4OPc+oiYnVlQZVLL1wYg6bckgzTeyrLXd0dmQZVB2o/oAmA2cB5wA8kQDG2AoyPiHxmGt8okPQscEBEzC9ZvBNwZETtmE1kahxPB8iQ9FxGF4yLVDElTiqyOiPhCiwdTZrV8bQCSriuyOiLi+BYPpowkjQV+BqxN0r5+v4h4VtIWwMiI2DbTAFeRpAkR0XtFt7UUJ4IiJF1A0gnuDuDT3PqI+FdmQZnVMEnjI6Jv+viViPhK3rYXaiARvA5sGRELC9a3AyZFRK9sIktUctC5apa7G8gfECqAr2UQS9lJ6gT8COgeEUMk9QK+HBH3ZBzaKqvlawOQ9CWSeTs2jIitJfUGDoyIX2Yc2qpanPd4QcG2Wvi2egfwR0nDIuJjAElrAJen2zLlO4I6JOlmkvqPo9MPk47AM7lvZNWslq8NQNITwE+AP+S+JUt6OSK2zjayVSNpEUmdh4COJEPOkC53iIh2WcVWDpJWA34JnAi8na7uDvwJ+L+I+Dyr2MB3BEVJWhs4G9gtXfUEcG5EzMkuqrLaPCKOkDQIICIW1ErrDGr72gA6RcTzBZe0sLGdq0VEtM06hgpTRJwp6RfAF9N1kyOi8O4nE24+WtwIYB7wrfRnLlCskq5afZZ+Uw4ASZuTVxdS5Wr52gBmpdeUu77DKJjIyVqlf0v6I/BV4OWIeKm1JAFw0VBR+RVXTa2rVmm75f8lmUv6QWBn4NiIeDzLuMqhlq8NQNIXSFrV7AR8AEwBjoqIqVnGtaokzSNJbvm3OkFSatE+Iqq69ELSesBhJMPx9wJuI2kN9VymgaWcCIqQ9Azwk4h4Kl3eGbg467a+5ZS+Mb9K8o/3bESs+JR5rVQtX1tOWtHYJiLmZR1LJUhaC/g+8F2SdvY/zjikspG0CXA4SVLYALgpIs7KNCYnguVJ6gv8maRNs0g6uRwbES9mGtgqkrRFRLwqabti26u5eWwtXxuApKMi4q+SflRse0Rc0tIxVYKkLsCpwNHA34BLa6UjZz5JawL/Q9LCbeOI2DDLeKr6dqtSImI80EdS53R5bsYhlcuPgCHAb4tsq/bmsbV8bQCd0t9rZRpFhUhaH/gxcARJHd22NdQ4AwBJHYADgEEkRZb/AH5KUoSZKSeCPI1968q10KiBb10Ppb9PiIiaGDspTy1fG8Dm6e9JEXFrppFUxtvATJJGGfOBE/JbRlX7/56kvwFfB0aT3Ol8OyI+yTaqpdxqaFlrpL/XauSn2v00/X1bplFURi1fG8D+aS/Unza7Z3X6DUtb5tXi/94DJE2bD4uI21pTEgDXEdQVSQ+R3AX2BZ4s3B4RB7Z4UGVSy9cGkA4/PYTky8r8/E0kYw11ziQwK4mkA4AJEfF2uvxz4FCSO6EfRkSxMbJaLj4nguVJuoikF+ACknK8PsCpEfHXTANbRZLaA9uRjOx4YuH2iHiixYMqk1q+tnyS7o6Ig7KOo9wkXd7U9og4paViqQRJE4CvRsR8Sd8ELiGpK9gWODwi9sk0PieC5eX6DEg6BDiYZEjqxyKiT8ahlYWkhsLhcGtFLV9bLZN0TFPbI+LPLRVLJUh6Mff5IWkE8FpEXJgu/ysiirZ2aymuLC4uN67J/iSdPmbXwigFki6LiFOBEZKW+wZQzcUntXxtAJKeiohdGut4Ve1FQ9X+QV8CpU1G5wN7AVfnbeuQTUhLOREU9/d0cpoFwPclNQCtqnJnJd2Q/r440ygqo5avjYjYJf1dCxWnjUr/184g6Rm+5AMyIqq9+e9lwHiS4WpeiYixAJK2pRUMEeKioUZIWgeYGxGL0qGNO0fEe1nHVW7pdXaLiAlZx1JutXht6ThD0yPiU0l7AL2Bv0TEh9lGVh6SHiSZXe50YChwDDAzIs7INLAykNQN6Ak8Fcm0qkjaGGgXEe9kGZubjxYh6XBgYZoE/hf4K7BJxmGVjaTHJXWWtC7wInCdpKpup51Ty9eWuh1YJOmLJEMY9yRpl14r1ouIPwGfR8QTkcy89tWsgyqHiJhG0lN6cd66d7NOAuBE0Jj/i4h5knYB9iEZbuL3GcdUTmunvaX/B7guIvqRdHapBbV8bQCLI5nl6hDgsog4Ddg445jKKTcu/7uSvpEWnXTNMqAye1bS9lkHUciJoLjchPXfAH4fEXcD7TOMp9xWS29JvwXUxMxdeWr52gA+T+daOIal11fVk7YU+GU6H8iPSYqHriVptVcr9gSekfSmpAmSXkqblmbKlcXF/VvSH0i+SV4oaXVqK2meS9LT8amIGJMObfxGxjGVSy1fG8BxJGXnv4qIKZJ6khRd1oRYOqXoHJIPzVqzX9YBFOPK4iLSyuF9gZci4o30G+Y2EZH54FBmObVUGS7p/0XERZKuoMgcxdXeoayQpA1YtlWUK4tbm4iYD/wX2CVdtZAa+lYp6aK0QrWdpEckzZJ0VNZxlUMtXxvUdGX4K+nvsSRzThf+1ARJB0p6g2RCoSeAqcD9mQaF7wiKknQ20B/4ckR8KZ1I4taI2Dnj0MqilntO1/K1AUh6ISK2lXQiyd3A2ZImRETvrGOz5kl6kWRI9IfTv+OewKCIGJJlXL4jKO4Q4EDgY4CImEFtjICYs1zP6SyDKbNavjao8cpwSf0l3SnpX2ll6oTWUJlaRp+nE+20kdQmIh4jGSgxU64sLu6ziIjcUAVKpgWsJbXacxpq+9qg9ivDbwR+ArwELG5m32r0YTrUxJPAjZL+S1L0nCkXDRUh6XSSCab3Bn4NHA/8LSKuyDSwMqrlntO1fG21LjemUtZxVEr6pXIBSWnMYJLpcG/MejpOJ4ICSkaX6wpsAQwkGdzrgYh4qMkDq4ykrVl+PJe/ZBdR+dT4tXUATgC2YtnrOz6zoMpI0l4kwzM/AnyaWx8Rd2QWVJlJ2gzoFREPp19U2kbEvCxjctFQgbRI6K60R2pNffjnpJXhe5B8WN5H0rb5KaDqPyxr+dpSNwCvkvR4P5fkW+UrTR5RXY4j+RLWjqVFQwHURCKQdBLJBEPrkkw/uikwnGRE0uzi8h3B8iRdBVwfEWOyjqUSJL1EMtnOCxHRR9KGwLURcUDGoa2yWr42WKbV0ISI6K1k+soHamB0TiD5+0XENlnHUSmSxgMDgOciYtt0XebX7FZDxbXKbuBltCAd+GqhpM4kfSa+kHFM5VLL1wZLx+L5MC0CWxvokV04ZfespC2zDqKCPo2Iz3ILklajSAe6luaioeJaZTfwMhorqQvwR5LOOh8Bz2cbUtnU8rUBXJNWhv8fMApYE/h5tiGV1S7AMZKmkNQR5OZkrpV+Ek9I+hnQUdLewPeBv2cck4uGikl7bRaaFxGfF1lf1ST1IGlVU0t3PEBtX1utSitSlxPppO/VTlIbksr+JQ1RSIouM/0gdiIoQtJUoBvwAckfqwvJLEL/BU6KiKrs8i6pyXlRI+JfLRVLudXytQFI+lFT2yOiFoaZAEBSH2DXdPHJiHgxy3jqgYuGivsHcGdEPAAgaSDJIHS3kMw1ukOGsa2K3zaxLUi6vlerWr42qK2e7Y2S9EPgJJa2EvqrpGtqpQ+PpJ2Bc4DNSD5/c0VfmdZj+Y6gCEljI6J/sXW5sWyyis2slqWNMnaMiI/T5TWAZ2qljiDt9X4aSf1Vbt4Tsu5Q5juC4mZLOgO4KV0+AvhAUluquNt7OgqnIuKGgvUnAR9HRNVOeVjL1wbJqKrAWxExvGD9acBGtTCnb0rkfUCmj5VRLJUwJyIyH220kO8IipC0PnA2S4ehfoqk884coHtETM4qtlUh6QVgt8JejGkzy8fSTnRVqZavDUDSJGDr/Plu0/VtgAkRsXU2kZVXWhdyDHBnuupgkj49l2UXVflIugBoS1L0ld9zOtM6LN8RFBERs4CTJa0ZER8VbK7KJJAq2pU9IuamHZOqWS1fGyTlyMvdjUbE4nRYlJoQEZdIegLYmeRO4LiIeCHjsMopV7+YX/SceR2WE0ERknYimSt1TaB72orhuxHx/WwjW2XtJK2RK3/NkbQW1T8ncy1fG8B8Sb0iYpmRRiX1IhnErJaMJ2mltxqApO5Zz+BVLhHRKqffdCIo7lKSsVxGAUTEi5J2yzaksvgTcJuk70XEVFjS1v6qdFs1q+Vrg6TT2P2SfsnSGbv6Az8FTs0sqjKTdDJJsex/WFo/EEBVVxZLOioi/tpYM+Csm/86ETQiIqYV3HEvamzfahERF0v6iKR345rp6o+ACyLi9xmGtspq+doAIuJ+SQeTjNV/crr6ZeDQiHgpu8jK7ockMwNm2oqmAnJzmhRrBpx5Ra0ri4uQdBtwCXAl8FXgFKB/RByZaWBllH5YKuvhbyuhxq/t8Ii4tbl11UrSY8DeEZH5ZC0tRdKpWVeGOxEUkbYa+h3wdZJb0weBU2pl2sN0RM7zgU0iYr90kK8dI6Jqi1DScfqPAGaTTOH4E2A34E3gvLQBQNWT9K+I2K65ddVK0p+ALwP3smyrmprpOV1I0jsR0T3LGFw0VET6oTE4t5wO8vV94FeZBVVe1wPXAWely68DN1PdZel/IRmZcw3gdJJikytJmgBfD3wzs8jKQNJ+JPMwbyrp8rxNnWkFUx2W0TvpT3tqo5K/FJm3+nIiyCOpG8mojpuQtGMeSdJ/4Oj0ca1YPyJukfRTgIhYKKna60C2jIit02F9p0fE7un6f0iqhbFqZgBjgQNZWlkMMI+kp2pNiIhfZB1DBjIvlnEiWNZfgCeA20nGFnoWmAj0rrE5bz+WtB7pG1DSV0k6y1Wzz2BJUptRsK3akxzpwGsvSvpbbhTc9E61W0R8kG10q07SZRFxqqS/U+SDMSIOzCCsspE0j+If+AI6tnA4ywfhOoKlJL0YEX3ylv9D0pP40yYOqzrpSJ1XAFuTFKE0AIdV83DNkv5LMiSISOoKcsODCPhWRGyYVWzlJOlxkruC1Uja288EnoiIJkcnbe0k9YuIcZJ2L7Y9Ip5o6Zjqie8ICqTfsnJldu8BndKBr6iVyuKI+Ff6D/dlkmt9rQbmWvhJ3uOxBdsKl6vZ2mlv6ROB6yLi7FqYPS9vaPe+EfG7/G3piKROBBXkO4I86TwEiyleeZP5ULHlIqkT8CNgs4g4Ke2d+uWIuCfj0KwZSuZkHgj8GTgrIsYonb8449DKopFWUS9EOr+vVYbvCPJERI+sY2gh15FUOO6YLk8HbiVpdlmVJO0CfCEi/pIu3wbkZpr7ZUQ8mllw5XUuyaxW/0yTwBeAN5o5ptWTNAj4NtBT0qi8TWsBtda5rNXxHUERkg4BHo2IOelyF2CPiLgr28jKI29uhSXftArrR6qNpEeAkyNiUrr8EnAsSXPSn0XEvhmGZ81QMkVlT+DXwJl5m+aRjK5aS01kW502WQfQSp2dSwIAEfEhyfgnteIzSR1Z2mpoc/I671SpzrkkkHojIsZFxGhqaHYvSV+S9Iikl9Pl3pL+N+u4VlVEvB0Rj0fEjhHxRN7Pv5wEKs+JoLhir0stFaOdTTIdZzdJNwKPAP8v25BWWZf8hYj4n7zFmmgxlPojyUBznwOkLb2qfugTSfMkzS3yM0/S3Kzjq3W19OFWTmMlXUIycmWQDPJVlRPWF0onMlkH+B+ScZQE/LAGhmB4VdI3IuLe/JWSvgm8llFMldApIp4vGBCx6r8xR0TN3LVVIyeC4k4m6WF8M0vHGvpBphGVSTqRybCIuIVkPJda8SPgHkmHAbnZnvoBO1Hlw0sUmJUW5eWK9Q4jGbu/JkgqOuZOrcxH0Fq5srgOSfo/kslMbgaWTORSzf0k0uFB/ksyRtRW6eqJwN+A7SPiyaxiK6e0ldA1JAnuA2AKMDgi3s40sDJJK/lzOpBUIL8WEVs1coiVgRNBnjro5n59RBwraUqRzVXdT0LSW8Bw4JJc5WI6yupvSfpIbJ9lfOUgqS3J/Ao/STs5tqnFobbzpb3gvxsR3806llrmoqFl3ZD+vjjTKCqnN0BE9Mw6kAroB1wAvJD2RN2GpLjoIpJBA6teRCyS1C99/HFz+9eCtBd81Sfx1s6JIE8ddHPvJGlbGhn2NiL+VWx9NUgHXvtu+nd6mGS0zq9GxPRsIyu7F9IOV7eybLHeHdmFVD4FUzm2AbYjGU/JKshFQ0XUajf3dATEMTQ+hMbXWjikskk7/V0I7EDSFHZ/YC+SFlG10qsYSdcVWR0RcXyLB1MBkvL76ywEpgK3R8Qn2URUH5wI8uR1c98FyK9c7AwsjIivZxJYmdRCMmtMWkdwNXBZXh1B33Td2xExKMv4zFozFw0t62mSpnjrk1Qy5swDqn6Exxq3W2ExUESMB3aSdFJGMZWdpK4kQ4jvTNKg4SmSu56qLgIrGF9oOdXeUKO18x1BEWmLjAVpm/svAVsA91f7UM2SBkbEg1nHYStP0kMkTWJzDRuOImk+und2Ua06STOBaSQzAT5HQfGl5yOoLCeCIiSNA3Yl6YH7LMl49vMjYnCTB1YJSTsD5wCbkdwViipvPlovJI2PiL7Nras2adPYvYFBJK3b7gVGRsTETAOrEx5rqDhFxHySYRiuiIhDgC0zjqmc/gRcQlIXsj3QP/1trd8sSUdJapv+HEUNDNMcEYsi4h8RcQzJ0CeTgcclnZxxaHXBdQTFSdKOJL1UT0jX1dJrNSci7s86CFspxwNXApeS1BE8na6repJWB75BclfQA7gcqIlmsa2di4aKSKdx/DHJ5B8Xpt36T42IUzIOrSwkXQC0JfknWzL8dDX3I6h1kr4aEc9mHUelSPozyRza9wM3RcTLGYdUV5wI6pCkx4qsrup+BLUuv2+LpGciYsfmjqkmkhaztINc/odSrv6qc8tHVT9qqbhjldX6WEM5EbFn1jHYCstvRdMhsygqJCJcX5khJ4Jl1fpYQwBIWptkcprd0lVPAOfmz8pmrU4bSeuQNPDIPV6SHKp55FjLnouG6pCk24GXgT+nq74D9CmY1ctaEUlTgcU0PjyIm/7aSnMiKCIdE73whZlD0p/glxFR1c31arUtupmtHBcNFXc/sIikByckc8KKJBlcDxyQTVhls0DSLhHxFCzpYLYg45isRJJ6kzSvXPL/Wyujj1o2fEdQhKR/RsTOxdZJeikitskqtnJIB2P7M7A2SYKbDRwbES9mGpg1S9IIkp63E0mKiqCGRh+1bPiOoLg1Je0QEc8BSBoArJluq4WJwscDfSR1TpfnZhySle6rEVFLvdytFXAiKO5EYISkNUm+Mc8FTkgHo/t1ppGtAklHRcRfCyb/QErqHyPikkwCsxXxjKQtI2JS1oFY7XAiKCIixgDbpM0sFREf5m2+JaOwymGN9PdamUZhq+LPJMngPZJe4bkOV72zDcuqmesIinA7e2utJE0mmYv5JZbWERARb2cWlFU99+YrbgTJZDTfSn/mAsWmCKxKki6S1FlSO0mPSJqVjmJprd87ETEqIqZExNu5n6yDsurmO4Iiar2dfe5aJB0CHAycBjwWEX0yDs2aIelqoAvwd5YdMNDNR22luY6guFpvZ98u/b0/yeQfs3MVxtbqdSRJAAPz1gUertlWgRNBcUOBv6R1BQAfAMdkGE+5/V3SqyTJ7fuSGoBPMo7JShARx2Udg9UeFw01Ib+dvaRTI+KyrGMql3TQsrkRsUhSJ6BzRLyXdVzWtFqdvN6y5URQIknvRET3rONYFZK+FhGPSio6uJzLmVu/Wp283rLloqHS1UIh+u7AoxQfK8nlzNWhISLyW7BdL+nUzKKxmuBEULqqv3WKiLPT3y5nrl65pr4j0+VB1MDk9ZYt9yPII2mepLlFfuYBm2QdX7lIOl9Sl7zldST9MsuYrGTHk/RteQ94FziMGpm83rLjOoI6JOmFiNi2YN2SOXHNrL64aKg+tZW0ekR8CiCpI7B6xjFZEyRdQRPFkxFxSguGYzXGRUP16a/AI5JOkHQ88BBLp6201mksMI5k4vrtgDfSn74kkyiZrTQXDdUpSfsCXydpDfVgRDyQcUhWAkmPAQMj4vN0uR3J32/PbCOzauaiofr1CrAwIh6W1EnSWhExL+ugrFmbkAwjPjtdXpMaashg2XAiqEOSTgKGAOsCmwObAsOBvbKMy0pyAfBCemcASd+Qc7ILx2qBi4bqkKTxwADguVzroVqYi7leSNoI2CFdfM5Dg9iqcmVxffo0Ij7LLUhajRroMFdH2gIzSQZD/JKk3ZrZ36xJLhqqT09I+hnQUdLewPdJxre3Vk7ShcARwESWzlAWwOjMgrKq56KhOiSpDXACyZj2Ah4Arg2/GVo9Sa8BvXN9QMzKwYmgTqVzEBARM7OOxUon6X7g8Ij4KOtYrHa4aKiOKJmG7GxgGMmdgCQtAq6IiHMzDc5KNR8YL+kRlp2q0j2LbaU5EdSXU0kmNNk+IqYASPoC8HtJp0XEpZlGZ6UYlf6YlY2LhuqIpBeAvSNiVsH6BpLeqdsWP9LMapnvCOpLu8IkAEk9QTpUgbVyknoBvwa2JBl3CICI+EJmQVnVcz+C+vLZSm6z1uM64PfAQmBP4C8snbbSbKW4aKiOpBXDHxfbBHSICN8VtHKSxkVEv/ye4JKejIhds47NqpeLhupIRLTNOgZbZZ+k/UDekDQM+DewQcYxWZXzHYFZFZG0PcnIsV2A84C1gQsj4rlMA7Oq5kRgVsXScaKOiIgbs47Fqpcri82qgKTOkn4q6UpJA5UYBkwmmczebKX5jsCsCki6m2S00WdI5o1YB2gP/DAixmcZm1U/JwKzKlDQSqgtMAvo7lnlrBxcNGRWHT7PPYiIRcAUJwErF98RmFWBgj4gAjqSDEAnICKic1axWfVzIjAzq3MuGjIzq3NOBGZmdc6JwKwISSHphrzl1STNlHTPCp5nqqT1V3Ufs0pyIjAr7mNga0kd0+W9Scb1Mas5TgRmjbsf+Eb6eBAwMrdB0rqS7pI0QdKzknqn69eT9KCkFyT9gaRVT+6YoyQ9L2m8pD+k/QHMMudEYNa4m4AjJXUAegP5A7v9AnghInoDPyOZFwCSOaGfSmd7GwV0B5D0FeAIYOeI6AssAga3yFWYNcPDUJs1IiImSOpBcjdwX8HmXYBD0/0eTe8E1gZ2A/4nXX+vpA/S/fcC+gFjJEHSD+C/lb4Gs1I4EZg1bRRwMbAHsF7eehXZNwp+5xPw54j4aVmjMysDFw2ZNW0EcG5EvFSwfjRp0Y6kPYBZETG3YP1+JIPDATwCHCZpg3TbupI2q3z4Zs3zHYFZEyJiOvC7IpvOAa6TNIFkqIdj0vW/AEZK+hfwBPBOep5Jkv4XeDCdYexz4AfA25W9ArPmeYgJM7M656IhM7M650RgZlbnnAjMzOqcE4GZWZ1zIjAzq3NOBGZmdc6JwMyszjkRmJnVuf8PRZHL2ZU9O9AAAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 29,
      "metadata": {
        "gather": {
          "logged": 1642616490238
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#   Top 20 Feature used by LinearSVC\n",
        "feature_names = vectorizer_tfidf.get_feature_names() \n",
        "coefs_with_fns = sorted(zip(model_tfidf[5].coef_[0], feature_names)) \n",
        "word_coefficient=pd.DataFrame(coefs_with_fns)\n",
        "word_coefficient.columns='coefficient','word'\n",
        "word_coefficient_sorted = word_coefficient.sort_values(by='coefficient')\n",
        "word_coefficient_positive = word_coefficient_sorted.tail(15)\n",
        "word_coefficient_negative = word_coefficient_sorted.head(15)\n",
        "plt.figure(figsize=(12,7))\n",
        "plt.bar(word_coefficient_negative['word'],word_coefficient_negative['coefficient'] , color='red')\n",
        "plt.bar(word_coefficient_positive['word'],word_coefficient_positive['coefficient'] , color='green')\n",
        "plt.xticks(rotation = 90)\n",
        "plt.title('Top 15 Negative/Positive Features')\n",
        "plt.xlabel(\"Word\")\n",
        "plt.ylabel(\"Coefficient\")\n",
        "plt.show()"
      ],
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 864x504 with 1 Axes>",
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "execution_count": 30,
      "metadata": {
        "gather": {
          "logged": 1642616502726
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Fine-Tuning Parameters "
      ],
      "metadata": {
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "For LinearSVC Classifier using TF-IDF Vectorizer"
      ],
      "metadata": {
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# We choose the model with the best F1 score and done a fine tuning to find best parameters\n",
        "\n",
        "from sklearn.pipeline import Pipeline\n",
        "pipeline = Pipeline([\n",
        "           ('vect', TfidfVectorizer(preprocessor=' '.join,ngram_range=(1,3))),\n",
        "           ('clf', LinearSVC(loss='hinge')),\n",
        "])\n",
        "parameters = {\n",
        "'vect__max_df': (0.2, 0.3, 0.4, 0.5),\n",
        "'clf__C':(0.8, 0.9, 1, 1.1, 1.2)\n",
        "}\n",
        "\n",
        "grid_search_svc = GridSearchCV(pipeline, parameters, n_jobs=-1, scoring='f1_macro',verbose=10, cv=5)\n",
        "grid_search_svc.fit(X_train,y_train)"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "Fitting 5 folds for each of 20 candidates, totalling 100 fits\n"
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 4 concurrent workers.\n[Parallel(n_jobs=-1)]: Done   5 tasks      | elapsed:  1.3min\n[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:  2.7min\n[Parallel(n_jobs=-1)]: Done  17 tasks      | elapsed:  4.4min\n[Parallel(n_jobs=-1)]: Done  24 tasks      | elapsed:  6.0min\n[Parallel(n_jobs=-1)]: Done  33 tasks      | elapsed:  8.2min\n[Parallel(n_jobs=-1)]: Done  42 tasks      | elapsed: 10.5min\n[Parallel(n_jobs=-1)]: Done  53 tasks      | elapsed: 13.5min\n[Parallel(n_jobs=-1)]: Done  64 tasks      | elapsed: 16.6min\n[Parallel(n_jobs=-1)]: Done  77 tasks      | elapsed: 20.6min\n[Parallel(n_jobs=-1)]: Done  90 tasks      | elapsed: 24.3min\n[Parallel(n_jobs=-1)]: Done 100 out of 100 | elapsed: 27.4min finished\n/anaconda/envs/azureml_py36/lib/python3.6/site-packages/sklearn/svm/_base.py:947: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n  \"the number of iterations.\", ConvergenceWarning)\n"
        },
        {
          "output_type": "execute_result",
          "execution_count": 31,
          "data": {
            "text/plain": "GridSearchCV(cv=5, error_score=nan,\n             estimator=Pipeline(memory=None,\n                                steps=[('vect',\n                                        TfidfVectorizer(analyzer='word',\n                                                        binary=False,\n                                                        decode_error='strict',\n                                                        dtype=<class 'numpy.float64'>,\n                                                        encoding='utf-8',\n                                                        input='content',\n                                                        lowercase=True,\n                                                        max_df=1.0,\n                                                        max_features=None,\n                                                        min_df=1,\n                                                        ngram_range=(1, 3),\n                                                        norm='l2',\n                                                        preprocessor=<built-in method join of str object at 0x7fda22846650>...\n                                                  dual=True, fit_intercept=True,\n                                                  intercept_scaling=1,\n                                                  loss='hinge', max_iter=1000,\n                                                  multi_class='ovr',\n                                                  penalty='l2',\n                                                  random_state=None, tol=0.0001,\n                                                  verbose=0))],\n                                verbose=False),\n             iid='deprecated', n_jobs=-1,\n             param_grid={'clf__C': (0.8, 0.9, 1, 1.1, 1.2),\n                         'vect__max_df': (0.2, 0.3, 0.4, 0.5)},\n             pre_dispatch='2*n_jobs', refit=True, return_train_score=False,\n             scoring='f1_macro', verbose=10)"
          },
          "metadata": {}
        }
      ],
      "execution_count": 31,
      "metadata": {
        "gather": {
          "logged": 1642618235033
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "grid_search_svc.best_params_"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 32,
          "data": {
            "text/plain": "{'clf__C': 1.2, 'vect__max_df': 0.3}"
          },
          "metadata": {}
        }
      ],
      "execution_count": 32,
      "metadata": {
        "gather": {
          "logged": 1642618235508
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "grid_svc_df = pd.concat([pd.DataFrame(grid_search_svc.cv_results_[\"params\"]),pd.DataFrame(grid_search_svc.cv_results_[\"mean_test_score\"], columns=[\"f1_score\"])],axis=1)\n",
        "grid_svc_df.to_csv('grid_svc_df.csv')\n",
        "grid_svc_df"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 33,
          "data": {
            "text/plain": "    clf__C  vect__max_df  f1_score\n0      0.8           0.2  0.820806\n1      0.8           0.3  0.820735\n2      0.8           0.4  0.820735\n3      0.8           0.5  0.820735\n4      0.9           0.2  0.822079\n5      0.9           0.3  0.822050\n6      0.9           0.4  0.822050\n7      0.9           0.5  0.822050\n8      1.0           0.2  0.822428\n9      1.0           0.3  0.822618\n10     1.0           0.4  0.822618\n11     1.0           0.5  0.822618\n12     1.1           0.2  0.822941\n13     1.1           0.3  0.822997\n14     1.1           0.4  0.822997\n15     1.1           0.5  0.822997\n16     1.2           0.2  0.823231\n17     1.2           0.3  0.823377\n18     1.2           0.4  0.823377\n19     1.2           0.5  0.823377",
            "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>clf__C</th>\n      <th>vect__max_df</th>\n      <th>f1_score</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0.8</td>\n      <td>0.2</td>\n      <td>0.820806</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0.8</td>\n      <td>0.3</td>\n      <td>0.820735</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0.8</td>\n      <td>0.4</td>\n      <td>0.820735</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0.8</td>\n      <td>0.5</td>\n      <td>0.820735</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0.9</td>\n      <td>0.2</td>\n      <td>0.822079</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>0.9</td>\n      <td>0.3</td>\n      <td>0.822050</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>0.9</td>\n      <td>0.4</td>\n      <td>0.822050</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>0.9</td>\n      <td>0.5</td>\n      <td>0.822050</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>1.0</td>\n      <td>0.2</td>\n      <td>0.822428</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>1.0</td>\n      <td>0.3</td>\n      <td>0.822618</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>1.0</td>\n      <td>0.4</td>\n      <td>0.822618</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>1.0</td>\n      <td>0.5</td>\n      <td>0.822618</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>1.1</td>\n      <td>0.2</td>\n      <td>0.822941</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>1.1</td>\n      <td>0.3</td>\n      <td>0.822997</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>1.1</td>\n      <td>0.4</td>\n      <td>0.822997</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>1.1</td>\n      <td>0.5</td>\n      <td>0.822997</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td>1.2</td>\n      <td>0.2</td>\n      <td>0.823231</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>1.2</td>\n      <td>0.3</td>\n      <td>0.823377</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>1.2</td>\n      <td>0.4</td>\n      <td>0.823377</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>1.2</td>\n      <td>0.5</td>\n      <td>0.823377</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
          },
          "metadata": {}
        }
      ],
      "execution_count": 33,
      "metadata": {
        "gather": {
          "logged": 1642618236009
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "For LogisticRegression Classifier using BoW"
      ],
      "metadata": {
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.pipeline import Pipeline\n",
        "pipeline = Pipeline([\n",
        "           ('vect', CountVectorizer(preprocessor=' '.join,ngram_range=(1,3))),\n",
        "           ('clf', LogisticRegression(multi_class='ovr')),\n",
        "])\n",
        "parameters = {\n",
        "'vect__max_df': (0.2, 0.3, 0.4, 0.5),\n",
        "'clf__C':(0.8, 0.9, 1, 1.1, 1.2)\n",
        "}\n",
        "\n",
        "grid_search_lr = GridSearchCV(pipeline, parameters, n_jobs=-1, scoring='f1_macro',verbose=10, cv=5)\n",
        "grid_search_lr.fit(X_train,y_train)"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "Fitting 5 folds for each of 20 candidates, totalling 100 fits\n"
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 4 concurrent workers.\n[Parallel(n_jobs=-1)]: Done   5 tasks      | elapsed:  2.6min\n[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:  3.9min\n[Parallel(n_jobs=-1)]: Done  17 tasks      | elapsed:  6.4min\n[Parallel(n_jobs=-1)]: Done  24 tasks      | elapsed:  7.7min\n[Parallel(n_jobs=-1)]: Done  33 tasks      | elapsed: 11.4min\n[Parallel(n_jobs=-1)]: Done  42 tasks      | elapsed: 14.1min\n[Parallel(n_jobs=-1)]: Done  53 tasks      | elapsed: 17.7min\n[Parallel(n_jobs=-1)]: Done  64 tasks      | elapsed: 20.5min\n[Parallel(n_jobs=-1)]: Done  77 tasks      | elapsed: 25.2min\n[Parallel(n_jobs=-1)]: Done  90 tasks      | elapsed: 29.3min\n[Parallel(n_jobs=-1)]: Done 100 out of 100 | elapsed: 32.0min finished\n/anaconda/envs/azureml_py36/lib/python3.6/site-packages/sklearn/linear_model/_logistic.py:940: ConvergenceWarning: lbfgs failed to converge (status=1):\nSTOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n\nIncrease the number of iterations (max_iter) or scale the data as shown in:\n    https://scikit-learn.org/stable/modules/preprocessing.html\nPlease also refer to the documentation for alternative solver options:\n    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n  extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG)\n"
        },
        {
          "output_type": "execute_result",
          "execution_count": 34,
          "data": {
            "text/plain": "GridSearchCV(cv=5, error_score=nan,\n             estimator=Pipeline(memory=None,\n                                steps=[('vect',\n                                        CountVectorizer(analyzer='word',\n                                                        binary=False,\n                                                        decode_error='strict',\n                                                        dtype=<class 'numpy.int64'>,\n                                                        encoding='utf-8',\n                                                        input='content',\n                                                        lowercase=True,\n                                                        max_df=1.0,\n                                                        max_features=None,\n                                                        min_df=1,\n                                                        ngram_range=(1, 3),\n                                                        preprocessor=<built-in method join of str object at 0x7fda22846650>,\n                                                        stop_words=...\n                                                           l1_ratio=None,\n                                                           max_iter=100,\n                                                           multi_class='ovr',\n                                                           n_jobs=None,\n                                                           penalty='l2',\n                                                           random_state=None,\n                                                           solver='lbfgs',\n                                                           tol=0.0001,\n                                                           verbose=0,\n                                                           warm_start=False))],\n                                verbose=False),\n             iid='deprecated', n_jobs=-1,\n             param_grid={'clf__C': (0.8, 0.9, 1, 1.1, 1.2),\n                         'vect__max_df': (0.2, 0.3, 0.4, 0.5)},\n             pre_dispatch='2*n_jobs', refit=True, return_train_score=False,\n             scoring='f1_macro', verbose=10)"
          },
          "metadata": {}
        }
      ],
      "execution_count": 34,
      "metadata": {
        "gather": {
          "logged": 1642620229031
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "grid_search_lr.best_params_"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 35,
          "data": {
            "text/plain": "{'clf__C': 1.2, 'vect__max_df': 0.3}"
          },
          "metadata": {}
        }
      ],
      "execution_count": 35,
      "metadata": {
        "gather": {
          "logged": 1642620229540
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "grid_lr_df = pd.concat([pd.DataFrame(grid_search_lr.cv_results_[\"params\"]),pd.DataFrame(grid_search_lr.cv_results_[\"mean_test_score\"], columns=[\"f1_score\"])],axis=1)\n",
        "grid_lr_df.to_csv('grid_lr_df.csv')\n",
        "grid_lr_df"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 36,
          "data": {
            "text/plain": "    clf__C  vect__max_df  f1_score\n0      0.8           0.2  0.819608\n1      0.8           0.3  0.819412\n2      0.8           0.4  0.819412\n3      0.8           0.5  0.819412\n4      0.9           0.2  0.819573\n5      0.9           0.3  0.819453\n6      0.9           0.4  0.819453\n7      0.9           0.5  0.819453\n8      1.0           0.2  0.819710\n9      1.0           0.3  0.819704\n10     1.0           0.4  0.819704\n11     1.0           0.5  0.819704\n12     1.1           0.2  0.819654\n13     1.1           0.3  0.819852\n14     1.1           0.4  0.819852\n15     1.1           0.5  0.819852\n16     1.2           0.2  0.819807\n17     1.2           0.3  0.819941\n18     1.2           0.4  0.819941\n19     1.2           0.5  0.819941",
            "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>clf__C</th>\n      <th>vect__max_df</th>\n      <th>f1_score</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0.8</td>\n      <td>0.2</td>\n      <td>0.819608</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0.8</td>\n      <td>0.3</td>\n      <td>0.819412</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0.8</td>\n      <td>0.4</td>\n      <td>0.819412</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0.8</td>\n      <td>0.5</td>\n      <td>0.819412</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0.9</td>\n      <td>0.2</td>\n      <td>0.819573</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>0.9</td>\n      <td>0.3</td>\n      <td>0.819453</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>0.9</td>\n      <td>0.4</td>\n      <td>0.819453</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>0.9</td>\n      <td>0.5</td>\n      <td>0.819453</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>1.0</td>\n      <td>0.2</td>\n      <td>0.819710</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>1.0</td>\n      <td>0.3</td>\n      <td>0.819704</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>1.0</td>\n      <td>0.4</td>\n      <td>0.819704</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>1.0</td>\n      <td>0.5</td>\n      <td>0.819704</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>1.1</td>\n      <td>0.2</td>\n      <td>0.819654</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>1.1</td>\n      <td>0.3</td>\n      <td>0.819852</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>1.1</td>\n      <td>0.4</td>\n      <td>0.819852</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>1.1</td>\n      <td>0.5</td>\n      <td>0.819852</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td>1.2</td>\n      <td>0.2</td>\n      <td>0.819807</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>1.2</td>\n      <td>0.3</td>\n      <td>0.819941</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>1.2</td>\n      <td>0.4</td>\n      <td>0.819941</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>1.2</td>\n      <td>0.5</td>\n      <td>0.819941</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
          },
          "metadata": {}
        }
      ],
      "execution_count": 36,
      "metadata": {
        "gather": {
          "logged": 1642620231065
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "We then trained the model with the best parameters obtained in the GridSearch"
      ],
      "metadata": {
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Results"
      ],
      "metadata": {
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Using parameters {'clf__C': 1.2, 'vect__max_df': 0.3}\n",
        "# We computed a grid search on a larger server to ensure that we use the best features like\n",
        "# ngram_range = 1, 3\n",
        "# min_df = 0.0\n",
        "\n",
        "# Vect\n",
        "grid_vectorizer_tfidf = TfidfVectorizer(preprocessor=' '.join, ngram_range=(1,3), max_df=0.3)\n",
        "grid_vectorizer_tfidf.fit(X_train)\n",
        "X_train_tfidf_g = grid_vectorizer_tfidf.transform(X_train)\n",
        "X_test_tfidf_g = grid_vectorizer_tfidf.transform(X_test)\n",
        "\n",
        "# Model\n",
        "svc_best_param = LinearSVC(C=1.2, loss='hinge', max_iter=5000)\n",
        "\n",
        "svc_best_param.fit(X_train_tfidf_g,y_train)\n",
        "\n",
        "# Prediction\n",
        "y_pred_svc = svc_best_param.predict(X_test_tfidf_g)\n",
        "# Score\n",
        "print(classification_report(y_pred_svc, y_test))\n",
        "print(f1_score(y_test, y_pred_svc))"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "              precision    recall  f1-score   support\n\n           0       0.82      0.79      0.81     19543\n           1       0.84      0.87      0.85     25069\n\n    accuracy                           0.83     44612\n   macro avg       0.83      0.83      0.83     44612\nweighted avg       0.83      0.83      0.83     44612\n\n0.8541687125601493\n"
        }
      ],
      "execution_count": 37,
      "metadata": {
        "gather": {
          "logged": 1642620409981
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Using parameters {'clf__C': 1.1, 'vect__max_df': 0.3}\n",
        "# We computed a grid search on a larger server to ensure that we use the best features like\n",
        "# ngram_range = 1, 3\n",
        "# min_df = 0.0\n",
        "\n",
        "# Vect\n",
        "grid_vectorizer_bow = CountVectorizer(preprocessor=' '.join, ngram_range=(1,3), max_df=0.3)\n",
        "grid_vectorizer_bow.fit(X_train)\n",
        "X_train_bow_g = grid_vectorizer_bow.transform(X_train)\n",
        "X_test_bow_g = grid_vectorizer_bow.transform(X_test)\n",
        "\n",
        "# Model\n",
        "lr_best_param = LogisticRegression(multi_class='ovr', max_iter=5000)\n",
        "\n",
        "lr_best_param.fit(X_train_bow_g,y_train)\n",
        "\n",
        "# Prediction\n",
        "y_pred_lr = lr_best_param.predict(X_test_bow_g)\n",
        "# Score\n",
        "print(classification_report(y_pred_lr, y_test))\n",
        "print(f1_score(y_test, y_pred_lr))"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "              precision    recall  f1-score   support\n\n           0       0.77      0.82      0.79     17688\n           1       0.88      0.84      0.86     26924\n\n    accuracy                           0.83     44612\n   macro avg       0.82      0.83      0.83     44612\nweighted avg       0.83      0.83      0.83     44612\n\n0.8572294864506349\n"
        }
      ],
      "execution_count": 38,
      "metadata": {
        "gather": {
          "logged": 1642620598112
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Prediction on the evaluation set"
      ],
      "metadata": {
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_eval = pd.read_csv(\"DSL2122_january_dataset/evaluation.csv\")"
      ],
      "outputs": [],
      "execution_count": 39,
      "metadata": {
        "gather": {
          "logged": 1642620598782
        },
        "jupyter": {
          "outputs_hidden": false,
          "source_hidden": false
        },
        "nteract": {
          "transient": {
            "deleting": false
          }
        }
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_eval = df_eval[['user','text']]\n",
        "df_eval['fixed_text'] = df_eval['text'].apply(textPreprocessor)\n",
        "df_eval['fixed_text'] = df_eval['user'] + ' ' + df_eval['fixed_text']\n",
        "df_eval"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 40,
          "data": {
            "text/plain": "                  user                                               text  \\\n0      urbanperspectiv  @engteacher I'm pretty much the same ...in eit...   \n1        therealsecret      @JaxLicurse same here  have a gr8 week ahead    \n2           bitchville     @blacksweater  that's just nightmares all over   \n3            epi_longo  @dlead @jishanvn cháº¯c pháº£i Äi thi Äáº¡i ...   \n4          Curiosafmmb        @CA_Sweetie awe. ok sweetie. ttyl.   *hugs*   \n...                ...                                                ...   \n74994            Irv25  @NIYANA man down,code 10...I'm going 2 try &am...   \n74995        iHomeTech  @senhordaguerra Thank you for following me: I ...   \n74996     danger_skies  Why isn't Friday's Hollyoaks available for dow...   \n74997      tracyewilli  @hollywilli she WAS !!! she was a MADAM they q...   \n74998          jjanika  Plans for today = shower, shopping, rent some ...   \n\n                                              fixed_text  \n0      urbanperspectiv  engteacher i am pretty much t...  \n1      therealsecret  jaxlicurse same here  have a gr...  \n2      bitchville  blacksweater  that is just nightma...  \n3      epi_longo  dlead  jishanvn ch c ph i  i thi  i...  \n4      Curiosafmmb  ca_sweetie awe  ok sweetie  talk ...  \n...                                                  ...  \n74994  Irv25  niyana man down code  i am going  try  ...  \n74995  iHomeTech  senhordaguerra thank you for follow...  \n74996  danger_skies why is not NEG_friday s hollyoaks...  \n74997  tracyewilli  hollywilli she was   she was a ma...  \n74998  jjanika plans for today   shower  shopping  re...  \n\n[74999 rows x 3 columns]",
            "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>user</th>\n      <th>text</th>\n      <th>fixed_text</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>urbanperspectiv</td>\n      <td>@engteacher I'm pretty much the same ...in eit...</td>\n      <td>urbanperspectiv  engteacher i am pretty much t...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>therealsecret</td>\n      <td>@JaxLicurse same here  have a gr8 week ahead</td>\n      <td>therealsecret  jaxlicurse same here  have a gr...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>bitchville</td>\n      <td>@blacksweater  that's just nightmares all over</td>\n      <td>bitchville  blacksweater  that is just nightma...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>epi_longo</td>\n      <td>@dlead @jishanvn cháº¯c pháº£i Äi thi Äáº¡i ...</td>\n      <td>epi_longo  dlead  jishanvn ch c ph i  i thi  i...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Curiosafmmb</td>\n      <td>@CA_Sweetie awe. ok sweetie. ttyl.   *hugs*</td>\n      <td>Curiosafmmb  ca_sweetie awe  ok sweetie  talk ...</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>74994</th>\n      <td>Irv25</td>\n      <td>@NIYANA man down,code 10...I'm going 2 try &amp;am...</td>\n      <td>Irv25  niyana man down code  i am going  try  ...</td>\n    </tr>\n    <tr>\n      <th>74995</th>\n      <td>iHomeTech</td>\n      <td>@senhordaguerra Thank you for following me: I ...</td>\n      <td>iHomeTech  senhordaguerra thank you for follow...</td>\n    </tr>\n    <tr>\n      <th>74996</th>\n      <td>danger_skies</td>\n      <td>Why isn't Friday's Hollyoaks available for dow...</td>\n      <td>danger_skies why is not NEG_friday s hollyoaks...</td>\n    </tr>\n    <tr>\n      <th>74997</th>\n      <td>tracyewilli</td>\n      <td>@hollywilli she WAS !!! she was a MADAM they q...</td>\n      <td>tracyewilli  hollywilli she was   she was a ma...</td>\n    </tr>\n    <tr>\n      <th>74998</th>\n      <td>jjanika</td>\n      <td>Plans for today = shower, shopping, rent some ...</td>\n      <td>jjanika plans for today   shower  shopping  re...</td>\n    </tr>\n  </tbody>\n</table>\n<p>74999 rows × 3 columns</p>\n</div>"
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        "df_eval[\"stemmed\"] =  df_eval[\"fixed_text\"].apply(lambda x: [stemmer.stem(word) for word in x.split(' ')])"
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      "execution_count": 41,
      "metadata": {
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        "y_eval = lr_best_param.predict(X_eval)"
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      "execution_count": 43,
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        "df_eval['Predicted'] = y_eval"
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      "execution_count": 44,
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        "pd.DataFrame(y_eval, index=df_eval.index).to_csv(\"bow_lr_bestparams_19_01.csv\", index_label=\"Id\", header=[\"Predicted\"])"
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      "execution_count": 45,
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        "X_eval = grid_vectorizer_tfidf.transform(df_eval['stemmed'])\n",
        "y_eval = svc_best_param.predict(X_eval)"
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      "execution_count": 46,
      "metadata": {
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      "outputs": [],
      "execution_count": 49,
      "metadata": {
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