SentimentAnalysis_CSCI544.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# NLP Homework 1\n",
        "submission by Harshitha B R\n",
        "\n",
        "Task - Bnary Text Classification for classifying sentiment of reviews"
      ],
      "metadata": {
        "id": "LR1EHjcbMfWd"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ObiSRL_kh_qs",
        "outputId": "854c2792-46cf-4c01-8cf9-0f99332d77ab"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[nltk_data] Downloading package wordnet to /root/nltk_data...\n"
          ]
        }
      ],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import nltk\n",
        "nltk.download('wordnet')\n",
        "import re\n",
        "from bs4 import BeautifulSoup\n",
        "import nltk\n",
        "from nltk.corpus import stopwords\n",
        "from nltk.stem import WordNetLemmatizer\n",
        "from nltk import pos_tag\n",
        "from nltk.tokenize import word_tokenize\n",
        "\n",
        "import string\n",
        "! pip install contractions\n",
        "import contractions\n",
        "\n",
        "from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.metrics import accuracy_score, f1_score, precision_score, recall_score\n",
        "\n",
        "from sklearn.linear_model import Perceptron\n",
        "from sklearn.naive_bayes import MultinomialNB\n",
        "from sklearn.model_selection import GridSearchCV\n",
        "from sklearn.svm import LinearSVC\n",
        "from sklearn.metrics import classification_report\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cpySxNTYh_qy",
        "outputId": "976fdfed-8433-4381-a4e1-862241541cc2"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting bs4\n",
            "  Downloading bs4-0.0.1.tar.gz (1.1 kB)\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: beautifulsoup4 in /usr/local/lib/python3.10/dist-packages (from bs4) (4.11.2)\n",
            "Requirement already satisfied: soupsieve>1.2 in /usr/local/lib/python3.10/dist-packages (from beautifulsoup4->bs4) (2.5)\n",
            "Building wheels for collected packages: bs4\n",
            "  Building wheel for bs4 (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for bs4: filename=bs4-0.0.1-py3-none-any.whl size=1256 sha256=c375a0bd2eab138c5b301dc9b16d1f1cd926876e77f87ffb5aaf9bd19e96b2d0\n",
            "  Stored in directory: /root/.cache/pip/wheels/25/42/45/b773edc52acb16cd2db4cf1a0b47117e2f69bb4eb300ed0e70\n",
            "Successfully built bs4\n",
            "Installing collected packages: bs4\n",
            "Successfully installed bs4-0.0.1\n"
          ]
        }
      ],
      "source": [
        "\n",
        "\n",
        "! pip install bs4 # in case you don't have it installed\n",
        "\n",
        "# Dataset: https://web.archive.org/web/20201127142707if_/https://s3.amazonaws.com/amazon-reviews-pds/tsv/amazon_reviews_us_Office_Products_v1_00.tsv.gz"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-By2GkMoh_qz"
      },
      "source": [
        "## Read Data"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "T2-Hl8Cki_L4",
        "outputId": "9be72d27-4ef5-4cb6-e0e2-e207d91032bd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "reading the data from tsv file using read_csv:\n"
      ],
      "metadata": {
        "id": "7-5yjszPN_59"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
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        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zH68WI6lh_q1",
        "outputId": "97e34a63-3f03-43b6-8179-a133982db659"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-4-6f2b01c50d79>:1: FutureWarning: The error_bad_lines argument has been deprecated and will be removed in a future version. Use on_bad_lines in the future.\n",
            "\n",
            "\n",
            "  df = pd.read_csv('/content/drive/MyDrive/Colab Notebooks/ANLP/amazon_reviews_us_Office_Products_v1_00.tsv.gz', sep='\\t', error_bad_lines=False)\n",
            "Skipping line 20773: expected 15 fields, saw 22\n",
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            "\n",
            "<ipython-input-4-6f2b01c50d79>:1: DtypeWarning: Columns (7) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv('/content/drive/MyDrive/Colab Notebooks/ANLP/amazon_reviews_us_Office_Products_v1_00.tsv.gz', sep='\\t', error_bad_lines=False)\n"
          ]
        }
      ],
      "source": [
        "df = pd.read_csv('/content/drive/MyDrive/Colab Notebooks/ANLP/amazon_reviews_us_Office_Products_v1_00.tsv.gz', sep='\\t', error_bad_lines=False)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 504
        },
        "id": "jpmS3RtTEYPi",
        "outputId": "2280387c-0c73-473f-d270-e05a3387166d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  marketplace  customer_id       review_id  product_id  product_parent  \\\n",
              "0          US     43081963  R18RVCKGH1SSI9  B001BM2MAC       307809868   \n",
              "1          US     10951564  R3L4L6LW1PUOFY  B00DZYEXPQ        75004341   \n",
              "2          US     21143145  R2J8AWXWTDX2TF  B00RTMUHDW       529689027   \n",
              "3          US     52782374  R1PR37BR7G3M6A  B00D7H8XB6       868449945   \n",
              "4          US     24045652  R3BDDDZMZBZDPU  B001XCWP34        33521401   \n",
              "\n",
              "                                       product_title product_category  \\\n",
              "0     Scotch Cushion Wrap 7961, 12 Inches x 100 Feet  Office Products   \n",
              "1          Dust-Off Compressed Gas Duster, Pack of 4  Office Products   \n",
              "2  Amram Tagger Standard Tag Attaching Tagging Gu...  Office Products   \n",
              "3  AmazonBasics 12-Sheet High-Security Micro-Cut ...  Office Products   \n",
              "4  Derwent Colored Pencils, Inktense Ink Pencils,...  Office Products   \n",
              "\n",
              "  star_rating  helpful_votes  total_votes vine verified_purchase  \\\n",
              "0           5            0.0          0.0    N                 Y   \n",
              "1           5            0.0          1.0    N                 Y   \n",
              "2           5            0.0          0.0    N                 Y   \n",
              "3           1            2.0          3.0    N                 Y   \n",
              "4           4            0.0          0.0    N                 Y   \n",
              "\n",
              "                                     review_headline  \\\n",
              "0                                         Five Stars   \n",
              "1  Phffffffft, Phfffffft. Lots of air, and it's C...   \n",
              "2                      but I am sure I will like it.   \n",
              "3  and the shredder was dirty and the bin was par...   \n",
              "4                                         Four Stars   \n",
              "\n",
              "                                         review_body review_date  \n",
              "0                                     Great product.  2015-08-31  \n",
              "1  What's to say about this commodity item except...  2015-08-31  \n",
              "2    Haven't used yet, but I am sure I will like it.  2015-08-31  \n",
              "3  Although this was labeled as &#34;new&#34; the...  2015-08-31  \n",
              "4                    Gorgeous colors and easy to use  2015-08-31  "
            ],
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>marketplace</th>\n",
              "      <th>customer_id</th>\n",
              "      <th>review_id</th>\n",
              "      <th>product_id</th>\n",
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              "      <th>product_title</th>\n",
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              "      <th>total_votes</th>\n",
              "      <th>vine</th>\n",
              "      <th>verified_purchase</th>\n",
              "      <th>review_headline</th>\n",
              "      <th>review_body</th>\n",
              "      <th>review_date</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>US</td>\n",
              "      <td>43081963</td>\n",
              "      <td>R18RVCKGH1SSI9</td>\n",
              "      <td>B001BM2MAC</td>\n",
              "      <td>307809868</td>\n",
              "      <td>Scotch Cushion Wrap 7961, 12 Inches x 100 Feet</td>\n",
              "      <td>Office Products</td>\n",
              "      <td>5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>N</td>\n",
              "      <td>Y</td>\n",
              "      <td>Five Stars</td>\n",
              "      <td>Great product.</td>\n",
              "      <td>2015-08-31</td>\n",
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              "      <td>US</td>\n",
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              "      <td>R3L4L6LW1PUOFY</td>\n",
              "      <td>B00DZYEXPQ</td>\n",
              "      <td>75004341</td>\n",
              "      <td>Dust-Off Compressed Gas Duster, Pack of 4</td>\n",
              "      <td>Office Products</td>\n",
              "      <td>5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>N</td>\n",
              "      <td>Y</td>\n",
              "      <td>Phffffffft, Phfffffft. Lots of air, and it's C...</td>\n",
              "      <td>What's to say about this commodity item except...</td>\n",
              "      <td>2015-08-31</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>US</td>\n",
              "      <td>21143145</td>\n",
              "      <td>R2J8AWXWTDX2TF</td>\n",
              "      <td>B00RTMUHDW</td>\n",
              "      <td>529689027</td>\n",
              "      <td>Amram Tagger Standard Tag Attaching Tagging Gu...</td>\n",
              "      <td>Office Products</td>\n",
              "      <td>5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>N</td>\n",
              "      <td>Y</td>\n",
              "      <td>but I am sure I will like it.</td>\n",
              "      <td>Haven't used yet, but I am sure I will like it.</td>\n",
              "      <td>2015-08-31</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>US</td>\n",
              "      <td>52782374</td>\n",
              "      <td>R1PR37BR7G3M6A</td>\n",
              "      <td>B00D7H8XB6</td>\n",
              "      <td>868449945</td>\n",
              "      <td>AmazonBasics 12-Sheet High-Security Micro-Cut ...</td>\n",
              "      <td>Office Products</td>\n",
              "      <td>1</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>N</td>\n",
              "      <td>Y</td>\n",
              "      <td>and the shredder was dirty and the bin was par...</td>\n",
              "      <td>Although this was labeled as &amp;#34;new&amp;#34; the...</td>\n",
              "      <td>2015-08-31</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>US</td>\n",
              "      <td>24045652</td>\n",
              "      <td>R3BDDDZMZBZDPU</td>\n",
              "      <td>B001XCWP34</td>\n",
              "      <td>33521401</td>\n",
              "      <td>Derwent Colored Pencils, Inktense Ink Pencils,...</td>\n",
              "      <td>Office Products</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>N</td>\n",
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              "      <td>Four Stars</td>\n",
              "      <td>Gorgeous colors and easy to use</td>\n",
              "      <td>2015-08-31</td>\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-f42fb54b-165d-446e-a701-ed8b712ce49d button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-f42fb54b-165d-446e-a701-ed8b712ce49d');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-98d65f8d-29a9-4da7-85c8-bd1810791dde\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-98d65f8d-29a9-4da7-85c8-bd1810791dde')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-98d65f8d-29a9-4da7-85c8-bd1810791dde button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VkmBXXfmh_q2"
      },
      "source": [
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "## Keep Reviews and Ratings"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Only columns ['review_body', 'star_rating'] are kept into account going forward. Other columns are dropped.\n",
        "\n"
      ],
      "metadata": {
        "id": "6guFzz8NOM24"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "D6S-HTtYh_q3"
      },
      "outputs": [],
      "source": [
        "df = df[['review_body', 'star_rating']]"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.head(100)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "2fQ9bn_AEnnr",
        "outputId": "8d23e901-ffe2-4453-a123-e3c9f86f3c6b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                          review_body star_rating\n",
              "0                                      Great product.           5\n",
              "1   What's to say about this commodity item except...           5\n",
              "2     Haven't used yet, but I am sure I will like it.           5\n",
              "3   Although this was labeled as &#34;new&#34; the...           1\n",
              "4                     Gorgeous colors and easy to use           4\n",
              "..                                                ...         ...\n",
              "95  It is ok, but considering the price plus shipp...           3\n",
              "96  It has nothing to do with the performance of t...           1\n",
              "97            Exactly as promised. Totally satisfied.           5\n",
              "98  Excellent storage!  Once I found the instructi...           5\n",
              "99  Have had them for about one year now. They are...           5\n",
              "\n",
              "[100 rows x 2 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-9fa98ab3-8f02-49fc-8756-d5dd60eb1ed1\" class=\"colab-df-container\">\n",
              "    <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>review_body</th>\n",
              "      <th>star_rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Great product.</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>What's to say about this commodity item except...</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Haven't used yet, but I am sure I will like it.</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Although this was labeled as &amp;#34;new&amp;#34; the...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Gorgeous colors and easy to use</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>95</th>\n",
              "      <td>It is ok, but considering the price plus shipp...</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>96</th>\n",
              "      <td>It has nothing to do with the performance of t...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>97</th>\n",
              "      <td>Exactly as promised. Totally satisfied.</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>98</th>\n",
              "      <td>Excellent storage!  Once I found the instructi...</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99</th>\n",
              "      <td>Have had them for about one year now. They are...</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>100 rows × 2 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-9fa98ab3-8f02-49fc-8756-d5dd60eb1ed1')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-9fa98ab3-8f02-49fc-8756-d5dd60eb1ed1 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-9fa98ab3-8f02-49fc-8756-d5dd60eb1ed1');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-b2e10405-fe35-4f03-8e81-40fe7562185a\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-b2e10405-fe35-4f03-8e81-40fe7562185a')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-b2e10405-fe35-4f03-8e81-40fe7562185a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "j7ZGxbTLh_q4"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0Kz9XXRhh_q5"
      },
      "source": [
        "# Data Cleaning\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Empty rows are dropped using dropna()"
      ],
      "metadata": {
        "id": "bZUvVKc4OpCm"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uax1hkoYh_q6",
        "outputId": "31c845ed-99f7-4c79-d1e9-881fb1ddb9fd"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2640254\n",
            "dropping those that are empty\n",
            "2640157\n"
          ]
        }
      ],
      "source": [
        "print((len(df)))\n",
        "df.dropna(subset=['review_body', 'star_rating'], inplace=True)\n",
        "print('dropping those that are empty')\n",
        "print((len(df)))"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "'sentiment' will be the target variable and this is got using 'star_rating'.\n",
        "\n",
        "'review_body' would be the feature to consider while modelling\n"
      ],
      "metadata": {
        "id": "i4qqag-_Os_V"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df['sentiment'] = df['star_rating'].apply(lambda rating: 1 if int(rating) >= 4 else 0)\n"
      ],
      "metadata": {
        "id": "kftpyPYUFpHY"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.head(20)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 676
        },
        "id": "EuFKKVPCKeEw",
        "outputId": "5785051e-9772-41ea-e218-45734d1ff2a9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                          review_body star_rating  sentiment\n",
              "0                                      Great product.           5          1\n",
              "1   What's to say about this commodity item except...           5          1\n",
              "2     Haven't used yet, but I am sure I will like it.           5          1\n",
              "3   Although this was labeled as &#34;new&#34; the...           1          0\n",
              "4                     Gorgeous colors and easy to use           4          1\n",
              "5   Perfect for planning weekly meals. Removrd the...           5          1\n",
              "6   Gold plated fusers are the best! It will never...           5          1\n",
              "7   I have used these highlighters for my bible fo...           5          1\n",
              "8   Heavy pen that writes very well.  I've had it ...           5          1\n",
              "9   Not sure if they work but sent quickly and fit...           5          1\n",
              "10  Great product for the price. Easy to put toget...           4          1\n",
              "11  Love these highlighters. They took a while to ...           5          1\n",
              "12  Received on time, no issues. I've ordered mult...           5          1\n",
              "13                     worked about a month then died           1          0\n",
              "14  I purchased this 8/27/15 for 59.99 from Amazon...           5          1\n",
              "15                             Everything works fine.           5          1\n",
              "16                                         Thank you!           5          1\n",
              "17                                    Love these pens           5          1\n",
              "18          The product is everything that was stated           5          1\n",
              "19                                          Great buy           5          1"
            ],
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              "      <th>9</th>\n",
              "      <td>Not sure if they work but sent quickly and fit...</td>\n",
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              "      <th>10</th>\n",
              "      <td>Great product for the price. Easy to put toget...</td>\n",
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              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Love these highlighters. They took a while to ...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Received on time, no issues. I've ordered mult...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>worked about a month then died</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>I purchased this 8/27/15 for 59.99 from Amazon...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Everything works fine.</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Thank you!</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Love these pens</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>The product is everything that was stated</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Great buy</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
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              "  </tbody>\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-fa3af99b-818a-414f-b3b7-80891e9bb0d2 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-fa3af99b-818a-414f-b3b7-80891e9bb0d2');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "        element.appendChild(docLink);\n",
              "      }\n",
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              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-ba779cae-8c50-44e9-abaf-3b5942152a1e\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-ba779cae-8c50-44e9-abaf-3b5942152a1e')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
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              "      --disabled-fill-color: #666;\n",
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              "\n",
              "  .colab-df-quickchart {\n",
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              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
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              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
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              "      border-right-color: var(--fill-color);\n",
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              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-ba779cae-8c50-44e9-abaf-3b5942152a1e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Cleaning of data is performed in the following steps:\n",
        "\n",
        "\n",
        "*   Convert text to lower text\n",
        "*   Remove contractions in the reviews byexpanding them\n",
        "*   Remove any trailing or leading spaces\n",
        "*   Remove HTML tags using regex expression query\n",
        "*   Remove video tags using a regex expression query\n",
        "*   Removing Emojis and patterns using an emoji pattern, took help from a stackoverflow post : https://stackoverflow.com/a/38498442\n",
        "*   Removing non alphabetical values from the reviews using a regex expression\n",
        "*   Removing punctuatons and special characters\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "QqsPfleoPRbo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def cleanReviews(text): # function to clean the reviews\n",
        "    # print(text)\n",
        "    if pd.isna(text):\n",
        "        return \"\"\n",
        "\n",
        "    text = text.lower()\n",
        "    text = contractions.fix(text)\n",
        "    text = text.strip() #to remoe any trailing and leading spaces in the review\n",
        "    text = re.sub(r'<.*?>', '', text) # Remove HTML tags (if present)\n",
        "    text = re.sub(r'<video>.*?</video>', '', text)\n",
        "    text = re.sub(r'[:;][-]?[)D(|\\\\/\\]3]+', '', text)\n",
        "    emoji_pattern = re.compile(\n",
        "        r\"[\\U0001F600-\\U0001F64F]|[\\U0001F300-\\U0001F5FF]\",\n",
        "        flags=re.UNICODE,\n",
        "    )\n",
        "\n",
        "    text = re.sub(r'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\\\\(\\\\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+', '', text)\n",
        "    ### https://stackoverflow.com/a/38498442\n",
        "    text = re.sub(r'[^a-zA-Z\\s]', '', text) # Remove special characters, punctuation, and symbols\n",
        "    text = emoji_pattern.sub(r\"\", text)\n",
        "\n",
        "    text = text.translate(str.maketrans('', '', string.punctuation)) #to remove punctuation\n",
        "\n",
        "    return text"
      ],
      "metadata": {
        "id": "qMtzdQovMnj3",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "06d1c3c9-8ff9-45d0-c84c-bc96e7e16768"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting contractions\n",
            "  Downloading contractions-0.1.73-py2.py3-none-any.whl (8.7 kB)\n",
            "Collecting textsearch>=0.0.21 (from contractions)\n",
            "  Downloading textsearch-0.0.24-py2.py3-none-any.whl (7.6 kB)\n",
            "Collecting anyascii (from textsearch>=0.0.21->contractions)\n",
            "  Downloading anyascii-0.3.2-py3-none-any.whl (289 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m289.9/289.9 kB\u001b[0m \u001b[31m6.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting pyahocorasick (from textsearch>=0.0.21->contractions)\n",
            "  Downloading pyahocorasick-2.0.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (110 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m110.8/110.8 kB\u001b[0m \u001b[31m11.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: pyahocorasick, anyascii, textsearch, contractions\n",
            "Successfully installed anyascii-0.3.2 contractions-0.1.73 pyahocorasick-2.0.0 textsearch-0.0.24\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(df['review_body'].apply(len).mean())\n",
        "beforeCleaning = df['review_body'].apply(len).mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "a4bF9i6tkRGy",
        "outputId": "be41812a-b2d7-4c42-f4ac-49e7740a45c9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "285.2624162123692\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "df['review_body'] = df['review_body'].apply(cleanReviews) # applying clenaning to all the reviews where html tags and special char and punctuations are removed\n",
        "\n",
        "df.head(20)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 676
        },
        "id": "u9LVCaYDNItv",
        "outputId": "c88f9b40-cbf3-44bb-cb4c-b84471fd70db"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                          review_body star_rating  sentiment\n",
              "0                                       great product           5          1\n",
              "1   what is to say about this commodity item excep...           5          1\n",
              "2      have not used yet but i am sure i will like it           5          1\n",
              "3   although this was labeled as new the one i rec...           1          0\n",
              "4                     gorgeous colors and easy to use           4          1\n",
              "5   perfect for planning weekly meals removrd the ...           5          1\n",
              "6   gold plated fusers are the best it will never ...           5          1\n",
              "7   i have used these highlighters for my bible fo...           5          1\n",
              "8   heavy pen that writes very well  i have had it...           5          1\n",
              "9   not sure if they work but sent quickly and fit...           5          1\n",
              "10  great product for the price easy to put togeth...           4          1\n",
              "11  love these highlighters they took a while to a...           5          1\n",
              "12  received on time no issues i have ordered mult...           5          1\n",
              "13                     worked about a month then died           1          0\n",
              "14  i purchased this  for  from amazon i am amazed...           5          1\n",
              "15                              everything works fine           5          1\n",
              "16                                          thank you           5          1\n",
              "17                                    love these pens           5          1\n",
              "18          the product is everything that was stated           5          1\n",
              "19                                          great buy           5          1"
            ],
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>review_body</th>\n",
              "      <th>star_rating</th>\n",
              "      <th>sentiment</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
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              "      <th>0</th>\n",
              "      <td>great product</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>what is to say about this commodity item excep...</td>\n",
              "      <td>5</td>\n",
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              "      <th>2</th>\n",
              "      <td>have not used yet but i am sure i will like it</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
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              "      <th>3</th>\n",
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              "      <td>4</td>\n",
              "      <td>1</td>\n",
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              "      <td>1</td>\n",
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              "      <td>5</td>\n",
              "      <td>1</td>\n",
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              "      <th>7</th>\n",
              "      <td>i have used these highlighters for my bible fo...</td>\n",
              "      <td>5</td>\n",
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              "      <th>8</th>\n",
              "      <td>heavy pen that writes very well  i have had it...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>not sure if they work but sent quickly and fit...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>great product for the price easy to put togeth...</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>love these highlighters they took a while to a...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>received on time no issues i have ordered mult...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>worked about a month then died</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>i purchased this  for  from amazon i am amazed...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>everything works fine</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>thank you</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>love these pens</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>the product is everything that was stated</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>great buy</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-27fd345f-1a98-4a10-90ce-830bd0530ef9')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
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              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-27fd345f-1a98-4a10-90ce-830bd0530ef9 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-27fd345f-1a98-4a10-90ce-830bd0530ef9');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-a6d8d93b-04bf-4765-94e5-3e330f33b5c3\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-a6d8d93b-04bf-4765-94e5-3e330f33b5c3')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    <g>\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
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              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-a6d8d93b-04bf-4765-94e5-3e330f33b5c3 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "removing any empty rows after cleaning"
      ],
      "metadata": {
        "id": "2YeHy_CbRH7J"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = df[df['review_body'] != '']\n",
        "print(len(df))\n",
        "print(df.head())\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "05QTD8uUhjF3",
        "outputId": "b6fd45dd-5924-408c-fed7-1bf13075632b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2639092\n",
            "                                         review_body star_rating  sentiment\n",
            "0                                      great product           5          1\n",
            "1  what is to say about this commodity item excep...           5          1\n",
            "2     have not used yet but i am sure i will like it           5          1\n",
            "3  although this was labeled as new the one i rec...           1          0\n",
            "4                    gorgeous colors and easy to use           4          1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(df['review_body'].apply(len).mean())\n",
        "afterCleaning = df['review_body'].apply(len).mean()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vMl8xal4ZvIk",
        "outputId": "475aa8a9-f5f5-43db-cea3-00e5bb5d9026"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "273.5473325674133\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "average length of data before and after performing cleaning"
      ],
      "metadata": {
        "id": "XhnmuZcwRKnD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(str(beforeCleaning)+\" , \" +str(afterCleaning))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "h6hZEGOvwm0M",
        "outputId": "20697b7d-c2c2-43a2-b64e-4506626a845c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "285.2624162123692 , 273.5473325674133\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "BUOQtNZnY69K",
        "outputId": "ec587ded-1a8c-48c1-db0f-f4207f7d9e63"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                               review_body star_rating  \\\n",
              "0                                            great product           5   \n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
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              "    </div>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CYuPVeCRh_q6"
      },
      "source": [
        "# Pre-processing"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Data preprocessing is carried out on the dataset by prforming stop words and lemmatization\n"
      ],
      "metadata": {
        "id": "HKc0twafRnOz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(df['review_body'].apply(len).mean())\n",
        "beforePreProcessing = df['review_body'].apply(len).mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-_tRL-U_XP3e",
        "outputId": "c251f115-9bb7-420a-b88a-2342d376b4db"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "273.5473325674133\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WTP5xCoTh_q7"
      },
      "source": [
        "## remove the stop words"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "szQtU7Quh_q7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7fc27b68-0004-4fcc-9e3b-130aab2fd2fa"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n"
          ]
        }
      ],
      "source": [
        "nltk.download('stopwords')\n",
        "stop_words = set(stopwords.words('english'))\n",
        "\n",
        "df['review_without_stopwords'] = df['review_body'].apply(lambda x: ' '.join([word for word in x.split() if word not in (stop_words)]))\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xyfgWdwih_q7"
      },
      "source": [
        "## perform lemmatization  "
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Lemmatization is the process of reducing a word to its base or dictionary form, known as the lemma."
      ],
      "metadata": {
        "id": "ytMLJSiPSQ1Z"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "lemmatizer = WordNetLemmatizer()\n",
        "def lemmatize_text(text):\n",
        "    words = nltk.word_tokenize(text)\n",
        "    lemmatized_words = [lemmatizer.lemmatize(word) for word in words]\n",
        "    lemmatized_text = \" \".join(lemmatized_words)\n",
        "    return lemmatized_text"
      ],
      "metadata": {
        "id": "UygqMxBM0qgw"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['lemmatized_review'] = df['review_without_stopwords'].apply(lemmatize_text)\n"
      ],
      "metadata": {
        "id": "o_b0_YY_0wi6"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "2czhJkIK1O_7",
        "outputId": "ff7b0158-70c6-4a9c-d33f-35a119dc4529"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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            "text/plain": [
              "                                               review_body star_rating  \\\n",
              "0                                            great product           5   \n",
              "1        what is to say about this commodity item excep...           5   \n",
              "2           have not used yet but i am sure i will like it           5   \n",
              "3        although this was labeled as new the one i rec...           1   \n",
              "4                          gorgeous colors and easy to use           4   \n",
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              "2640249  i cannot live anymore whithout my palm iii but...           4   \n",
              "2640250  although the palm pilot is thin and compact it...           4   \n",
              "2640251  this book had a lot of great content without b...           4   \n",
              "2640252  i am teaching a course in excel and am using t...           5   \n",
              "2640253  a very comprehensive layout of exactly how vis...           5   \n",
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              "         sentiment                           review_without_stopwords  \\\n",
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              "      <td>although this was labeled as new the one i rec...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>although labeled new one received clearly used...</td>\n",
              "      <td>although labeled new one received clearly used...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>gorgeous colors and easy to use</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>gorgeous colors easy use</td>\n",
              "      <td>gorgeous color easy use</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2640249</th>\n",
              "      <td>i cannot live anymore whithout my palm iii but...</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>cannot live anymore whithout palm iii also hat...</td>\n",
              "      <td>can not live anymore whithout palm iii also ha...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2640250</th>\n",
              "      <td>although the palm pilot is thin and compact it...</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>although palm pilot thin compact may exceed po...</td>\n",
              "      <td>although palm pilot thin compact may exceed po...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2640251</th>\n",
              "      <td>this book had a lot of great content without b...</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>book lot great content without boring monotono...</td>\n",
              "      <td>book lot great content without boring monotono...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2640252</th>\n",
              "      <td>i am teaching a course in excel and am using t...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>teaching course excel using stepbystep books g...</td>\n",
              "      <td>teaching course excel using stepbystep book go...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2640253</th>\n",
              "      <td>a very comprehensive layout of exactly how vis...</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>comprehensive layout exactly visual basic give...</td>\n",
              "      <td>comprehensive layout exactly visual basic give...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2639092 rows × 5 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-dcfbb789-214f-4b80-b84b-d3514ca9fdf0')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-dcfbb789-214f-4b80-b84b-d3514ca9fdf0 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-dcfbb789-214f-4b80-b84b-d3514ca9fdf0');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-53692423-cf08-419f-be63-cb1c148f0b6a\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-53692423-cf08-419f-be63-cb1c148f0b6a')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-53692423-cf08-419f-be63-cb1c148f0b6a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "XqTSasa-h_q8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "25dd9fb4-f2ab-4d7d-81d8-f64c877b0deb"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "169.45235406723222\n"
          ]
        }
      ],
      "source": [
        "print(df['lemmatized_review'].apply(len).mean())\n",
        "afterPreProcessing = df['lemmatized_review'].apply(len).mean()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Tlz54nmFh_q4"
      },
      "source": [
        " ## We form two classes and select 50000 reviews randomly from each class.\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "To make it easier to hande computationally, we use a subset of the dataset from the bogger dataset, by taking 50000 reviews for each of the two classes of sentiment."
      ],
      "metadata": {
        "id": "KhL8evyqSYI7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(str(beforePreProcessing)+\" , \"+str(afterPreProcessing))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7k8mzfF72w4G",
        "outputId": "e41cf4b6-820d-48a8-92c5-97f60220c09d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "273.5473325674133 , 169.45235406723222\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sentiment_counts = df['sentiment'].value_counts()\n",
        "\n",
        "# Print the counts\n",
        "print(\"Number of positive (sentiment=1) rows:\", sentiment_counts.get(1, 0))\n",
        "print(\"Number of negative (sentiment=0) rows:\", sentiment_counts.get(0, 0))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yXiaaserjyY9",
        "outputId": "9c6d2661-c4b3-4509-c605-12027732529a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of positive (sentiment=1) rows: 2000130\n",
            "Number of negative (sentiment=0) rows: 638962\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "positive_count = (df['sentiment'] == 1).sum()\n",
        "negative_count = (df['sentiment'] == 0).sum()\n",
        "num_samples = min(50000, positive_count, negative_count)\n",
        "\n",
        "# Sample the rows for each sentiment value\n",
        "positive_samples = df[df['sentiment'] == 1].sample(n=num_samples, random_state=11)\n",
        "negative_samples = df[df['sentiment'] == 0].sample(n=num_samples, random_state=11)\n",
        "\n",
        "\n",
        "# Combine the sampled rows into a single DataFrame\n",
        "sampled_df = pd.concat([positive_samples, negative_samples])\n",
        "\n",
        "# Reset the index of the combined DataFrame\n",
        "sampled_df.reset_index(drop=True, inplace=True)\n",
        "\n",
        "print(len(positive_samples))\n",
        "print(len(negative_samples))\n",
        "print(positive_samples)\n",
        "print(negative_samples)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FMm3h6A4kF51",
        "outputId": "892ce56a-608c-4404-b5ab-b35dbb4256a7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "50000\n",
            "50000\n",
            "                                               review_body star_rating  \\\n",
            "644175   very cool this was for my daughter who had her...           5   \n",
            "2138702  it is so hard to find a good qualified binder ...           5   \n",
            "1753775  i love my rhinestone badge holder i get so man...           4   \n",
            "500377                                             love it           5   \n",
            "165337   i use these folders to keep student files i lo...           5   \n",
            "...                                                    ...         ...   \n",
            "2014213  i reccommend canon products and their supplies...           4   \n",
            "2187227  small waterproof and handy to use can be used ...         5.0   \n",
            "1653687  my favorite mechanical pencil i have been usin...           5   \n",
            "1597700  wonderful pens they write incredibly smoothly ...           5   \n",
            "922069   i love this very feminine pen in pink and cros...           5   \n",
            "\n",
            "         sentiment                           review_without_stopwords  \\\n",
            "644175           1  cool daughter share needle staying hospital re...   \n",
            "2138702          1  hard find good qualified binder cabinet need o...   \n",
            "1753775          1  love rhinestone badge holder get many compleme...   \n",
            "500377           1                                               love   \n",
            "165337           1  use folders keep student files love folders us...   \n",
            "...            ...                                                ...   \n",
            "2014213          1  reccommend canon products supplies good qualit...   \n",
            "2187227          1  small waterproof handy use used pencil weather...   \n",
            "1653687          1  favorite mechanical pencil using years found a...   \n",
            "1597700          1  wonderful pens write incredibly smoothly love ...   \n",
            "922069           1  love feminine pen pink cross pens always favorite   \n",
            "\n",
            "                                         lemmatized_review  \n",
            "644175   cool daughter share needle staying hospital re...  \n",
            "2138702  hard find good qualified binder cabinet need o...  \n",
            "1753775  love rhinestone badge holder get many compleme...  \n",
            "500377                                                love  \n",
            "165337   use folder keep student file love folder used ...  \n",
            "...                                                    ...  \n",
            "2014213  reccommend canon product supply good quality e...  \n",
            "2187227  small waterproof handy use used pencil weather...  \n",
            "1653687  favorite mechanical pencil using year found an...  \n",
            "1597700  wonderful pen write incredibly smoothly love w...  \n",
            "922069    love feminine pen pink cross pen always favorite  \n",
            "\n",
            "[50000 rows x 5 columns]\n",
            "                                               review_body star_rating  \\\n",
            "2358021  the software for this printer is worthless on ...         1.0   \n",
            "2600825  after purchasing  different pdas before i foun...           2   \n",
            "1005878  advertised as weatherproof but labels i got ar...           1   \n",
            "2530575  when i first received this printer it was grea...         1.0   \n",
            "276404   i hardly ever write bad reviews but this produ...           1   \n",
            "...                                                    ...         ...   \n",
            "2044313  two of these plush toys fell apart on christma...           1   \n",
            "1686142  it fits some of my equipment i would have like...           3   \n",
            "175235   would be perfect if the bottom ring actually m...           2   \n",
            "547551                                                  ok           3   \n",
            "739589   doubt these will hold up more than a few pages...           3   \n",
            "\n",
            "         sentiment                           review_without_stopwords  \\\n",
            "2358021          0  software printer worthless mac makes printer u...   \n",
            "2600825          0  purchasing different pdas found one liked deci...   \n",
            "1005878          0  advertised weatherproof labels got slightest a...   \n",
            "2530575          0  first received printer great pictures look gre...   \n",
            "276404           0  hardly ever write bad reviews product garbage ...   \n",
            "...            ...                                                ...   \n",
            "2044313          0  two plush toys fell apart christmas morning th...   \n",
            "1686142          0  fits equipment would liked bigger large textbo...   \n",
            "175235           0  would perfect bottom ring actually met properl...   \n",
            "547551           0                                                 ok   \n",
            "739589           0  doubt hold pages used hold queensized black sh...   \n",
            "\n",
            "                                         lemmatized_review  \n",
            "2358021  software printer worthless mac make printer un...  \n",
            "2600825  purchasing different pda found one liked decid...  \n",
            "1005878  advertised weatherproof label got slightest am...  \n",
            "2530575  first received printer great picture look grea...  \n",
            "276404   hardly ever write bad review product garbage c...  \n",
            "...                                                    ...  \n",
            "2044313  two plush toy fell apart christmas morning thi...  \n",
            "1686142  fit equipment would liked bigger large textboo...  \n",
            "175235   would perfect bottom ring actually met properl...  \n",
            "547551                                                  ok  \n",
            "739589   doubt hold page used hold queensized black she...  \n",
            "\n",
            "[50000 rows x 5 columns]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sampled_df\n",
        "sdf = sampled_df\n",
        "df=sdf\n",
        "sdf.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "cM1uplx78Act",
        "outputId": "88bcd412-bb5e-4d37-b8a2-24ab6873d4ca"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                         review_body star_rating  sentiment  \\\n",
              "0  very cool this was for my daughter who had her...           5          1   \n",
              "1  it is so hard to find a good qualified binder ...           5          1   \n",
              "2  i love my rhinestone badge holder i get so man...           4          1   \n",
              "3                                            love it           5          1   \n",
              "4  i use these folders to keep student files i lo...           5          1   \n",
              "\n",
              "                            review_without_stopwords  \\\n",
              "0  cool daughter share needle staying hospital re...   \n",
              "1  hard find good qualified binder cabinet need o...   \n",
              "2  love rhinestone badge holder get many compleme...   \n",
              "3                                               love   \n",
              "4  use folders keep student files love folders us...   \n",
              "\n",
              "                                   lemmatized_review  \n",
              "0  cool daughter share needle staying hospital re...  \n",
              "1  hard find good qualified binder cabinet need o...  \n",
              "2  love rhinestone badge holder get many compleme...  \n",
              "3                                               love  \n",
              "4  use folder keep student file love folder used ...  "
            ],
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            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e3TqwkRRh_q8"
      },
      "source": [
        "# TF-IDF and BoW Feature Extraction"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(df)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qzNwLyolBA0W",
        "outputId": "853bb8c0-9fb8-479a-eb57-01471ddd9ecd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "100000"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "dPA3kPsABEdX",
        "outputId": "3b3985e3-5770-420d-9c9a-9dad4f2ead6c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                         review_body star_rating  sentiment  \\\n",
              "0  very cool this was for my daughter who had her...           5          1   \n",
              "1  it is so hard to find a good qualified binder ...           5          1   \n",
              "2  i love my rhinestone badge holder i get so man...           4          1   \n",
              "3                                            love it           5          1   \n",
              "4  i use these folders to keep student files i lo...           5          1   \n",
              "\n",
              "                            review_without_stopwords  \\\n",
              "0  cool daughter share needle staying hospital re...   \n",
              "1  hard find good qualified binder cabinet need o...   \n",
              "2  love rhinestone badge holder get many compleme...   \n",
              "3                                               love   \n",
              "4  use folders keep student files love folders us...   \n",
              "\n",
              "                                   lemmatized_review  \n",
              "0  cool daughter share needle staying hospital re...  \n",
              "1  hard find good qualified binder cabinet need o...  \n",
              "2  love rhinestone badge holder get many compleme...  \n",
              "3                                               love  \n",
              "4  use folder keep student file love folder used ...  "
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              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
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              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
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              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-07a4ad6c-6498-4bbd-adc3-16436911f171 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "df['original_review_body'] = df['review_body']\n",
        "df['review_body'] = df['lemmatized_review']"
      ],
      "metadata": {
        "id": "A-bFuy6bBwcA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 275
        },
        "id": "yyVRfH0uB2wC",
        "outputId": "1eea200e-3562-4d69-dff9-a6829a71a71f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                         review_body star_rating  sentiment  \\\n",
              "0  cool daughter share needle staying hospital re...           5          1   \n",
              "1  hard find good qualified binder cabinet need o...           5          1   \n",
              "2  love rhinestone badge holder get many compleme...           4          1   \n",
              "3                                               love           5          1   \n",
              "4  use folder keep student file love folder used ...           5          1   \n",
              "\n",
              "                            review_without_stopwords  \\\n",
              "0  cool daughter share needle staying hospital re...   \n",
              "1  hard find good qualified binder cabinet need o...   \n",
              "2  love rhinestone badge holder get many compleme...   \n",
              "3                                               love   \n",
              "4  use folders keep student files love folders us...   \n",
              "\n",
              "                                   lemmatized_review  \\\n",
              "0  cool daughter share needle staying hospital re...   \n",
              "1  hard find good qualified binder cabinet need o...   \n",
              "2  love rhinestone badge holder get many compleme...   \n",
              "3                                               love   \n",
              "4  use folder keep student file love folder used ...   \n",
              "\n",
              "                                original_review_body  \n",
              "0  very cool this was for my daughter who had her...  \n",
              "1  it is so hard to find a good qualified binder ...  \n",
              "2  i love my rhinestone badge holder i get so man...  \n",
              "3                                            love it  \n",
              "4  i use these folders to keep student files i lo...  "
            ],
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              "      <td>love</td>\n",
              "      <td>love</td>\n",
              "      <td>love it</td>\n",
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              "    <div class=\"colab-df-buttons\">\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-06ad96b4-2584-43d1-a61d-8de48f336be3 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-06ad96b4-2584-43d1-a61d-8de48f336be3');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
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              "      --disabled-fill-color: #AAA;\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
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              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-62e4e4cd-2ead-4d69-be22-5fa526d5c126 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "test_train_split is being used to split the dataset into train (80%) and test(20%) data\n"
      ],
      "metadata": {
        "id": "GddER2B-S_BG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "X_text = df['review_body']  # Textual feature\n",
        "y = df['sentiment']  # Assuming 'sentiment' is your target label (0 for negative, 1 for positive)\n",
        "X_text_train, X_text_test, y_train, y_test = train_test_split(\n",
        "    X_text, y, test_size=0.2, random_state=42\n",
        ")"
      ],
      "metadata": {
        "id": "VEBHzr_mNJ04"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "sklearn methods of CountVectorizer() and TfidfVectorizer() are used to generate TF-IDF(term frequency- inverse document frequency) and BoW(Bag of Words) Representations of the Data.\n",
        "\n",
        "To prevent data leakage, fit_transform on train feature dataset alone transform method on the test feature dataset.\n",
        "fit_transform is used intially during vecorization to convert text to numerical features and learn the vocabulary.\n",
        "\n",
        "transorm is run on new data, and the transformation learnt previously would be used to learn parameters during this fitting phase."
      ],
      "metadata": {
        "id": "1YSai2SVTsq-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# creating feature extraction of bag of words\n",
        "count_vectorizer = CountVectorizer()\n",
        "X_train_bow = count_vectorizer.fit_transform(X_text_train)\n",
        "X_test_bow = count_vectorizer.transform(X_text_test)\n"
      ],
      "metadata": {
        "id": "CLnsWjShNUMC"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# creating feature extraction of tfidf\n",
        "tfidf_vectorizer = TfidfVectorizer()\n",
        "X_train_tfidf = tfidf_vectorizer.fit_transform(X_text_train)\n",
        "X_test_tfidf = tfidf_vectorizer.transform(X_text_test)\n"
      ],
      "metadata": {
        "id": "0FEpyNJ0Nk-A"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Model training"
      ],
      "metadata": {
        "id": "veqMcswKNyxO"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xMIToMZlh_q8"
      },
      "source": [
        "# Perceptron Using Both Features"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Perceptron model is initiated and grid search is carried out to find best regularization and maximum iterations needed for optimal running of the training.\n",
        "\n",
        "training is done on both the features extracted\n",
        "\n",
        "inference is got using the .predict() function and precision, recall and f1 score are calculated using sklearn.metrics"
      ],
      "metadata": {
        "id": "yF5xgD3pUzPS"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "b0zYGevrh_q9",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "30c65aee-f7f0-4000-d4d1-13f90b54bb44"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Perceptron BOW\n",
            "F1-score: 0.79\n",
            "Precision: 0.81\n",
            "Recall: 0.78\n"
          ]
        }
      ],
      "source": [
        "perceptron = Perceptron()\n",
        "param_grid = {\n",
        "    'alpha': [0.1, 0.01, 0.001],  # Regularization strength\n",
        "    'max_iter': [100, 500, 1000],  # Maximum no of iterations\n",
        "}\n",
        "\n",
        "grid_search = GridSearchCV(perceptron, param_grid, cv=5, scoring='f1')\n",
        "\n",
        "grid_search.fit(X_train_bow, y_train)# Performing hyperparameter tuning on the training data\n",
        "\n",
        "best_alpha = grid_search.best_params_['alpha'] # Get the best hyperparameters\n",
        "best_max_iter = grid_search.best_params_['max_iter']\n",
        "\n",
        "perceptron_classifier_best = Perceptron(alpha=best_alpha, max_iter=best_max_iter)\n",
        "\n",
        "perceptron_classifier_best.fit(X_train_bow, y_train)\n",
        "\n",
        "y_pred = perceptron_classifier_best.predict(X_test_bow)\n",
        "f1 = f1_score(y_test, y_pred)\n",
        "precision = precision_score(y_test, y_pred)\n",
        "recall = recall_score(y_test, y_pred)\n",
        "\n",
        "print(\"Perceptron BOW\")\n",
        "print(f\"F1-score: {f1:.2f}\")\n",
        "print(f\"Precision: {precision:.2f}\")\n",
        "print(f\"Recall: {recall:.2f}\")\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "perceptron.fit(X_train_tfidf, y_train)\n",
        "y_pred_perceptron = perceptron.predict(X_test_tfidf)\n",
        "\n",
        "\n",
        "y_pred = perceptron.predict(X_test_tfidf)\n",
        "\n",
        "# Calculate accuracy\n",
        "accuracy = accuracy_score(y_test, y_pred)\n",
        "# Calculate F1-score, precision, and recall\n",
        "f1 = f1_score(y_test, y_pred)\n",
        "precision = precision_score(y_test, y_pred)\n",
        "recall = recall_score(y_test, y_pred)\n",
        "\n",
        "print(\"Perceptron TFIDF\")\n",
        "print(f\"F1-score: {f1:.2f}\")\n",
        "print(f\"Precision: {precision:.2f}\")\n",
        "print(f\"Recall: {recall:.2f}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lhC1bvUNmQgn",
        "outputId": "0bff8fbc-0128-4485-aa51-ecc3d53f8c28"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Perceptron TFIDF\n",
            "F1-score: 0.80\n",
            "Precision: 0.79\n",
            "Recall: 0.81\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sNPvII98h_q9"
      },
      "source": [
        "# SVM Using Both Features"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "LinearSVC was instantiated and model was trained on the features extracted from both TFIDF and BoW"
      ],
      "metadata": {
        "id": "9yi-rduuVmir"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "linear_svc_classifier = LinearSVC()\n",
        "\n",
        "linear_svc_classifier.fit(X_train_bow, y_train)\n",
        "\n",
        "# Make predictions on the test data\n",
        "y_pred = linear_svc_classifier.predict(X_test_bow)\n",
        "\n",
        "# Evaluate the classifier\n",
        "accuracy = accuracy_score(y_test, y_pred)\n",
        "# Calculate F1-score, precision, and recall\n",
        "f1 = f1_score(y_test, y_pred)\n",
        "precision = precision_score(y_test, y_pred)\n",
        "recall = recall_score(y_test, y_pred)\n",
        "print(\"SVM BoW\")\n",
        "print(f\"Accuracy: {accuracy:.2f}\")\n",
        "print(f\"F1-score: {f1:.2f}\")\n",
        "print(f\"Precision: {precision:.2f}\")\n",
        "print(f\"Recall: {recall:.2f}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "thPzBt38qcoR",
        "outputId": "7017a61d-9806-4648-ebef-c7175be98421"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "SVM BoW\n",
            "Accuracy: 0.83\n",
            "F1-score: 0.83\n",
            "Precision: 0.82\n",
            "Recall: 0.85\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
            "  warnings.warn(\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "\n",
        "linear_svc_classifier.fit(X_train_tfidf, y_train)\n",
        "\n",
        "y_pred = linear_svc_classifier.predict(X_test_tfidf)\n",
        "\n",
        "f1 = f1_score(y_test, y_pred)\n",
        "precision = precision_score(y_test, y_pred)\n",
        "recall = recall_score(y_test, y_pred)\n",
        "print(\"SVM TFIDF\")\n",
        "print(f\"F1-score: {f1:.2f}\")\n",
        "print(f\"Precision: {precision:.2f}\")\n",
        "print(f\"Recall: {recall:.2f}\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wMFHiuVthvpv",
        "outputId": "363d8402-f4cb-45fc-b48f-8561568d9f17"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "SVM TFIDF\n",
            "F1-score: 0.84\n",
            "Precision: 0.84\n",
            "Recall: 0.84\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UdacItHqh_q-"
      },
      "source": [
        "# Logistic Regression Using Both Features"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Logistic regression was instantiated and l2 score, max iterations were played around with to find the optimal hyperparameters to use"
      ],
      "metadata": {
        "id": "oQtcpC72VxEG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "logistic_regression = LogisticRegression(penalty='l2', max_iter=1000)\n",
        "logistic_regression.fit(X_train_bow, y_train)\n",
        "\n",
        "y_pred = logistic_regression.predict(X_test_bow)\n",
        "\n",
        "f1 = f1_score(y_test, y_pred)\n",
        "precision = precision_score(y_test, y_pred)\n",
        "recall = recall_score(y_test, y_pred)\n",
        "\n",
        "print(\"Logistic regression BOW\")\n",
        "print(f\"Accuracy: {accuracy:.2f}\")\n",
        "print(f\"F1-score: {f1:.2f}\")\n",
        "print(f\"Precision: {precision:.2f}\")\n",
        "print(f\"Recall: {recall:.2f}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zVA9sHggA02r",
        "outputId": "ce1c4aa9-2c1f-4e0b-80ac-71784bf2b251"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Logistic regression BOW\n",
            "Accuracy: 0.83\n",
            "F1-score: 0.84\n",
            "Precision: 0.83\n",
            "Recall: 0.86\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "logistic_regression = LogisticRegression(penalty='l2', max_iter=1000)\n",
        "logistic_regression.fit(X_train_tfidf, y_train)\n",
        "\n",
        "y_pred = logistic_regression.predict(X_test_tfidf)\n",
        "\n",
        "f1 = f1_score(y_test, y_pred)\n",
        "precision = precision_score(y_test, y_pred)\n",
        "recall = recall_score(y_test, y_pred)\n",
        "\n",
        "print(\"Logistic regression TFIDF\")\n",
        "print(f\"Accuracy: {accuracy:.2f}\")\n",
        "print(f\"F1-score: {f1:.2f}\")\n",
        "print(f\"Precision: {precision:.2f}\")\n",
        "print(f\"Recall: {recall:.2f}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qQIKnaqEAyMT",
        "outputId": "f79e4e9e-9252-46bf-ac56-06314d167b8e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Logistic regression TFIDF\n",
            "Accuracy: 0.83\n",
            "F1-score: 0.85\n",
            "Precision: 0.85\n",
            "Recall: 0.85\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2L7CNwUMh_q-"
      },
      "source": [
        "# Naive Bayes Using Both Features"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Multinomial Naive Bayes was used to implement Naive Bayes model\n"
      ],
      "metadata": {
        "id": "mQ26QcXRWAWc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "multinomial_nb = MultinomialNB()\n",
        "\n",
        "param_grid = {'alpha': [0.05, 0.1, 0.5, 1.0, 1.5, 2.0, 2.5]} #range of hyperparameters (alpha) to search\n",
        "\n",
        "grid_search = GridSearchCV(multinomial_nb, param_grid, cv=5, scoring='f1') # do GridSearchCV for hyperparameter tuning\n",
        "grid_search.fit(X_train_tfidf, y_train)\n",
        "\n",
        "best_alpha = grid_search.best_params_['alpha'] # best hyperparameter\n",
        "\n",
        "multinomial_nb_best = MultinomialNB(alpha=best_alpha) # Train the MultinomialNB classifier with the best hyperparameter\n",
        "multinomial_nb_best.fit(X_train_tfidf, y_train)\n",
        "\n",
        "# Make predictions on the test review text\n",
        "y_pred = multinomial_nb_best.predict(X_test_tfidf)\n",
        "\n",
        "f1 = f1_score(y_test, y_pred)\n",
        "precision = precision_score(y_test, y_pred)\n",
        "recall = recall_score(y_test, y_pred)\n",
        "print(\"Naive BayesTFIDF\")\n",
        "print(f\"F1-score: {f1:.2f}\")\n",
        "print(f\"Precision: {precision:.2f}\")\n",
        "print(f\"Recall: {recall:.2f}\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "w1XhYKaxA5Ko",
        "outputId": "5a3ef889-5bd3-4294-afad-9e6faacc1222"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Naive BayesTFIDF\n",
            "F1-score: 0.82\n",
            "Precision: 0.83\n",
            "Recall: 0.81\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "grid_search.fit(X_train_bow, y_train)\n",
        "\n",
        "best_alpha = grid_search.best_params_['alpha']\n",
        "multinomial_nb_best = MultinomialNB(alpha=best_alpha)\n",
        "multinomial_nb_best.fit(X_train_bow, y_train)\n",
        "\n",
        "y_pred = multinomial_nb_best.predict(X_test_bow)\n",
        "\n",
        "f1 = f1_score(y_test, y_pred)\n",
        "precision = precision_score(y_test, y_pred)\n",
        "recall = recall_score(y_test, y_pred)\n",
        "print(\"Naive Bayes BOW\")\n",
        "print(f\"F1-score: {f1:.2f}\")\n",
        "print(f\"Precision: {precision:.2f}\")\n",
        "print(f\"Recall: {recall:.2f}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "t88UYnXiA9ab",
        "outputId": "5a9ad340-0b17-4fa0-fedd-302a60bbfd41"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Naive Bayes BOW\n",
            "F1-score: 0.81\n",
            "Precision: 0.79\n",
            "Recall: 0.84\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "QrY1ppFiAtLR"
      },
      "execution_count": null,
      "outputs": []
    }
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    "kernelspec": {
      "display_name": "Python 3",
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      "codemirror_mode": {
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      "file_extension": ".py",
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      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
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    },
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