SATP_ActionType_Shallow_Models.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Action Type Classification"
      ],
      "metadata": {
        "id": "kJdEfo2_fejC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#TODO: Hyperparameter Tuning to improve lightgbm model's test score."
      ],
      "metadata": {
        "id": "oXXFtzR4fk_G"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jTQnVb4iMxsg"
      },
      "source": [
        "# Import Libraries"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-t5ZeY2CCmJ0",
        "outputId": "e99c1670-319e-421e-f1d2-46404334e245"
      },
      "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",
            "/usr/local/lib/python3.10/dist-packages/dask/dataframe/__init__.py:42: FutureWarning: \n",
            "Dask dataframe query planning is disabled because dask-expr is not installed.\n",
            "\n",
            "You can install it with `pip install dask[dataframe]` or `conda install dask`.\n",
            "This will raise in a future version.\n",
            "\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ]
        }
      ],
      "source": [
        "import nltk\n",
        "nltk.download('stopwords')\n",
        "\n",
        "import re\n",
        "import pandas as pd\n",
        "from nltk.corpus import stopwords\n",
        "\n",
        "from sklearn.pipeline import Pipeline\n",
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "from lightgbm import LGBMClassifier\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.multioutput import MultiOutputClassifier\n",
        "from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer, TfidfTransformer"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ECwdtovUM2oX"
      },
      "source": [
        "# Get Data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "I4vy1KQFYkDV",
        "outputId": "ad6e12ce-c5f4-4110-e51c-cfe51d85a8de"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   armed_assault  arrest  bombing  infrastructure  surrender  seizure  \\\n",
              "0              0       1        0               0          0        0   \n",
              "1              0       0        0               0          1        0   \n",
              "2              0       1        0               0          0        0   \n",
              "3              1       0        0               0          0        0   \n",
              "4              0       0        1               1          0        0   \n",
              "\n",
              "   abduction                                   incident_summary  \n",
              "0          0  An alleged arms supplier to the Communist Part...  \n",
              "1          0  A Kamareddy dalam (squad) member belonging to ...  \n",
              "2          0  Senior CPI-Maoist 'Polit Bureau' and 'central ...  \n",
              "3          0  A TDP leader and former Sarpanch of Jerrela Gr...  \n",
              "4          0  The CPI-Maoist cadres blasted coffee pulping u...  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5448046d-1478-4ff2-9448-c1d296d7b646\" 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>armed_assault</th>\n",
              "      <th>arrest</th>\n",
              "      <th>bombing</th>\n",
              "      <th>infrastructure</th>\n",
              "      <th>surrender</th>\n",
              "      <th>seizure</th>\n",
              "      <th>abduction</th>\n",
              "      <th>incident_summary</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>An alleged arms supplier to the Communist Part...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A Kamareddy dalam (squad) member belonging to ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Senior CPI-Maoist 'Polit Bureau' and 'central ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A TDP leader and former Sarpanch of Jerrela Gr...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>The CPI-Maoist cadres blasted coffee pulping u...</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-5448046d-1478-4ff2-9448-c1d296d7b646')\"\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-5448046d-1478-4ff2-9448-c1d296d7b646 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-5448046d-1478-4ff2-9448-c1d296d7b646');\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-9126afe4-97a6-4344-9555-5ffed576fd33\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-9126afe4-97a6-4344-9555-5ffed576fd33')\"\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-9126afe4-97a6-4344-9555-5ffed576fd33 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "data",
              "summary": "{\n  \"name\": \"data\",\n  \"rows\": 9921,\n  \"fields\": [\n    {\n      \"column\": \"armed_assault\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"arrest\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"bombing\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"infrastructure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"surrender\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"seizure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"abduction\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"incident_summary\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 9918,\n        \"samples\": [\n          \"A leader of the BJP's youth wing, BJYM, was shot at by CPI-Maoist in Bijapur District of Chhattisgarh. \\\"A small action team of Maoists attacked Murlikrishna Reddy, the BJYM Bijapur district president, last night at Bairamgad town of Bijapur. He was attacked with a country-made gun and other traditional weapons,\\\" SP KL Dhruw said.\",\n          \"Rumpa Mahato alias Sujata alias Ashtami (21), a self-styled CPI-Maoist 'deputy area commander' in the Nayagram area of West Midnapore District, surrendered before the Police at the Bankura District Police lines.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 3
        }
      ],
      "source": [
        "data_dir = \"https://raw.githubusercontent.com/eteitelbaum/code-satp/refs/heads/main/data/action_type.csv\"\n",
        "\n",
        "data = pd.read_csv(data_dir)\n",
        "data.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "BFZxW56qY0xl",
        "outputId": "7396aa25-6934-4860-be9e-c914dea31551"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   armed_assault  arrest  bombing  infrastructure  surrender  seizure  \\\n",
              "0              0       1        0               0          0        0   \n",
              "1              0       0        0               0          1        0   \n",
              "2              0       1        0               0          0        0   \n",
              "3              1       0        0               0          0        0   \n",
              "4              0       0        1               1          0        0   \n",
              "\n",
              "   abduction                                   incident_summary    action_type  \n",
              "0          0  An alleged arms supplier to the Communist Part...         arrest  \n",
              "1          0  A Kamareddy dalam (squad) member belonging to ...      surrender  \n",
              "2          0  Senior CPI-Maoist 'Polit Bureau' and 'central ...         arrest  \n",
              "3          0  A TDP leader and former Sarpanch of Jerrela Gr...  armed_assault  \n",
              "4          0  The CPI-Maoist cadres blasted coffee pulping u...        bombing  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-fe7629b2-e855-439b-adfc-eda425597bd6\" 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>armed_assault</th>\n",
              "      <th>arrest</th>\n",
              "      <th>bombing</th>\n",
              "      <th>infrastructure</th>\n",
              "      <th>surrender</th>\n",
              "      <th>seizure</th>\n",
              "      <th>abduction</th>\n",
              "      <th>incident_summary</th>\n",
              "      <th>action_type</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>An alleged arms supplier to the Communist Part...</td>\n",
              "      <td>arrest</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A Kamareddy dalam (squad) member belonging to ...</td>\n",
              "      <td>surrender</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Senior CPI-Maoist 'Polit Bureau' and 'central ...</td>\n",
              "      <td>arrest</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A TDP leader and former Sarpanch of Jerrela Gr...</td>\n",
              "      <td>armed_assault</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>The CPI-Maoist cadres blasted coffee pulping u...</td>\n",
              "      <td>bombing</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-fe7629b2-e855-439b-adfc-eda425597bd6')\"\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-fe7629b2-e855-439b-adfc-eda425597bd6 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-fe7629b2-e855-439b-adfc-eda425597bd6');\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-fe574da1-a6ae-45c8-8f3c-f1939f664234\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-fe574da1-a6ae-45c8-8f3c-f1939f664234')\"\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-fe574da1-a6ae-45c8-8f3c-f1939f664234 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "data",
              "summary": "{\n  \"name\": \"data\",\n  \"rows\": 9921,\n  \"fields\": [\n    {\n      \"column\": \"armed_assault\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"arrest\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"bombing\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"infrastructure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"surrender\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"seizure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"abduction\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"incident_summary\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 9918,\n        \"samples\": [\n          \"A leader of the BJP's youth wing, BJYM, was shot at by CPI-Maoist in Bijapur District of Chhattisgarh. \\\"A small action team of Maoists attacked Murlikrishna Reddy, the BJYM Bijapur district president, last night at Bairamgad town of Bijapur. He was attacked with a country-made gun and other traditional weapons,\\\" SP KL Dhruw said.\",\n          \"Rumpa Mahato alias Sujata alias Ashtami (21), a self-styled CPI-Maoist 'deputy area commander' in the Nayagram area of West Midnapore District, surrendered before the Police at the Bankura District Police lines.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"action_type\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 7,\n        \"samples\": [\n          \"arrest\",\n          \"surrender\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 4
        }
      ],
      "source": [
        "data[\"action_type\"] = data.drop(\"incident_summary\", axis = 1).idxmax(axis=1)\n",
        "data.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 554
        },
        "id": "_sZMhEDT9qNh",
        "outputId": "117a1cc0-7302-4b51-e966-13b86e4171a2"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='action_type'>"
            ]
          },
          "metadata": {},
          "execution_count": 5
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "data[\"action_type\"].value_counts().plot(kind = \"bar\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data[\"action_type\"].value_counts().to_dict()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_7MPED6uqDYX",
        "outputId": "e3862a4a-5a1e-4d94-c64d-22931caaf41e"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'armed_assault': 3577,\n",
              " 'arrest': 2947,\n",
              " 'bombing': 1012,\n",
              " 'infrastructure': 803,\n",
              " 'surrender': 774,\n",
              " 'seizure': 607,\n",
              " 'abduction': 201}"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zGnxomw9M8Oz"
      },
      "source": [
        "# Clean the Data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 293
        },
        "id": "1Pq-dXf8Bo_l",
        "outputId": "66172479-a028-4af3-8c7c-047f99a473e7"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   armed_assault  arrest  bombing  infrastructure  surrender  seizure  \\\n",
              "0              0       1        0               0          0        0   \n",
              "1              0       0        0               0          1        0   \n",
              "2              0       1        0               0          0        0   \n",
              "3              1       0        0               0          0        0   \n",
              "4              0       0        1               1          0        0   \n",
              "\n",
              "   abduction                                   incident_summary  \\\n",
              "0          0  An alleged arms supplier to the Communist Part...   \n",
              "1          0  A Kamareddy dalam (squad) member belonging to ...   \n",
              "2          0  Senior CPI-Maoist 'Polit Bureau' and 'central ...   \n",
              "3          0  A TDP leader and former Sarpanch of Jerrela Gr...   \n",
              "4          0  The CPI-Maoist cadres blasted coffee pulping u...   \n",
              "\n",
              "     action_type                                    summary_cleaned  \n",
              "0         arrest  alleged arms supplier communist party indiamao...  \n",
              "1      surrender  kamareddy dalam squad member belonging janasha...  \n",
              "2         arrest  senior cpimaoist polit bureau central committe...  \n",
              "3  armed_assault  tdp leader former sarpanch jerrela gram pancha...  \n",
              "4        bombing  cpimaoist cadres blasted coffee pulping units ...  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f0183355-bc5a-40c0-9226-1e4b7ad390a9\" 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>armed_assault</th>\n",
              "      <th>arrest</th>\n",
              "      <th>bombing</th>\n",
              "      <th>infrastructure</th>\n",
              "      <th>surrender</th>\n",
              "      <th>seizure</th>\n",
              "      <th>abduction</th>\n",
              "      <th>incident_summary</th>\n",
              "      <th>action_type</th>\n",
              "      <th>summary_cleaned</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>An alleged arms supplier to the Communist Part...</td>\n",
              "      <td>arrest</td>\n",
              "      <td>alleged arms supplier communist party indiamao...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A Kamareddy dalam (squad) member belonging to ...</td>\n",
              "      <td>surrender</td>\n",
              "      <td>kamareddy dalam squad member belonging janasha...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Senior CPI-Maoist 'Polit Bureau' and 'central ...</td>\n",
              "      <td>arrest</td>\n",
              "      <td>senior cpimaoist polit bureau central committe...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A TDP leader and former Sarpanch of Jerrela Gr...</td>\n",
              "      <td>armed_assault</td>\n",
              "      <td>tdp leader former sarpanch jerrela gram pancha...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>The CPI-Maoist cadres blasted coffee pulping u...</td>\n",
              "      <td>bombing</td>\n",
              "      <td>cpimaoist cadres blasted coffee pulping units ...</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-f0183355-bc5a-40c0-9226-1e4b7ad390a9')\"\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-f0183355-bc5a-40c0-9226-1e4b7ad390a9 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-f0183355-bc5a-40c0-9226-1e4b7ad390a9');\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-4cec2e7e-ea49-4d30-bffd-b9677aad227f\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-4cec2e7e-ea49-4d30-bffd-b9677aad227f')\"\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-4cec2e7e-ea49-4d30-bffd-b9677aad227f button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "data",
              "summary": "{\n  \"name\": \"data\",\n  \"rows\": 9921,\n  \"fields\": [\n    {\n      \"column\": \"armed_assault\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"arrest\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"bombing\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"infrastructure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"surrender\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"seizure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"abduction\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"incident_summary\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 9918,\n        \"samples\": [\n          \"A leader of the BJP's youth wing, BJYM, was shot at by CPI-Maoist in Bijapur District of Chhattisgarh. \\\"A small action team of Maoists attacked Murlikrishna Reddy, the BJYM Bijapur district president, last night at Bairamgad town of Bijapur. He was attacked with a country-made gun and other traditional weapons,\\\" SP KL Dhruw said.\",\n          \"Rumpa Mahato alias Sujata alias Ashtami (21), a self-styled CPI-Maoist 'deputy area commander' in the Nayagram area of West Midnapore District, surrendered before the Police at the Bankura District Police lines.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"action_type\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 7,\n        \"samples\": [\n          \"arrest\",\n          \"surrender\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"summary_cleaned\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 9917,\n        \"samples\": [\n          \"two plfi identified niral topno sanichar surin arrested explosives recovered gandekadah west singhbhum district\",\n          \"landmine exploded bhat area salbani police station west midnapore district damaged culvert road connecting midnapore town lalgarh bandh shutdown called cpimaoistbacked pcpa\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 7
        }
      ],
      "source": [
        "REPLACE_BY_SPACE_RE = re.compile('[/(){}\\[\\]\\|@,;]')\n",
        "BAD_SYMBOLS_RE = re.compile('[^a-z ]')\n",
        "STOPWORDS = set(stopwords.words('english'))\n",
        "\n",
        "def clean_text(text):\n",
        "    \"\"\"\n",
        "        Params:\n",
        "                text: input text\n",
        "\n",
        "        Return:\n",
        "                Cleaned text\n",
        "    \"\"\"\n",
        "    text = text.lower()\n",
        "    text = REPLACE_BY_SPACE_RE.sub(' ', text)\n",
        "    text = BAD_SYMBOLS_RE.sub('', text)\n",
        "    text = ' '.join(word for word in text.split() if word not in STOPWORDS)\n",
        "    return text\n",
        "\n",
        "data['summary_cleaned'] = data['incident_summary'].apply(clean_text)\n",
        "data.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qwgSB_viM_pj"
      },
      "source": [
        "# Create splits"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 98
        },
        "id": "X5hGbSXcXhh5",
        "outputId": "97c53911-73bf-41c8-c7af-83e8c1dba491"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   armed_assault  arrest  bombing  infrastructure  surrender  seizure  \\\n",
              "0              0       1        0               0          0        0   \n",
              "\n",
              "   abduction                                   incident_summary action_type  \\\n",
              "0          0  An alleged arms supplier to the Communist Part...      arrest   \n",
              "\n",
              "                                     summary_cleaned  \n",
              "0  alleged arms supplier communist party indiamao...  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-11806dd4-3258-4f24-8eb4-4e3ec98184ef\" 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>armed_assault</th>\n",
              "      <th>arrest</th>\n",
              "      <th>bombing</th>\n",
              "      <th>infrastructure</th>\n",
              "      <th>surrender</th>\n",
              "      <th>seizure</th>\n",
              "      <th>abduction</th>\n",
              "      <th>incident_summary</th>\n",
              "      <th>action_type</th>\n",
              "      <th>summary_cleaned</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>An alleged arms supplier to the Communist Part...</td>\n",
              "      <td>arrest</td>\n",
              "      <td>alleged arms supplier communist party indiamao...</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-11806dd4-3258-4f24-8eb4-4e3ec98184ef')\"\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-11806dd4-3258-4f24-8eb4-4e3ec98184ef 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-11806dd4-3258-4f24-8eb4-4e3ec98184ef');\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>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "data",
              "summary": "{\n  \"name\": \"data\",\n  \"rows\": 9921,\n  \"fields\": [\n    {\n      \"column\": \"armed_assault\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"arrest\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"bombing\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"infrastructure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"surrender\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"seizure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"abduction\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"incident_summary\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 9918,\n        \"samples\": [\n          \"A leader of the BJP's youth wing, BJYM, was shot at by CPI-Maoist in Bijapur District of Chhattisgarh. \\\"A small action team of Maoists attacked Murlikrishna Reddy, the BJYM Bijapur district president, last night at Bairamgad town of Bijapur. He was attacked with a country-made gun and other traditional weapons,\\\" SP KL Dhruw said.\",\n          \"Rumpa Mahato alias Sujata alias Ashtami (21), a self-styled CPI-Maoist 'deputy area commander' in the Nayagram area of West Midnapore District, surrendered before the Police at the Bankura District Police lines.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"action_type\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 7,\n        \"samples\": [\n          \"arrest\",\n          \"surrender\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"summary_cleaned\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 9917,\n        \"samples\": [\n          \"two plfi identified niral topno sanichar surin arrested explosives recovered gandekadah west singhbhum district\",\n          \"landmine exploded bhat area salbani police station west midnapore district damaged culvert road connecting midnapore town lalgarh bandh shutdown called cpimaoistbacked pcpa\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 8
        }
      ],
      "source": [
        "data.head(1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 213
        },
        "id": "qXdQTWDsG_i7",
        "outputId": "a984c4da-52d9-4ebe-9208-aceace7aa526"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "(9921,)"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "(9921, 7)"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "0    alleged arms supplier communist party indiamao...\n",
              "Name: summary_cleaned, dtype: object"
            ],
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>summary_cleaned</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>alleged arms supplier communist party indiamao...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> object</label>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   armed_assault  arrest  bombing  infrastructure  surrender  seizure  \\\n",
              "0              0       1        0               0          0        0   \n",
              "\n",
              "   abduction  \n",
              "0          0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-7dfb1833-0924-45cc-b90b-bb31fb19884a\" 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>armed_assault</th>\n",
              "      <th>arrest</th>\n",
              "      <th>bombing</th>\n",
              "      <th>infrastructure</th>\n",
              "      <th>surrender</th>\n",
              "      <th>seizure</th>\n",
              "      <th>abduction</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7dfb1833-0924-45cc-b90b-bb31fb19884a')\"\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-7dfb1833-0924-45cc-b90b-bb31fb19884a 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-7dfb1833-0924-45cc-b90b-bb31fb19884a');\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>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"display(X\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"armed_assault\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"arrest\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1,\n        \"max\": 1,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"bombing\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"infrastructure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"surrender\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"seizure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"abduction\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "X = data[\"summary_cleaned\"]\n",
        "y = data.iloc[:, 0:7]\n",
        "strat = data[\"action_type\"]\n",
        "display(X.shape, y.shape, X.head(1), y.head(1))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8zJG7uY4gskD",
        "outputId": "cb41088f-ccf1-419f-ec44-9e480c93dc6e"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((8928,), (993,), (8928, 7), (993, 7))"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ],
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(X, y, stratify=strat, test_size=0.1, random_state=42)\n",
        "X_train.shape, X_test.shape, y_train.shape, y_test.shape"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oXj-f629NBva"
      },
      "source": [
        "# Train a Logistic Regression Model (Multi-Label Classification)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 258
        },
        "collapsed": true,
        "id": "Dfii_eaeCzhf",
        "outputId": "a377a0df-9868-4a7e-91ed-2150c3e6b008"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Pipeline(steps=[('vect', CountVectorizer()), ('tfidf', TfidfTransformer()),\n",
              "                ('clf',\n",
              "                 MultiOutputClassifier(estimator=LogisticRegression(class_weight='balanced')))])"
            ],
            "text/html": [
              "<style>#sk-container-id-1 {\n",
              "  /* Definition of color scheme common for light and dark mode */\n",
              "  --sklearn-color-text: black;\n",
              "  --sklearn-color-line: gray;\n",
              "  /* Definition of color scheme for unfitted estimators */\n",
              "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
              "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
              "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
              "  --sklearn-color-unfitted-level-3: chocolate;\n",
              "  /* Definition of color scheme for fitted estimators */\n",
              "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
              "  --sklearn-color-fitted-level-1: #d4ebff;\n",
              "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
              "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
              "\n",
              "  /* Specific color for light theme */\n",
              "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
              "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
              "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
              "  --sklearn-color-icon: #696969;\n",
              "\n",
              "  @media (prefers-color-scheme: dark) {\n",
              "    /* Redefinition of color scheme for dark theme */\n",
              "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
              "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
              "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
              "    --sklearn-color-icon: #878787;\n",
              "  }\n",
              "}\n",
              "\n",
              "#sk-container-id-1 {\n",
              "  color: var(--sklearn-color-text);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 pre {\n",
              "  padding: 0;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 input.sk-hidden--visually {\n",
              "  border: 0;\n",
              "  clip: rect(1px 1px 1px 1px);\n",
              "  clip: rect(1px, 1px, 1px, 1px);\n",
              "  height: 1px;\n",
              "  margin: -1px;\n",
              "  overflow: hidden;\n",
              "  padding: 0;\n",
              "  position: absolute;\n",
              "  width: 1px;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-dashed-wrapped {\n",
              "  border: 1px dashed var(--sklearn-color-line);\n",
              "  margin: 0 0.4em 0.5em 0.4em;\n",
              "  box-sizing: border-box;\n",
              "  padding-bottom: 0.4em;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-container {\n",
              "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
              "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
              "     so we also need the `!important` here to be able to override the\n",
              "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
              "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
              "  display: inline-block !important;\n",
              "  position: relative;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-text-repr-fallback {\n",
              "  display: none;\n",
              "}\n",
              "\n",
              "div.sk-parallel-item,\n",
              "div.sk-serial,\n",
              "div.sk-item {\n",
              "  /* draw centered vertical line to link estimators */\n",
              "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
              "  background-size: 2px 100%;\n",
              "  background-repeat: no-repeat;\n",
              "  background-position: center center;\n",
              "}\n",
              "\n",
              "/* Parallel-specific style estimator block */\n",
              "\n",
              "#sk-container-id-1 div.sk-parallel-item::after {\n",
              "  content: \"\";\n",
              "  width: 100%;\n",
              "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
              "  flex-grow: 1;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-parallel {\n",
              "  display: flex;\n",
              "  align-items: stretch;\n",
              "  justify-content: center;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "  position: relative;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-parallel-item {\n",
              "  display: flex;\n",
              "  flex-direction: column;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
              "  align-self: flex-end;\n",
              "  width: 50%;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
              "  align-self: flex-start;\n",
              "  width: 50%;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
              "  width: 0;\n",
              "}\n",
              "\n",
              "/* Serial-specific style estimator block */\n",
              "\n",
              "#sk-container-id-1 div.sk-serial {\n",
              "  display: flex;\n",
              "  flex-direction: column;\n",
              "  align-items: center;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "  padding-right: 1em;\n",
              "  padding-left: 1em;\n",
              "}\n",
              "\n",
              "\n",
              "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
              "clickable and can be expanded/collapsed.\n",
              "- Pipeline and ColumnTransformer use this feature and define the default style\n",
              "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
              "*/\n",
              "\n",
              "/* Pipeline and ColumnTransformer style (default) */\n",
              "\n",
              "#sk-container-id-1 div.sk-toggleable {\n",
              "  /* Default theme specific background. It is overwritten whether we have a\n",
              "  specific estimator or a Pipeline/ColumnTransformer */\n",
              "  background-color: var(--sklearn-color-background);\n",
              "}\n",
              "\n",
              "/* Toggleable label */\n",
              "#sk-container-id-1 label.sk-toggleable__label {\n",
              "  cursor: pointer;\n",
              "  display: block;\n",
              "  width: 100%;\n",
              "  margin-bottom: 0;\n",
              "  padding: 0.5em;\n",
              "  box-sizing: border-box;\n",
              "  text-align: center;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
              "  /* Arrow on the left of the label */\n",
              "  content: \"▸\";\n",
              "  float: left;\n",
              "  margin-right: 0.25em;\n",
              "  color: var(--sklearn-color-icon);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
              "  color: var(--sklearn-color-text);\n",
              "}\n",
              "\n",
              "/* Toggleable content - dropdown */\n",
              "\n",
              "#sk-container-id-1 div.sk-toggleable__content {\n",
              "  max-height: 0;\n",
              "  max-width: 0;\n",
              "  overflow: hidden;\n",
              "  text-align: left;\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-toggleable__content pre {\n",
              "  margin: 0.2em;\n",
              "  border-radius: 0.25em;\n",
              "  color: var(--sklearn-color-text);\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
              "  /* Expand drop-down */\n",
              "  max-height: 200px;\n",
              "  max-width: 100%;\n",
              "  overflow: auto;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
              "  content: \"▾\";\n",
              "}\n",
              "\n",
              "/* Pipeline/ColumnTransformer-specific style */\n",
              "\n",
              "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
              "  color: var(--sklearn-color-text);\n",
              "  background-color: var(--sklearn-color-unfitted-level-2);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
              "  background-color: var(--sklearn-color-fitted-level-2);\n",
              "}\n",
              "\n",
              "/* Estimator-specific style */\n",
              "\n",
              "/* Colorize estimator box */\n",
              "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-2);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-2);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
              "#sk-container-id-1 div.sk-label label {\n",
              "  /* The background is the default theme color */\n",
              "  color: var(--sklearn-color-text-on-default-background);\n",
              "}\n",
              "\n",
              "/* On hover, darken the color of the background */\n",
              "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
              "  color: var(--sklearn-color-text);\n",
              "  background-color: var(--sklearn-color-unfitted-level-2);\n",
              "}\n",
              "\n",
              "/* Label box, darken color on hover, fitted */\n",
              "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
              "  color: var(--sklearn-color-text);\n",
              "  background-color: var(--sklearn-color-fitted-level-2);\n",
              "}\n",
              "\n",
              "/* Estimator label */\n",
              "\n",
              "#sk-container-id-1 div.sk-label label {\n",
              "  font-family: monospace;\n",
              "  font-weight: bold;\n",
              "  display: inline-block;\n",
              "  line-height: 1.2em;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-label-container {\n",
              "  text-align: center;\n",
              "}\n",
              "\n",
              "/* Estimator-specific */\n",
              "#sk-container-id-1 div.sk-estimator {\n",
              "  font-family: monospace;\n",
              "  border: 1px dotted var(--sklearn-color-border-box);\n",
              "  border-radius: 0.25em;\n",
              "  box-sizing: border-box;\n",
              "  margin-bottom: 0.5em;\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-estimator.fitted {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-0);\n",
              "}\n",
              "\n",
              "/* on hover */\n",
              "#sk-container-id-1 div.sk-estimator:hover {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-2);\n",
              "}\n",
              "\n",
              "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-2);\n",
              "}\n",
              "\n",
              "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
              "\n",
              "/* Common style for \"i\" and \"?\" */\n",
              "\n",
              ".sk-estimator-doc-link,\n",
              "a:link.sk-estimator-doc-link,\n",
              "a:visited.sk-estimator-doc-link {\n",
              "  float: right;\n",
              "  font-size: smaller;\n",
              "  line-height: 1em;\n",
              "  font-family: monospace;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "  border-radius: 1em;\n",
              "  height: 1em;\n",
              "  width: 1em;\n",
              "  text-decoration: none !important;\n",
              "  margin-left: 1ex;\n",
              "  /* unfitted */\n",
              "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
              "  color: var(--sklearn-color-unfitted-level-1);\n",
              "}\n",
              "\n",
              ".sk-estimator-doc-link.fitted,\n",
              "a:link.sk-estimator-doc-link.fitted,\n",
              "a:visited.sk-estimator-doc-link.fitted {\n",
              "  /* fitted */\n",
              "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
              "  color: var(--sklearn-color-fitted-level-1);\n",
              "}\n",
              "\n",
              "/* On hover */\n",
              "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
              ".sk-estimator-doc-link:hover,\n",
              "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
              ".sk-estimator-doc-link:hover {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-3);\n",
              "  color: var(--sklearn-color-background);\n",
              "  text-decoration: none;\n",
              "}\n",
              "\n",
              "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
              ".sk-estimator-doc-link.fitted:hover,\n",
              "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
              ".sk-estimator-doc-link.fitted:hover {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-3);\n",
              "  color: var(--sklearn-color-background);\n",
              "  text-decoration: none;\n",
              "}\n",
              "\n",
              "/* Span, style for the box shown on hovering the info icon */\n",
              ".sk-estimator-doc-link span {\n",
              "  display: none;\n",
              "  z-index: 9999;\n",
              "  position: relative;\n",
              "  font-weight: normal;\n",
              "  right: .2ex;\n",
              "  padding: .5ex;\n",
              "  margin: .5ex;\n",
              "  width: min-content;\n",
              "  min-width: 20ex;\n",
              "  max-width: 50ex;\n",
              "  color: var(--sklearn-color-text);\n",
              "  box-shadow: 2pt 2pt 4pt #999;\n",
              "  /* unfitted */\n",
              "  background: var(--sklearn-color-unfitted-level-0);\n",
              "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
              "}\n",
              "\n",
              ".sk-estimator-doc-link.fitted span {\n",
              "  /* fitted */\n",
              "  background: var(--sklearn-color-fitted-level-0);\n",
              "  border: var(--sklearn-color-fitted-level-3);\n",
              "}\n",
              "\n",
              ".sk-estimator-doc-link:hover span {\n",
              "  display: block;\n",
              "}\n",
              "\n",
              "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
              "\n",
              "#sk-container-id-1 a.estimator_doc_link {\n",
              "  float: right;\n",
              "  font-size: 1rem;\n",
              "  line-height: 1em;\n",
              "  font-family: monospace;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "  border-radius: 1rem;\n",
              "  height: 1rem;\n",
              "  width: 1rem;\n",
              "  text-decoration: none;\n",
              "  /* unfitted */\n",
              "  color: var(--sklearn-color-unfitted-level-1);\n",
              "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
              "  /* fitted */\n",
              "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
              "  color: var(--sklearn-color-fitted-level-1);\n",
              "}\n",
              "\n",
              "/* On hover */\n",
              "#sk-container-id-1 a.estimator_doc_link:hover {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-3);\n",
              "  color: var(--sklearn-color-background);\n",
              "  text-decoration: none;\n",
              "}\n",
              "\n",
              "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-3);\n",
              "}\n",
              "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;vect&#x27;, CountVectorizer()), (&#x27;tfidf&#x27;, TfidfTransformer()),\n",
              "                (&#x27;clf&#x27;,\n",
              "                 MultiOutputClassifier(estimator=LogisticRegression(class_weight=&#x27;balanced&#x27;)))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;vect&#x27;, CountVectorizer()), (&#x27;tfidf&#x27;, TfidfTransformer()),\n",
              "                (&#x27;clf&#x27;,\n",
              "                 MultiOutputClassifier(estimator=LogisticRegression(class_weight=&#x27;balanced&#x27;)))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;CountVectorizer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html\">?<span>Documentation for CountVectorizer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>CountVectorizer()</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;TfidfTransformer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.feature_extraction.text.TfidfTransformer.html\">?<span>Documentation for TfidfTransformer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>TfidfTransformer()</pre></div> </div></div><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;clf: MultiOutputClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.multioutput.MultiOutputClassifier.html\">?<span>Documentation for clf: MultiOutputClassifier</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>MultiOutputClassifier(estimator=LogisticRegression(class_weight=&#x27;balanced&#x27;))</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">estimator: LogisticRegression</label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression(class_weight=&#x27;balanced&#x27;)</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;LogisticRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression(class_weight=&#x27;balanced&#x27;)</pre></div> </div></div></div></div></div></div></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ],
      "source": [
        "lr = Pipeline([('vect', CountVectorizer()),\n",
        "               ('tfidf', TfidfTransformer()),\n",
        "               ('clf', MultiOutputClassifier(LogisticRegression(class_weight=\"balanced\")))\n",
        "              ])\n",
        "lr.fit(X_train, y_train)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "grpCs57JEsob"
      },
      "outputs": [],
      "source": [
        "train_preds_lr = lr.predict(X_train)\n",
        "test_preds_lr = lr.predict(X_test)\n",
        "\n",
        "preds_df_train_lr = pd.DataFrame(data=train_preds_lr, columns = y.columns)\n",
        "preds_df_test_lr = pd.DataFrame(data=test_preds_lr, columns = y.columns)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dQlHuLa1-7Nh"
      },
      "source": [
        "# LgithGBM Model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 258
        },
        "id": "212DHAKY_ESe",
        "outputId": "573d443f-65e2-4265-c296-2eab6741e286"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Pipeline(steps=[('vect', CountVectorizer()), ('tfidf', TfidfTransformer()),\n",
              "                ('clf',\n",
              "                 MultiOutputClassifier(estimator=LGBMClassifier(is_unbalance=True,\n",
              "                                                                verbose=-1)))])"
            ],
            "text/html": [
              "<style>#sk-container-id-2 {\n",
              "  /* Definition of color scheme common for light and dark mode */\n",
              "  --sklearn-color-text: black;\n",
              "  --sklearn-color-line: gray;\n",
              "  /* Definition of color scheme for unfitted estimators */\n",
              "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
              "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
              "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
              "  --sklearn-color-unfitted-level-3: chocolate;\n",
              "  /* Definition of color scheme for fitted estimators */\n",
              "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
              "  --sklearn-color-fitted-level-1: #d4ebff;\n",
              "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
              "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
              "\n",
              "  /* Specific color for light theme */\n",
              "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
              "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
              "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
              "  --sklearn-color-icon: #696969;\n",
              "\n",
              "  @media (prefers-color-scheme: dark) {\n",
              "    /* Redefinition of color scheme for dark theme */\n",
              "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
              "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
              "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
              "    --sklearn-color-icon: #878787;\n",
              "  }\n",
              "}\n",
              "\n",
              "#sk-container-id-2 {\n",
              "  color: var(--sklearn-color-text);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 pre {\n",
              "  padding: 0;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 input.sk-hidden--visually {\n",
              "  border: 0;\n",
              "  clip: rect(1px 1px 1px 1px);\n",
              "  clip: rect(1px, 1px, 1px, 1px);\n",
              "  height: 1px;\n",
              "  margin: -1px;\n",
              "  overflow: hidden;\n",
              "  padding: 0;\n",
              "  position: absolute;\n",
              "  width: 1px;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-dashed-wrapped {\n",
              "  border: 1px dashed var(--sklearn-color-line);\n",
              "  margin: 0 0.4em 0.5em 0.4em;\n",
              "  box-sizing: border-box;\n",
              "  padding-bottom: 0.4em;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-container {\n",
              "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
              "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
              "     so we also need the `!important` here to be able to override the\n",
              "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
              "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
              "  display: inline-block !important;\n",
              "  position: relative;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-text-repr-fallback {\n",
              "  display: none;\n",
              "}\n",
              "\n",
              "div.sk-parallel-item,\n",
              "div.sk-serial,\n",
              "div.sk-item {\n",
              "  /* draw centered vertical line to link estimators */\n",
              "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
              "  background-size: 2px 100%;\n",
              "  background-repeat: no-repeat;\n",
              "  background-position: center center;\n",
              "}\n",
              "\n",
              "/* Parallel-specific style estimator block */\n",
              "\n",
              "#sk-container-id-2 div.sk-parallel-item::after {\n",
              "  content: \"\";\n",
              "  width: 100%;\n",
              "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
              "  flex-grow: 1;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-parallel {\n",
              "  display: flex;\n",
              "  align-items: stretch;\n",
              "  justify-content: center;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "  position: relative;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-parallel-item {\n",
              "  display: flex;\n",
              "  flex-direction: column;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
              "  align-self: flex-end;\n",
              "  width: 50%;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
              "  align-self: flex-start;\n",
              "  width: 50%;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
              "  width: 0;\n",
              "}\n",
              "\n",
              "/* Serial-specific style estimator block */\n",
              "\n",
              "#sk-container-id-2 div.sk-serial {\n",
              "  display: flex;\n",
              "  flex-direction: column;\n",
              "  align-items: center;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "  padding-right: 1em;\n",
              "  padding-left: 1em;\n",
              "}\n",
              "\n",
              "\n",
              "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
              "clickable and can be expanded/collapsed.\n",
              "- Pipeline and ColumnTransformer use this feature and define the default style\n",
              "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
              "*/\n",
              "\n",
              "/* Pipeline and ColumnTransformer style (default) */\n",
              "\n",
              "#sk-container-id-2 div.sk-toggleable {\n",
              "  /* Default theme specific background. It is overwritten whether we have a\n",
              "  specific estimator or a Pipeline/ColumnTransformer */\n",
              "  background-color: var(--sklearn-color-background);\n",
              "}\n",
              "\n",
              "/* Toggleable label */\n",
              "#sk-container-id-2 label.sk-toggleable__label {\n",
              "  cursor: pointer;\n",
              "  display: block;\n",
              "  width: 100%;\n",
              "  margin-bottom: 0;\n",
              "  padding: 0.5em;\n",
              "  box-sizing: border-box;\n",
              "  text-align: center;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
              "  /* Arrow on the left of the label */\n",
              "  content: \"▸\";\n",
              "  float: left;\n",
              "  margin-right: 0.25em;\n",
              "  color: var(--sklearn-color-icon);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
              "  color: var(--sklearn-color-text);\n",
              "}\n",
              "\n",
              "/* Toggleable content - dropdown */\n",
              "\n",
              "#sk-container-id-2 div.sk-toggleable__content {\n",
              "  max-height: 0;\n",
              "  max-width: 0;\n",
              "  overflow: hidden;\n",
              "  text-align: left;\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-toggleable__content pre {\n",
              "  margin: 0.2em;\n",
              "  border-radius: 0.25em;\n",
              "  color: var(--sklearn-color-text);\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
              "  /* Expand drop-down */\n",
              "  max-height: 200px;\n",
              "  max-width: 100%;\n",
              "  overflow: auto;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
              "  content: \"▾\";\n",
              "}\n",
              "\n",
              "/* Pipeline/ColumnTransformer-specific style */\n",
              "\n",
              "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
              "  color: var(--sklearn-color-text);\n",
              "  background-color: var(--sklearn-color-unfitted-level-2);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
              "  background-color: var(--sklearn-color-fitted-level-2);\n",
              "}\n",
              "\n",
              "/* Estimator-specific style */\n",
              "\n",
              "/* Colorize estimator box */\n",
              "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-2);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-2);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
              "#sk-container-id-2 div.sk-label label {\n",
              "  /* The background is the default theme color */\n",
              "  color: var(--sklearn-color-text-on-default-background);\n",
              "}\n",
              "\n",
              "/* On hover, darken the color of the background */\n",
              "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
              "  color: var(--sklearn-color-text);\n",
              "  background-color: var(--sklearn-color-unfitted-level-2);\n",
              "}\n",
              "\n",
              "/* Label box, darken color on hover, fitted */\n",
              "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
              "  color: var(--sklearn-color-text);\n",
              "  background-color: var(--sklearn-color-fitted-level-2);\n",
              "}\n",
              "\n",
              "/* Estimator label */\n",
              "\n",
              "#sk-container-id-2 div.sk-label label {\n",
              "  font-family: monospace;\n",
              "  font-weight: bold;\n",
              "  display: inline-block;\n",
              "  line-height: 1.2em;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-label-container {\n",
              "  text-align: center;\n",
              "}\n",
              "\n",
              "/* Estimator-specific */\n",
              "#sk-container-id-2 div.sk-estimator {\n",
              "  font-family: monospace;\n",
              "  border: 1px dotted var(--sklearn-color-border-box);\n",
              "  border-radius: 0.25em;\n",
              "  box-sizing: border-box;\n",
              "  margin-bottom: 0.5em;\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-estimator.fitted {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-0);\n",
              "}\n",
              "\n",
              "/* on hover */\n",
              "#sk-container-id-2 div.sk-estimator:hover {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-2);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-2);\n",
              "}\n",
              "\n",
              "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
              "\n",
              "/* Common style for \"i\" and \"?\" */\n",
              "\n",
              ".sk-estimator-doc-link,\n",
              "a:link.sk-estimator-doc-link,\n",
              "a:visited.sk-estimator-doc-link {\n",
              "  float: right;\n",
              "  font-size: smaller;\n",
              "  line-height: 1em;\n",
              "  font-family: monospace;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "  border-radius: 1em;\n",
              "  height: 1em;\n",
              "  width: 1em;\n",
              "  text-decoration: none !important;\n",
              "  margin-left: 1ex;\n",
              "  /* unfitted */\n",
              "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
              "  color: var(--sklearn-color-unfitted-level-1);\n",
              "}\n",
              "\n",
              ".sk-estimator-doc-link.fitted,\n",
              "a:link.sk-estimator-doc-link.fitted,\n",
              "a:visited.sk-estimator-doc-link.fitted {\n",
              "  /* fitted */\n",
              "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
              "  color: var(--sklearn-color-fitted-level-1);\n",
              "}\n",
              "\n",
              "/* On hover */\n",
              "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
              ".sk-estimator-doc-link:hover,\n",
              "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
              ".sk-estimator-doc-link:hover {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-3);\n",
              "  color: var(--sklearn-color-background);\n",
              "  text-decoration: none;\n",
              "}\n",
              "\n",
              "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
              ".sk-estimator-doc-link.fitted:hover,\n",
              "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
              ".sk-estimator-doc-link.fitted:hover {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-3);\n",
              "  color: var(--sklearn-color-background);\n",
              "  text-decoration: none;\n",
              "}\n",
              "\n",
              "/* Span, style for the box shown on hovering the info icon */\n",
              ".sk-estimator-doc-link span {\n",
              "  display: none;\n",
              "  z-index: 9999;\n",
              "  position: relative;\n",
              "  font-weight: normal;\n",
              "  right: .2ex;\n",
              "  padding: .5ex;\n",
              "  margin: .5ex;\n",
              "  width: min-content;\n",
              "  min-width: 20ex;\n",
              "  max-width: 50ex;\n",
              "  color: var(--sklearn-color-text);\n",
              "  box-shadow: 2pt 2pt 4pt #999;\n",
              "  /* unfitted */\n",
              "  background: var(--sklearn-color-unfitted-level-0);\n",
              "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
              "}\n",
              "\n",
              ".sk-estimator-doc-link.fitted span {\n",
              "  /* fitted */\n",
              "  background: var(--sklearn-color-fitted-level-0);\n",
              "  border: var(--sklearn-color-fitted-level-3);\n",
              "}\n",
              "\n",
              ".sk-estimator-doc-link:hover span {\n",
              "  display: block;\n",
              "}\n",
              "\n",
              "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
              "\n",
              "#sk-container-id-2 a.estimator_doc_link {\n",
              "  float: right;\n",
              "  font-size: 1rem;\n",
              "  line-height: 1em;\n",
              "  font-family: monospace;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "  border-radius: 1rem;\n",
              "  height: 1rem;\n",
              "  width: 1rem;\n",
              "  text-decoration: none;\n",
              "  /* unfitted */\n",
              "  color: var(--sklearn-color-unfitted-level-1);\n",
              "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
              "  /* fitted */\n",
              "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
              "  color: var(--sklearn-color-fitted-level-1);\n",
              "}\n",
              "\n",
              "/* On hover */\n",
              "#sk-container-id-2 a.estimator_doc_link:hover {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-3);\n",
              "  color: var(--sklearn-color-background);\n",
              "  text-decoration: none;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-3);\n",
              "}\n",
              "</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;vect&#x27;, CountVectorizer()), (&#x27;tfidf&#x27;, TfidfTransformer()),\n",
              "                (&#x27;clf&#x27;,\n",
              "                 MultiOutputClassifier(estimator=LGBMClassifier(is_unbalance=True,\n",
              "                                                                verbose=-1)))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;vect&#x27;, CountVectorizer()), (&#x27;tfidf&#x27;, TfidfTransformer()),\n",
              "                (&#x27;clf&#x27;,\n",
              "                 MultiOutputClassifier(estimator=LGBMClassifier(is_unbalance=True,\n",
              "                                                                verbose=-1)))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;CountVectorizer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html\">?<span>Documentation for CountVectorizer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>CountVectorizer()</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-9\" type=\"checkbox\" ><label for=\"sk-estimator-id-9\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;TfidfTransformer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.feature_extraction.text.TfidfTransformer.html\">?<span>Documentation for TfidfTransformer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>TfidfTransformer()</pre></div> </div></div><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-10\" type=\"checkbox\" ><label for=\"sk-estimator-id-10\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;clf: MultiOutputClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.multioutput.MultiOutputClassifier.html\">?<span>Documentation for clf: MultiOutputClassifier</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>MultiOutputClassifier(estimator=LGBMClassifier(is_unbalance=True, verbose=-1))</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-11\" type=\"checkbox\" ><label for=\"sk-estimator-id-11\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">estimator: LGBMClassifier</label><div class=\"sk-toggleable__content fitted\"><pre>LGBMClassifier(is_unbalance=True, verbose=-1)</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-12\" type=\"checkbox\" ><label for=\"sk-estimator-id-12\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">LGBMClassifier</label><div class=\"sk-toggleable__content fitted\"><pre>LGBMClassifier(is_unbalance=True, verbose=-1)</pre></div> </div></div></div></div></div></div></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ],
      "source": [
        "lgbm = Pipeline([('vect', CountVectorizer()),\n",
        "               ('tfidf', TfidfTransformer()),\n",
        "               ('clf', MultiOutputClassifier(LGBMClassifier(is_unbalance = True, verbose = -1)))\n",
        "              ])\n",
        "\n",
        "lgbm.fit(X_train, y_train)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "id": "94cJetPU_oJw"
      },
      "outputs": [],
      "source": [
        "train_preds_lgbm = lgbm.predict(X_train)\n",
        "test_preds_lgbm = lgbm.predict(X_test)\n",
        "\n",
        "preds_df_train_lgbm = pd.DataFrame(data=train_preds_lgbm, columns = y.columns)\n",
        "preds_df_test_lgbm = pd.DataFrame(data=test_preds_lgbm, columns = y.columns)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7W4xAna2NHk0"
      },
      "source": [
        "# Evaluation"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JYo3kFytngCZ"
      },
      "source": [
        "MLC Scores"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3Dxe9XrDlLJI",
        "outputId": "f2b7a848-edc2-41cf-d0a7-d577dc18ae8c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Logistic Regression Train Accuracy: 0.8699596774193549\n"
          ]
        }
      ],
      "source": [
        "print(\"Logistic Regression Train Accuracy:\", lr.score(X_train, y_train))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y-XrlPPMIczc",
        "outputId": "14a1516b-c571-4555-b702-c3678b63a3c2"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Logistic Regression Test Accuracy: 0.7754279959718026\n"
          ]
        }
      ],
      "source": [
        "print(\"Logistic Regression Test Accuracy:\", lr.score(X_test, y_test))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eAWG1Upj_h43",
        "outputId": "e849cbc6-0cca-4e14-e451-9b4d879a8199"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "LGBM Train Accuracy: 0.975358422939068\n"
          ]
        }
      ],
      "source": [
        "print(\"LGBM Train Accuracy:\", lgbm.score(X_train, y_train))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gKV1MrCd_iR6",
        "outputId": "9d67c5ba-4549-4289-d648-153f8d824a1a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "LGBM Test Accuracy: 0.8318227593152064\n"
          ]
        }
      ],
      "source": [
        "print(\"LGBM Test Accuracy:\", lgbm.score(X_test, y_test))"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# How is the model performing of different labels\n",
        "\n",
        "compare = preds_df_train_lgbm == y_train.reset_index(drop=True)\n",
        "\n",
        "print(\"Training Scores:\")\n",
        "for i in range(compare.shape[1]):\n",
        "  print(f\"Label ({compare.columns[i]}) score: {(compare.iloc[:, i].sum()) / compare.shape[0]:.6f}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TvmiQEO4sSJQ",
        "outputId": "946bc59d-8bb0-4f3c-8cf1-4080bcf04dab"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training Scores:\n",
            "Label (armed_assault) score: 0.995968\n",
            "Label (arrest) score: 0.999888\n",
            "Label (bombing) score: 0.996192\n",
            "Label (infrastructure) score: 0.996528\n",
            "Label (surrender) score: 1.000000\n",
            "Label (seizure) score: 0.985887\n",
            "Label (abduction) score: 1.000000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# How is the model performing of different labels\n",
        "\n",
        "compare = preds_df_test_lgbm == y_test.reset_index(drop=True)\n",
        "\n",
        "print(\"Testing Scores:\")\n",
        "for i in range(compare.shape[1]):\n",
        "  print(f\"Label ({compare.columns[i]}) score: {(compare.iloc[:, i].sum()) / compare.shape[0]:.6f}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "buh3_SHD3eSL",
        "outputId": "510070f4-1137-4050-db84-28ca5752bbd9"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Testing Scores:\n",
            "Label (armed_assault) score: 0.966767\n",
            "Label (arrest) score: 0.986908\n",
            "Label (bombing) score: 0.966767\n",
            "Label (infrastructure) score: 0.958711\n",
            "Label (surrender) score: 0.998993\n",
            "Label (seizure) score: 0.939577\n",
            "Label (abduction) score: 0.984894\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Balanced Accuracy\n",
        "from sklearn.metrics import balanced_accuracy_score\n",
        "\n",
        "print(\"Balanced Accuracy Scores:\")\n",
        "for i in range(y_test.shape[1]):\n",
        "  y_true = y_test.iloc[:, i]\n",
        "  y_pred = preds_df_test_lgbm.iloc[:, i]\n",
        "\n",
        "  print(f\"Label ({y_test.columns[i]}) score: {balanced_accuracy_score(y_true, y_pred):.6f}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DnTsNKQmcV8K",
        "outputId": "4b24b4d2-1df8-4af7-a1f2-7be3cd5f8ee0"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Balanced Accuracy Scores:\n",
            "Label (armed_assault) score: 0.964877\n",
            "Label (arrest) score: 0.985989\n",
            "Label (bombing) score: 0.937153\n",
            "Label (infrastructure) score: 0.893064\n",
            "Label (surrender) score: 0.999454\n",
            "Label (seizure) score: 0.919378\n",
            "Label (abduction) score: 0.901189\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IWTFofdonhdR"
      },
      "source": [
        "SLC Scores (Predicitng atleast one event from the summary correctly)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "q60b1WlFnjO5",
        "outputId": "3c9f3012-ce4c-46e5-fc52-87c629409c4a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "LR Train Accuracy: 0.944108422939068\n"
          ]
        }
      ],
      "source": [
        "#LG\n",
        "corrects = (preds_df_train_lr.idxmax(axis=1) == y_train.reset_index(drop=True).idxmax(axis=1)).sum()\n",
        "total = y_train.shape[0]\n",
        "print(f\"LR Train Accuracy: {corrects/total}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zVKgEh2KnjSW",
        "outputId": "85ebdfcd-938f-4718-c31c-5b5e134f57fe"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "LR Test Accuracy: 0.8952668680765358\n"
          ]
        }
      ],
      "source": [
        "corrects = (preds_df_test_lr.idxmax(axis=1) == y_test.reset_index(drop=True).idxmax(axis=1)).sum()\n",
        "total = y_test.shape[0]\n",
        "print(f\"LR Test Accuracy: {corrects/total}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Fgur39iOARYp",
        "outputId": "3244c8c2-a9f2-4c5e-a600-efa3d3e0d434"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "LGBM Train Accuracy: 0.9921594982078853\n"
          ]
        }
      ],
      "source": [
        "#LGBM\n",
        "corrects = (preds_df_train_lgbm.idxmax(axis=1) == y_train.reset_index(drop=True).idxmax(axis=1)).sum()\n",
        "total = y_train.shape[0]\n",
        "print(f\"LGBM Train Accuracy: {corrects/total}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "muOb3ltuARRR",
        "outputId": "e692a537-6a8f-4ca6-9da7-41090ff6aaf4"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "LGBM Test Accuracy: 0.9224572004028198\n"
          ]
        }
      ],
      "source": [
        "corrects = (preds_df_test_lgbm.idxmax(axis=1) == y_test.reset_index(drop=True).idxmax(axis=1)).sum()\n",
        "total = y_test.shape[0]\n",
        "print(f\"LGBM Test Accuracy: {corrects/total}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "id": "_x0yTgRgOfti",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 395
        },
        "outputId": "a2e96648-fc44-4516-f4d6-5b9116715db5"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   armed_assault  arrest  bombing  infrastructure  surrender  seizure  \\\n",
              "0              1       0        0               0          0        0   \n",
              "1              0       1        0               0          0        0   \n",
              "2              1       0        0               0          0        1   \n",
              "3              1       0        0               0          0        0   \n",
              "4              0       1        0               0          0        0   \n",
              "\n",
              "   abduction  \n",
              "0          0  \n",
              "1          0  \n",
              "2          0  \n",
              "3          1  \n",
              "4          0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-d27bf6a8-2706-4831-ad2c-3113863e4228\" 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>armed_assault</th>\n",
              "      <th>arrest</th>\n",
              "      <th>bombing</th>\n",
              "      <th>infrastructure</th>\n",
              "      <th>surrender</th>\n",
              "      <th>seizure</th>\n",
              "      <th>abduction</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d27bf6a8-2706-4831-ad2c-3113863e4228')\"\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-d27bf6a8-2706-4831-ad2c-3113863e4228 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-d27bf6a8-2706-4831-ad2c-3113863e4228');\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-53c3fbc1-6cf6-4fd4-af63-5a39802278e9\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-53c3fbc1-6cf6-4fd4-af63-5a39802278e9')\"\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-53c3fbc1-6cf6-4fd4-af63-5a39802278e9 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"display(preds_df_test_lgbm\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"armed_assault\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"arrest\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"bombing\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"infrastructure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"surrender\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"seizure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"abduction\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "      armed_assault  arrest  bombing  infrastructure  surrender  seizure  \\\n",
              "7849              1       0        0               0          0        0   \n",
              "8320              0       1        0               0          0        0   \n",
              "7727              1       0        0               0          0        1   \n",
              "1253              1       0        0               0          0        0   \n",
              "2067              0       1        0               0          0        0   \n",
              "\n",
              "      abduction  \n",
              "7849          0  \n",
              "8320          0  \n",
              "7727          0  \n",
              "1253          0  \n",
              "2067          0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-245655f9-3acc-4ffb-8e12-629850623fc1\" 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>armed_assault</th>\n",
              "      <th>arrest</th>\n",
              "      <th>bombing</th>\n",
              "      <th>infrastructure</th>\n",
              "      <th>surrender</th>\n",
              "      <th>seizure</th>\n",
              "      <th>abduction</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>7849</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8320</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7727</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1253</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2067</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-245655f9-3acc-4ffb-8e12-629850623fc1')\"\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-245655f9-3acc-4ffb-8e12-629850623fc1 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-245655f9-3acc-4ffb-8e12-629850623fc1');\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-9f184fde-95cf-497d-8297-dbde3f97102b\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-9f184fde-95cf-497d-8297-dbde3f97102b')\"\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-9f184fde-95cf-497d-8297-dbde3f97102b button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"display(preds_df_test_lgbm\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"armed_assault\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"arrest\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"bombing\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"infrastructure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"surrender\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"seizure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"abduction\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "display(preds_df_test_lgbm.head(), y_test.head())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xNWiHFsENJ2v"
      },
      "source": [
        "# Testing with real samples"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "id": "pxkP4PIDL9by"
      },
      "outputs": [],
      "source": [
        "real_test = [\"On January 5, at least three Special Operations Group (SOG) jawans (personnel) were injured when an Improvised Explosive Device (IED), suspected to have been planted by the Communist Party of India (CPI-Maoist), exploded during a combing operation in the Badepanga forests bordering Boudh-Kandhamal in the Boudh District of Odisha, reports The New Indian Express.\",\n",
        "             \"A former Communist Party of India-Maoist (CPI-Maoist) cadre, identified as Pujari Ramudu alias Bheemanna (59), was found brutally beaten to death near RS Pendakal railway station in Kurnool District of Andhra Pradesh on January 6, reports jantaserishta.com. Pujari, a resident of RS Pendakal village, is also known to be the brother of Yuvajana Sramika Rythu Congress Party (YSRC) women's wing president and Member of the Legislative Council (MLC) Pothula Sunita. He was associated with the Maoist gang for 30 years. He later surrendered before the police in 1991 and started leading a normal life. On January 6, some unknown people attacked Ramudu with stones, due to which he died. After the incident, the attackers fled from the spot\",\n",
        "             \"On January 6, a 25-year-old school teacher, identified as Ramlal Nureti, was arrested from Karekatta village under Madanwada Police Station limits in Mohla-Manpur-Ambagarh Chowki District of Chhattisgarh for allegedly being a Communist Party of India-Maoist (CPI-Maoist) supporter, reports Devdiscourse. Angered by the arrest, a group of villagers, including schoolchildren, have launched a protest in front of Sitagaon Police Station, demanding his release. Ramlal was allegedly involved in putting up Maoist banners and posters in the area in September last year, the Police said. On September 15, 2023, the police recovered posters and banners from the Madanwada area, where Maoists appealed to observe the 19th anniversary of the outlawed movement, the Police added.\",\n",
        "             \"The Communist Party of India-Maoist (CPI-Maoist) cadres targeted a construction site and set ablaze at least three machines involved in soil cutting at Bariatu in Chandwa in the Latehar District of Jharkhand on January 6, reports The Avenue Mail. Kashyap Construction, responsible for the third railway line project in Bariatu, faced disruption as Poclain, JCB, and mixer machines were burned by the Maoists. Following the arson, at least seven rounds of firing were also reported, creating an atmosphere of fear and panic in the area.\",\n",
        "             \"Vehicles engaged in bridge construction work on the Manak River in Kurumdari village in Simaria in Chatra District of Jharkhand were set on fire by cadres of the Communist Party of India-Maoist (CPI-Maoist) on January 6, reports The Avenue Mail.\"\n",
        "             ]\n",
        "real_cleaned = [clean_text(text) for text in real_test]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "id": "ShVLgNAwAe_q",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "a309c7ff-f348-4c80-ae27-3790325acbf8"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   armed_assault  arrest  bombing  infrastructure  surrender  seizure  \\\n",
              "0              0       0        1               0          0        0   \n",
              "1              0       0        0               0          1        0   \n",
              "2              0       1        0               0          0        1   \n",
              "3              0       0        0               1          0        0   \n",
              "4              0       0        0               1          0        0   \n",
              "\n",
              "   abduction  \n",
              "0          0  \n",
              "1          0  \n",
              "2          0  \n",
              "3          0  \n",
              "4          0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-38ad1acd-42ed-44bd-b0af-2995bfeaab6d\" 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>armed_assault</th>\n",
              "      <th>arrest</th>\n",
              "      <th>bombing</th>\n",
              "      <th>infrastructure</th>\n",
              "      <th>surrender</th>\n",
              "      <th>seizure</th>\n",
              "      <th>abduction</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</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-38ad1acd-42ed-44bd-b0af-2995bfeaab6d')\"\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-38ad1acd-42ed-44bd-b0af-2995bfeaab6d 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-38ad1acd-42ed-44bd-b0af-2995bfeaab6d');\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-1286f582-4e9d-48dd-a8f7-2ca598c4e641\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-1286f582-4e9d-48dd-a8f7-2ca598c4e641')\"\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-1286f582-4e9d-48dd-a8f7-2ca598c4e641 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"pd\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"armed_assault\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"arrest\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"bombing\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"infrastructure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"surrender\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"seizure\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"abduction\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 28
        }
      ],
      "source": [
        "real_preds = lgbm.predict(real_cleaned)\n",
        "pd.DataFrame(data=real_preds, columns = y.columns)"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}