Crop_Prediction_using_ML.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# **Crop Prediction using Machine Learning**"
      ],
      "metadata": {
        "id": "WUQtHDhKCCoX"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Dataset Link:**  https://www.kaggle.com/code/theeyeschico/crop-analysis-and-prediction/data?select=Crop_recommendation.csv"
      ],
      "metadata": {
        "id": "4meavZEibY-J"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "* This Algorithm takes the nutrients present in the sample of soil, like amount of Nitrogen, Phosphorus and Potassium present in it.\n",
        "\n",
        "* It also accounts for the pH value of the soil, the average rainfall and Humidity of the soil as well.\n",
        "\n",
        "* After having all these information the model predicts which crop will be the best to grow on that particular area, and increase the yield.\n",
        "\n",
        "* Farming and Agriculture is the leading sector and lot of farmers incur losses on their yields due to a lot of reasons and lack of knowledge, this model will solve those problems and help the farmers to have a great yield."
      ],
      "metadata": {
        "id": "6rW-et84aVkS"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "▪️The Algorithms used are Logistic Regression, Random Forest and Decision Tree Algorithm\n",
        "\n",
        "▪️This Algorithm takes the nutrients present in the sample of soil, like amount of Nitrogen, Phosphorus and Potassium present in it.\n",
        "\n",
        "▪️It also accounts for the pH value of the soil, the average rainfall and Humidity of the soil as well.\n",
        "\n",
        "▪️After having all these information the model predicts which crop will be the best to grow on that particular area, and increase the yield.\n",
        "\n",
        "▪️Farming and Agriculture is the leading sector and lot of farmers incur losses on their yields due to a lot of reasons and lack of knowledge, this model will solve those problems and help the farmers to have a great yield.\n",
        "\n",
        "▪️Once the sample soil is tested and the nutrients are knowns, the model will be good to go.!!"
      ],
      "metadata": {
        "id": "YbRkEFD0d0mu"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Classification Use Case**"
      ],
      "metadata": {
        "id": "Xno8OgoGbtlX"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "MuPdKrDvCBru"
      },
      "outputs": [],
      "source": [
        "# Import required Libraries\n",
        "\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from statsmodels.stats.outliers_influence import variance_inflation_factor\n",
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.tree import DecisionTreeClassifier\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "\n",
        "from sklearn import metrics\n",
        "from sklearn.metrics import accuracy_score,confusion_matrix,precision_score,precision_recall_curve,f1_score,classification_report\n",
        "\n",
        "from sklearn.model_selection import GridSearchCV\n",
        "\n",
        "import warnings\n",
        "from warnings import filterwarnings\n",
        "filterwarnings(\"ignore\")\n",
        "\n",
        "sns.set()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data = pd.read_csv(\"/content/Crop_recommendation.csv\")\n",
        "data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "friNGV1KFunS",
        "outputId": "d8245936-abea-48aa-f3d9-42c619790505"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    N   P   K  temperature   humidity        ph    rainfall label\n",
              "0  90  42  43    20.879744  82.002744  6.502985  202.935536  rice\n",
              "1  85  58  41    21.770462  80.319644  7.038096  226.655537  rice\n",
              "2  60  55  44    23.004459  82.320763  7.840207  263.964248  rice\n",
              "3  74  35  40    26.491096  80.158363  6.980401  242.864034  rice\n",
              "4  78  42  42    20.130175  81.604873  7.628473  262.717340  rice"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1fc1fcff-215d-4c4d-bd24-d7f7a332d6cb\">\n",
              "    <div 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>N</th>\n",
              "      <th>P</th>\n",
              "      <th>K</th>\n",
              "      <th>temperature</th>\n",
              "      <th>humidity</th>\n",
              "      <th>ph</th>\n",
              "      <th>rainfall</th>\n",
              "      <th>label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>90</td>\n",
              "      <td>42</td>\n",
              "      <td>43</td>\n",
              "      <td>20.879744</td>\n",
              "      <td>82.002744</td>\n",
              "      <td>6.502985</td>\n",
              "      <td>202.935536</td>\n",
              "      <td>rice</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>85</td>\n",
              "      <td>58</td>\n",
              "      <td>41</td>\n",
              "      <td>21.770462</td>\n",
              "      <td>80.319644</td>\n",
              "      <td>7.038096</td>\n",
              "      <td>226.655537</td>\n",
              "      <td>rice</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>60</td>\n",
              "      <td>55</td>\n",
              "      <td>44</td>\n",
              "      <td>23.004459</td>\n",
              "      <td>82.320763</td>\n",
              "      <td>7.840207</td>\n",
              "      <td>263.964248</td>\n",
              "      <td>rice</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>74</td>\n",
              "      <td>35</td>\n",
              "      <td>40</td>\n",
              "      <td>26.491096</td>\n",
              "      <td>80.158363</td>\n",
              "      <td>6.980401</td>\n",
              "      <td>242.864034</td>\n",
              "      <td>rice</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>78</td>\n",
              "      <td>42</td>\n",
              "      <td>42</td>\n",
              "      <td>20.130175</td>\n",
              "      <td>81.604873</td>\n",
              "      <td>7.628473</td>\n",
              "      <td>262.717340</td>\n",
              "      <td>rice</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1fc1fcff-215d-4c4d-bd24-d7f7a332d6cb')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-1fc1fcff-215d-4c4d-bd24-d7f7a332d6cb 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-1fc1fcff-215d-4c4d-bd24-d7f7a332d6cb');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R9Ecr5alGBJ0",
        "outputId": "de7ed4a0-16a1-4c02-8fc4-38a50673e659"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(2200, 8)"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "oc9lvwVZGCnj",
        "outputId": "8ed0931b-dfa8-461d-a37b-44eba8bb66ee"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                 N            P            K  temperature     humidity  \\\n",
              "count  2200.000000  2200.000000  2200.000000  2200.000000  2200.000000   \n",
              "mean     50.551818    53.362727    48.149091    25.616244    71.481779   \n",
              "std      36.917334    32.985883    50.647931     5.063749    22.263812   \n",
              "min       0.000000     5.000000     5.000000     8.825675    14.258040   \n",
              "25%      21.000000    28.000000    20.000000    22.769375    60.261953   \n",
              "50%      37.000000    51.000000    32.000000    25.598693    80.473146   \n",
              "75%      84.250000    68.000000    49.000000    28.561654    89.948771   \n",
              "max     140.000000   145.000000   205.000000    43.675493    99.981876   \n",
              "\n",
              "                ph     rainfall  \n",
              "count  2200.000000  2200.000000  \n",
              "mean      6.469480   103.463655  \n",
              "std       0.773938    54.958389  \n",
              "min       3.504752    20.211267  \n",
              "25%       5.971693    64.551686  \n",
              "50%       6.425045    94.867624  \n",
              "75%       6.923643   124.267508  \n",
              "max       9.935091   298.560117  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-7b03d5b6-806f-4fef-9d7b-21471607e4f3\">\n",
              "    <div 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>N</th>\n",
              "      <th>P</th>\n",
              "      <th>K</th>\n",
              "      <th>temperature</th>\n",
              "      <th>humidity</th>\n",
              "      <th>ph</th>\n",
              "      <th>rainfall</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>2200.000000</td>\n",
              "      <td>2200.000000</td>\n",
              "      <td>2200.000000</td>\n",
              "      <td>2200.000000</td>\n",
              "      <td>2200.000000</td>\n",
              "      <td>2200.000000</td>\n",
              "      <td>2200.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>50.551818</td>\n",
              "      <td>53.362727</td>\n",
              "      <td>48.149091</td>\n",
              "      <td>25.616244</td>\n",
              "      <td>71.481779</td>\n",
              "      <td>6.469480</td>\n",
              "      <td>103.463655</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>36.917334</td>\n",
              "      <td>32.985883</td>\n",
              "      <td>50.647931</td>\n",
              "      <td>5.063749</td>\n",
              "      <td>22.263812</td>\n",
              "      <td>0.773938</td>\n",
              "      <td>54.958389</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>8.825675</td>\n",
              "      <td>14.258040</td>\n",
              "      <td>3.504752</td>\n",
              "      <td>20.211267</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>21.000000</td>\n",
              "      <td>28.000000</td>\n",
              "      <td>20.000000</td>\n",
              "      <td>22.769375</td>\n",
              "      <td>60.261953</td>\n",
              "      <td>5.971693</td>\n",
              "      <td>64.551686</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>37.000000</td>\n",
              "      <td>51.000000</td>\n",
              "      <td>32.000000</td>\n",
              "      <td>25.598693</td>\n",
              "      <td>80.473146</td>\n",
              "      <td>6.425045</td>\n",
              "      <td>94.867624</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>84.250000</td>\n",
              "      <td>68.000000</td>\n",
              "      <td>49.000000</td>\n",
              "      <td>28.561654</td>\n",
              "      <td>89.948771</td>\n",
              "      <td>6.923643</td>\n",
              "      <td>124.267508</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>140.000000</td>\n",
              "      <td>145.000000</td>\n",
              "      <td>205.000000</td>\n",
              "      <td>43.675493</td>\n",
              "      <td>99.981876</td>\n",
              "      <td>9.935091</td>\n",
              "      <td>298.560117</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7b03d5b6-806f-4fef-9d7b-21471607e4f3')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-7b03d5b6-806f-4fef-9d7b-21471607e4f3 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-7b03d5b6-806f-4fef-9d7b-21471607e4f3');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "O8LXwGfSGDzT",
        "outputId": "b6acae1e-3ba9-44da-c9c3-1727c4764981"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 2200 entries, 0 to 2199\n",
            "Data columns (total 8 columns):\n",
            " #   Column       Non-Null Count  Dtype  \n",
            "---  ------       --------------  -----  \n",
            " 0   N            2200 non-null   int64  \n",
            " 1   P            2200 non-null   int64  \n",
            " 2   K            2200 non-null   int64  \n",
            " 3   temperature  2200 non-null   float64\n",
            " 4   humidity     2200 non-null   float64\n",
            " 5   ph           2200 non-null   float64\n",
            " 6   rainfall     2200 non-null   float64\n",
            " 7   label        2200 non-null   object \n",
            "dtypes: float64(4), int64(3), object(1)\n",
            "memory usage: 137.6+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NW0D-R01GFbH",
        "outputId": "b62e2e35-f0c9-42a5-a719-e49d92fba3a9"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "N              0\n",
              "P              0\n",
              "K              0\n",
              "temperature    0\n",
              "humidity       0\n",
              "ph             0\n",
              "rainfall       0\n",
              "label          0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**EDA**"
      ],
      "metadata": {
        "id": "gkn5fiLfGSX-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data[\"label\"].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "49O44YTeGo0F",
        "outputId": "36913ccf-a35e-4c49-9cc4-e43bd0f1c2b6"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['rice', 'maize', 'chickpea', 'kidneybeans', 'pigeonpeas',\n",
              "       'mothbeans', 'mungbean', 'blackgram', 'lentil', 'pomegranate',\n",
              "       'banana', 'mango', 'grapes', 'watermelon', 'muskmelon', 'apple',\n",
              "       'orange', 'papaya', 'coconut', 'cotton', 'jute', 'coffee'],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(25,15))\n",
        "plotnumber = 1\n",
        "\n",
        "for column in data.iloc[:,0:-1]:\n",
        "  if plotnumber <= 8:\n",
        "    ax = plt.subplot(2,4,plotnumber)\n",
        "    sns.distplot(data[column])\n",
        "    plt.xlabel(column)\n",
        "  plotnumber+=1\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "2z6wQOY9IC7S",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 751
        },
        "outputId": "90fdd3ea-a73b-4005-8027-fc74187b7dd7"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1800x1080 with 7 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data[\"label\"].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lZaQNOm1RxUv",
        "outputId": "c909dfa7-7155-4c8b-acf7-8ed65b853c22"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "rice           100\n",
              "maize          100\n",
              "jute           100\n",
              "cotton         100\n",
              "coconut        100\n",
              "papaya         100\n",
              "orange         100\n",
              "apple          100\n",
              "muskmelon      100\n",
              "watermelon     100\n",
              "grapes         100\n",
              "mango          100\n",
              "banana         100\n",
              "pomegranate    100\n",
              "lentil         100\n",
              "blackgram      100\n",
              "mungbean       100\n",
              "mothbeans      100\n",
              "pigeonpeas     100\n",
              "kidneybeans    100\n",
              "chickpea       100\n",
              "coffee         100\n",
              "Name: label, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "class_labels = ['rice', 'maize', 'chickpea', 'kidneybeans', 'pigeonpeas',\n",
        "       'mothbeans', 'mungbean', 'blackgram', 'lentil', 'pomegranate',\n",
        "       'banana', 'mango', 'grapes', 'watermelon', 'muskmelon', 'apple',\n",
        "       'orange', 'papaya', 'coconut', 'cotton', 'jute', 'coffee']\n",
        "plt.figure(figsize = (10,10))\n",
        "data[\"label\"].value_counts().plot(kind  = \"pie\",autopct = \"%0.2f%%\",labels = class_labels)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 575
        },
        "id": "QEMFELWGEv63",
        "outputId": "e742f5d5-3369-4efa-e267-7d642fbaa5ce"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig,ax = plt.subplots(figsize = (18,8))\n",
        "sns.boxplot(data=data,width = 0.5,fliersize = 3,ax=ax)"
      ],
      "metadata": {
        "id": "pQWXowd1DoBK",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 502
        },
        "outputId": "0e685caf-bf50-43ac-8732-eccc8157c3ec"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:>"
            ]
          },
          "metadata": {},
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1296x576 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "Fx_gNVuLbkcv"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Handling Outliers**"
      ],
      "metadata": {
        "id": "_cnjzrfZbk0f"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df2 = data.copy()"
      ],
      "metadata": {
        "id": "P07Ssl4hUsz1"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def outlier_remove_IQR(column):\n",
        " percentile_25 = df2[column].quantile(.25)\n",
        " percentile_75 = df2[column].quantile(.72)\n",
        " IQR = percentile_75 - percentile_25\n",
        " upper_lmt = percentile_75 + 1.5*IQR\n",
        " lower_lmt = percentile_25 - 1.5*IQR\n",
        " print('25 Percentile : ',percentile_25)\n",
        " print('75 percentile : ',percentile_75)\n",
        " print('Upper limit is : ',upper_lmt)\n",
        " print('Lower limit is : ',lower_lmt)\n",
        " print('IQR is : ',IQR)\n",
        " df2[column] = np.where(df2[column]>upper_lmt,upper_lmt,np.where(df2[column]<lower_lmt,lower_lmt,df2[column]))\n",
        " #return df2[df2[column] > upper_lmt]\n",
        " #return df2[df2[column]<lower_lmt]"
      ],
      "metadata": {
        "id": "QuK9gQdmS_ck"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def comparison_plot(data,df2,column):\n",
        " # Comparing data of before and after outlier handling\n",
        " plt.figure(figsize=(15,10))\n",
        " plt.subplot(2,2,1)\n",
        " sns.distplot(data[column])\n",
        " plt.subplot(2,2,2)\n",
        " sns.boxplot(data[column])\n",
        " plt.subplot(2,2,3)\n",
        " sns.distplot(df2[column])\n",
        " plt.subplot(2,2,4)\n",
        " sns.boxplot(df2[column])\n",
        " plt.show()"
      ],
      "metadata": {
        "id": "BQd2Fre8Yobj"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "outlier_remove_IQR('K')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KNEKFhwbYoXe",
        "outputId": "84d4aed6-e781-455a-f36e-d7cf9eafa73c"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "25 Percentile :  20.0\n",
            "75 percentile :  47.0\n",
            "Upper limit is :  87.5\n",
            "Lower limit is :  -20.5\n",
            "IQR is :  27.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "comparison_plot(data,df2,'K')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 611
        },
        "id": "U-qSo2qsYrRx",
        "outputId": "b0c9c7e5-6907-4ed0-c998-e5619cce8401"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x720 with 4 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "outlier_remove_IQR('rainfall')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hfQSGXnfYr5W",
        "outputId": "e0e6c63d-9508-4a57-f0e9-ec47ecaea290"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "25 Percentile :  64.55168599999999\n",
            "75 percentile :  117.853457108\n",
            "Upper limit is :  197.80611377000002\n",
            "Lower limit is :  -15.40097066200002\n",
            "IQR is :  53.30177110800001\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "comparison_plot(data,df2,'rainfall')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 611
        },
        "id": "9AdCt4LPYr2H",
        "outputId": "6e7feef9-e5a4-4c3e-ff34-337b76591767"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x720 with 4 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig,ax = plt.subplots(figsize = (18,8))\n",
        "sns.boxplot(data=df2,width = 0.5,fliersize = 3,ax=ax)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 502
        },
        "id": "eZEwtNa9cG5U",
        "outputId": "4b2d9666-a750-4efd-9dfc-3c96a994e8cf"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:>"
            ]
          },
          "metadata": {},
          "execution_count": 19
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1296x576 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# constructing a heatmap to understand the correlation\n",
        "\n",
        "plt.figure(figsize=(10,7))\n",
        "sns.heatmap(df2.corr(), cmap='Blues',annot = True)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 435
        },
        "id": "2kUlGiyGa7Wz",
        "outputId": "ae8c0d24-ae62-4d0c-c404-c7baee2cf92d"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x504 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,6))\n",
        "sns.barplot(y = 'K', x = 'label', data=df2, palette = 'husl')\n",
        "plt.xticks(rotation = 90)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "id": "9fuXKj9DcysZ",
        "outputId": "e3a5b69c-9c0a-42cd-eaaf-980e83632a2f"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,6))\n",
        "sns.barplot(y = 'N', x = 'label', data=df2, palette = 'husl')\n",
        "plt.xticks(rotation = 90)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "id": "TtJ1sAocc6z6",
        "outputId": "8ead2336-9814-439e-bb89-a16f5eafdcde"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,6))\n",
        "sns.barplot(y = 'P', x = 'label', data=df2, palette = 'husl')\n",
        "plt.xticks(rotation = 90)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "id": "DtOPMig3c9_N",
        "outputId": "25b66b1a-4f1b-4483-e250-e1b5e248154a"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,6))\n",
        "sns.barplot(y = 'humidity', x = 'label', data=df2, palette = 'husl')\n",
        "plt.xticks(rotation = 90)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 462
        },
        "id": "uGdZ5YGRdCsQ",
        "outputId": "29b263e6-320d-457f-dd6a-abc178d04f61"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "o-fbuhtfb8qt",
        "outputId": "6306fc21-d206-4883-a10c-b685b21a3e3d"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    N   P     K  temperature   humidity        ph    rainfall label\n",
              "0  90  42  43.0    20.879744  82.002744  6.502985  197.806114  rice\n",
              "1  85  58  41.0    21.770462  80.319644  7.038096  197.806114  rice\n",
              "2  60  55  44.0    23.004459  82.320763  7.840207  197.806114  rice\n",
              "3  74  35  40.0    26.491096  80.158363  6.980401  197.806114  rice\n",
              "4  78  42  42.0    20.130175  81.604873  7.628473  197.806114  rice"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-eae22925-1fd8-45f2-8c0e-bd9d1fa82d2b\">\n",
              "    <div 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>N</th>\n",
              "      <th>P</th>\n",
              "      <th>K</th>\n",
              "      <th>temperature</th>\n",
              "      <th>humidity</th>\n",
              "      <th>ph</th>\n",
              "      <th>rainfall</th>\n",
              "      <th>label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>90</td>\n",
              "      <td>42</td>\n",
              "      <td>43.0</td>\n",
              "      <td>20.879744</td>\n",
              "      <td>82.002744</td>\n",
              "      <td>6.502985</td>\n",
              "      <td>197.806114</td>\n",
              "      <td>rice</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>85</td>\n",
              "      <td>58</td>\n",
              "      <td>41.0</td>\n",
              "      <td>21.770462</td>\n",
              "      <td>80.319644</td>\n",
              "      <td>7.038096</td>\n",
              "      <td>197.806114</td>\n",
              "      <td>rice</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>60</td>\n",
              "      <td>55</td>\n",
              "      <td>44.0</td>\n",
              "      <td>23.004459</td>\n",
              "      <td>82.320763</td>\n",
              "      <td>7.840207</td>\n",
              "      <td>197.806114</td>\n",
              "      <td>rice</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>74</td>\n",
              "      <td>35</td>\n",
              "      <td>40.0</td>\n",
              "      <td>26.491096</td>\n",
              "      <td>80.158363</td>\n",
              "      <td>6.980401</td>\n",
              "      <td>197.806114</td>\n",
              "      <td>rice</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>78</td>\n",
              "      <td>42</td>\n",
              "      <td>42.0</td>\n",
              "      <td>20.130175</td>\n",
              "      <td>81.604873</td>\n",
              "      <td>7.628473</td>\n",
              "      <td>197.806114</td>\n",
              "      <td>rice</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-eae22925-1fd8-45f2-8c0e-bd9d1fa82d2b')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-eae22925-1fd8-45f2-8c0e-bd9d1fa82d2b 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-eae22925-1fd8-45f2-8c0e-bd9d1fa82d2b');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### **Split Independent and Dependent Features**"
      ],
      "metadata": {
        "id": "3F0lo0YMcUp8"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "X = df2.drop(columns = [\"label\"],axis = 1)\n",
        "y = df2[\"label\"]"
      ],
      "metadata": {
        "id": "HemhUViicaMb"
      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "QpOOAYIFcoOB",
        "outputId": "312749f9-159e-45cc-8a78-f3f7037e547a"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    N   P     K  temperature   humidity        ph    rainfall\n",
              "0  90  42  43.0    20.879744  82.002744  6.502985  197.806114\n",
              "1  85  58  41.0    21.770462  80.319644  7.038096  197.806114\n",
              "2  60  55  44.0    23.004459  82.320763  7.840207  197.806114\n",
              "3  74  35  40.0    26.491096  80.158363  6.980401  197.806114\n",
              "4  78  42  42.0    20.130175  81.604873  7.628473  197.806114"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b8f708be-4902-4d53-ba83-ebaca10c7867\">\n",
              "    <div 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>N</th>\n",
              "      <th>P</th>\n",
              "      <th>K</th>\n",
              "      <th>temperature</th>\n",
              "      <th>humidity</th>\n",
              "      <th>ph</th>\n",
              "      <th>rainfall</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>90</td>\n",
              "      <td>42</td>\n",
              "      <td>43.0</td>\n",
              "      <td>20.879744</td>\n",
              "      <td>82.002744</td>\n",
              "      <td>6.502985</td>\n",
              "      <td>197.806114</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>85</td>\n",
              "      <td>58</td>\n",
              "      <td>41.0</td>\n",
              "      <td>21.770462</td>\n",
              "      <td>80.319644</td>\n",
              "      <td>7.038096</td>\n",
              "      <td>197.806114</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>60</td>\n",
              "      <td>55</td>\n",
              "      <td>44.0</td>\n",
              "      <td>23.004459</td>\n",
              "      <td>82.320763</td>\n",
              "      <td>7.840207</td>\n",
              "      <td>197.806114</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>74</td>\n",
              "      <td>35</td>\n",
              "      <td>40.0</td>\n",
              "      <td>26.491096</td>\n",
              "      <td>80.158363</td>\n",
              "      <td>6.980401</td>\n",
              "      <td>197.806114</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>78</td>\n",
              "      <td>42</td>\n",
              "      <td>42.0</td>\n",
              "      <td>20.130175</td>\n",
              "      <td>81.604873</td>\n",
              "      <td>7.628473</td>\n",
              "      <td>197.806114</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b8f708be-4902-4d53-ba83-ebaca10c7867')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-b8f708be-4902-4d53-ba83-ebaca10c7867 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-b8f708be-4902-4d53-ba83-ebaca10c7867');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DeTxpfIdeGE_",
        "outputId": "d803ca6f-b714-492c-8169-63d4106b6e6d"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    rice\n",
              "1    rice\n",
              "2    rice\n",
              "3    rice\n",
              "4    rice\n",
              "Name: label, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### **Feature Scaling**"
      ],
      "metadata": {
        "id": "75Qh4zLoeTAr"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "scaler = StandardScaler()\n",
        "X_scaled = scaler.fit_transform(X)"
      ],
      "metadata": {
        "id": "6Ko47xqzeJFs"
      },
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_scaled"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Dx8QFwwoegkv",
        "outputId": "0c2bb8ed-31ad-4b0c-91e5-1a930becd01e"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 1.0687974 , -0.34455075,  0.22642508, ...,  0.47266646,\n",
              "         0.04330173,  1.95864019],\n",
              "       [ 0.93332887,  0.14061552,  0.13724943, ...,  0.39705125,\n",
              "         0.73487256,  1.95864019],\n",
              "       [ 0.25598625,  0.04964684,  0.27101291, ...,  0.48695381,\n",
              "         1.77151047,  1.95864019],\n",
              "       ...,\n",
              "       [ 1.82742114, -0.61745677, -0.35321665, ..., -0.19123516,\n",
              "        -0.13812031,  1.46266644],\n",
              "       [ 1.80032743, -0.64777967, -0.17486534, ..., -0.86951801,\n",
              "         0.37390383,  0.52782536],\n",
              "       [ 1.44810927, -1.07230015, -0.35321665, ..., -0.49802006,\n",
              "         0.40109573,  0.80660612]])"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**VIF**"
      ],
      "metadata": {
        "id": "yZQ5lF8jekBj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "variables = X_scaled\n",
        "\n",
        "vif = pd.DataFrame()\n",
        "vif[\"VIF\"] = [variance_inflation_factor(variables,i) for i in range(variables.shape[1])]\n",
        "vif[\"Feature\"] = X.columns"
      ],
      "metadata": {
        "id": "X9fNXyldehr5"
      },
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "vif"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "id": "v5iME8hJfEHp",
        "outputId": "fd0f2f8a-b108-4ce1-ef7e-0435c320d8ff"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        VIF      Feature\n",
              "0  1.128779            N\n",
              "1  1.657128            P\n",
              "2  1.595282            K\n",
              "3  1.081895  temperature\n",
              "4  1.142994     humidity\n",
              "5  1.045545           ph\n",
              "6  1.029943     rainfall"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-aaa9a4ca-14ea-4e3d-8aa0-b009383532fe\">\n",
              "    <div 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>VIF</th>\n",
              "      <th>Feature</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1.128779</td>\n",
              "      <td>N</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1.657128</td>\n",
              "      <td>P</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1.595282</td>\n",
              "      <td>K</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1.081895</td>\n",
              "      <td>temperature</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1.142994</td>\n",
              "      <td>humidity</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>1.045545</td>\n",
              "      <td>ph</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>1.029943</td>\n",
              "      <td>rainfall</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-aaa9a4ca-14ea-4e3d-8aa0-b009383532fe')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-aaa9a4ca-14ea-4e3d-8aa0-b009383532fe 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-aaa9a4ca-14ea-4e3d-8aa0-b009383532fe');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### **Splitting the data for training and Testing**"
      ],
      "metadata": {
        "id": "_rkMPdK_fOiJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#split the data into training and testing\n",
        "\n",
        "X_train,X_test,y_train,y_test = train_test_split(X_scaled,y,test_size=0.2,random_state = 10)"
      ],
      "metadata": {
        "id": "v4CpnWRhfFJW"
      },
      "execution_count": 35,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Shape of X Train: \",X_train.shape)\n",
        "print(\"Shape of X Test: \",X_test.shape)\n",
        "print(\"Shape of y Train: \",y_train.shape)\n",
        "print(\"Shape of y Test: \",y_test.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tGFH2LlHfTjj",
        "outputId": "b03a5202-d867-4ec5-f7da-68d096e0cee6"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Shape of X Train:  (1760, 7)\n",
            "Shape of X Test:  (440, 7)\n",
            "Shape of y Train:  (1760,)\n",
            "Shape of y Test:  (440,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Logistic Regression**"
      ],
      "metadata": {
        "id": "A_7J-dETgnTS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "logmodel = LogisticRegression()\n",
        "logmodel.fit(X_train,y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_hc5CnDygNbJ",
        "outputId": "524fe440-6db0-4d5d-aec4-d9343e3e96aa"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "LogisticRegression()"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred = logmodel.predict(X_test)"
      ],
      "metadata": {
        "id": "ApSnYHTggmbv"
      },
      "execution_count": 46,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(classification_report(y_test,y_pred))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2-Cv-TVagmYi",
        "outputId": "1be017cd-fdbb-4c71-c4d1-62fe427c3f34"
      },
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "       apple       1.00      1.00      1.00        18\n",
            "      banana       1.00      1.00      1.00        18\n",
            "   blackgram       0.96      0.96      0.96        23\n",
            "    chickpea       1.00      1.00      1.00        15\n",
            "     coconut       1.00      1.00      1.00        24\n",
            "      coffee       1.00      1.00      1.00        24\n",
            "      cotton       1.00      1.00      1.00        27\n",
            "      grapes       1.00      1.00      1.00        15\n",
            "        jute       0.83      0.79      0.81        19\n",
            " kidneybeans       0.96      1.00      0.98        22\n",
            "      lentil       0.97      0.97      0.97        30\n",
            "       maize       1.00      1.00      1.00        22\n",
            "       mango       0.95      1.00      0.98        21\n",
            "   mothbeans       0.94      0.83      0.88        18\n",
            "    mungbean       1.00      1.00      1.00        16\n",
            "   muskmelon       1.00      1.00      1.00        17\n",
            "      orange       1.00      1.00      1.00        18\n",
            "      papaya       1.00      0.94      0.97        18\n",
            "  pigeonpeas       0.88      0.88      0.88        16\n",
            " pomegranate       1.00      1.00      1.00        18\n",
            "        rice       0.82      0.88      0.85        26\n",
            "  watermelon       1.00      1.00      1.00        15\n",
            "\n",
            "    accuracy                           0.97       440\n",
            "   macro avg       0.97      0.97      0.97       440\n",
            "weighted avg       0.97      0.97      0.97       440\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "Z30XdyTtikaD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**DecisionTree Algorithm**"
      ],
      "metadata": {
        "id": "1fMupcEQioW_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "deccls = DecisionTreeClassifier()\n",
        "deccls.fit(X_train,y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ko6F-3RHitE5",
        "outputId": "4d77bac2-253f-4e15-c853-4cefddcf59e8"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DecisionTreeClassifier()"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred = deccls.predict(X_test)"
      ],
      "metadata": {
        "id": "dg4ItBtdjJ7r"
      },
      "execution_count": 52,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(classification_report(y_test,y_pred))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g6v1yjTIjUjB",
        "outputId": "805ad41d-b164-458b-fa5b-fb0d7818bc75"
      },
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "       apple       1.00      1.00      1.00        18\n",
            "      banana       1.00      1.00      1.00        18\n",
            "   blackgram       1.00      1.00      1.00        23\n",
            "    chickpea       1.00      1.00      1.00        15\n",
            "     coconut       1.00      1.00      1.00        24\n",
            "      coffee       1.00      1.00      1.00        24\n",
            "      cotton       1.00      0.96      0.98        27\n",
            "      grapes       1.00      1.00      1.00        15\n",
            "        jute       1.00      0.68      0.81        19\n",
            " kidneybeans       1.00      1.00      1.00        22\n",
            "      lentil       1.00      1.00      1.00        30\n",
            "       maize       0.96      1.00      0.98        22\n",
            "       mango       1.00      1.00      1.00        21\n",
            "   mothbeans       1.00      1.00      1.00        18\n",
            "    mungbean       1.00      1.00      1.00        16\n",
            "   muskmelon       1.00      1.00      1.00        17\n",
            "      orange       1.00      1.00      1.00        18\n",
            "      papaya       1.00      1.00      1.00        18\n",
            "  pigeonpeas       1.00      1.00      1.00        16\n",
            " pomegranate       1.00      1.00      1.00        18\n",
            "        rice       0.81      1.00      0.90        26\n",
            "  watermelon       1.00      1.00      1.00        15\n",
            "\n",
            "    accuracy                           0.98       440\n",
            "   macro avg       0.99      0.98      0.98       440\n",
            "weighted avg       0.99      0.98      0.98       440\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "hq-TcMhQjg2K"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**RandomForest Classifier**"
      ],
      "metadata": {
        "id": "VV-9KZ1PjkwK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "rfcls = RandomForestClassifier()\n",
        "rfcls.fit(X_train,y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VMzxihWmjnyB",
        "outputId": "98116321-f35c-4a56-8bda-99893fe73ff0"
      },
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "RandomForestClassifier()"
            ]
          },
          "metadata": {},
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred = rfcls.predict(X_test)"
      ],
      "metadata": {
        "id": "okYceEozjvJZ"
      },
      "execution_count": 55,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(classification_report(y_test,y_pred))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "b7XQjjBIjznG",
        "outputId": "db93d168-f80f-4193-ce1c-e89759469405"
      },
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "       apple       1.00      1.00      1.00        18\n",
            "      banana       1.00      1.00      1.00        18\n",
            "   blackgram       1.00      1.00      1.00        23\n",
            "    chickpea       1.00      1.00      1.00        15\n",
            "     coconut       1.00      1.00      1.00        24\n",
            "      coffee       1.00      1.00      1.00        24\n",
            "      cotton       1.00      1.00      1.00        27\n",
            "      grapes       1.00      1.00      1.00        15\n",
            "        jute       1.00      0.95      0.97        19\n",
            " kidneybeans       1.00      1.00      1.00        22\n",
            "      lentil       1.00      1.00      1.00        30\n",
            "       maize       1.00      1.00      1.00        22\n",
            "       mango       1.00      1.00      1.00        21\n",
            "   mothbeans       1.00      1.00      1.00        18\n",
            "    mungbean       1.00      1.00      1.00        16\n",
            "   muskmelon       1.00      1.00      1.00        17\n",
            "      orange       1.00      1.00      1.00        18\n",
            "      papaya       1.00      1.00      1.00        18\n",
            "  pigeonpeas       1.00      1.00      1.00        16\n",
            " pomegranate       1.00      1.00      1.00        18\n",
            "        rice       0.96      1.00      0.98        26\n",
            "  watermelon       1.00      1.00      1.00        15\n",
            "\n",
            "    accuracy                           1.00       440\n",
            "   macro avg       1.00      1.00      1.00       440\n",
            "weighted avg       1.00      1.00      1.00       440\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "bRE8y4BdllyX"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}