logistic_regression_BinaryClassification.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyPbv5KGN9mUaW/FQ0LTX2Su",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
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      "source": [
        "<a href=\"https://colab.research.google.com/github/samarthm04/ComputerVision_0_to_Hero/blob/main/logistic_regression_BinaryClassification.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Logistic Regression\n",
        "Quite useful in classification problems\n"
      ],
      "metadata": {
        "id": "bkJyGN7YuZgF"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Types of Classification\n",
        "1.   Binary Classification\n",
        "2.   Multiclass Classification\n",
        "\n"
      ],
      "metadata": {
        "id": "FDpkfuSHuxBt"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        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)"
      ],
      "metadata": {
        "id": "q0rKNNIxvvnN"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 1) Binary Classification"
      ],
      "metadata": {
        "id": "xTdQ73PpFpTi"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "ynjmtj4dt8o_"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df=pd.read_csv(\"insurance_data.csv\")"
      ],
      "metadata": {
        "id": "Ch24fgGjxAXs"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
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        "colab": {
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        "id": "wTpcsqkaxOnS",
        "outputId": "f26f5913-6f33-47a7-fbba-c1c0ff3b0d39"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   age  bought_insurance\n",
              "0   22                 0\n",
              "1   25                 0\n",
              "2   47                 1\n",
              "3   52                 0\n",
              "4   46                 1"
            ],
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 27,\n  \"fields\": [\n    {\n      \"column\": \"age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 15,\n        \"min\": 18,\n        \"max\": 62,\n        \"num_unique_values\": 24,\n        \"samples\": [\n          62,\n          19,\n          22\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"bought_insurance\",\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}"
            }
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.scatter(df['age'],df['bought_insurance'],marker='*', color='green')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 448
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        "id": "cc3Y_Nz4xQ_J",
        "outputId": "1f76e5e3-3ba8-45ec-e766-2d7d2e9eef72"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.collections.PathCollection at 0x7dd0219b32b0>"
            ]
          },
          "metadata": {},
          "execution_count": 9
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Mjk_xGvryGMU",
        "outputId": "94354ba2-ef7a-4acc-cb45-383eeaeedd33"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(27, 2)"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split"
      ],
      "metadata": {
        "id": "FHl8dC7nyYY4"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train, X_test, y_train, y_test =train_test_split(df[['age']],df['bought_insurance'],train_size=0.9)"
      ],
      "metadata": {
        "id": "h-aktlCvzMHt"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.linear_model import LogisticRegression"
      ],
      "metadata": {
        "id": "_OHTfk23Ew4N"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model=LogisticRegression()"
      ],
      "metadata": {
        "id": "j1UCkxWOFa3S"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.fit(X_train,y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 80
        },
        "id": "_sRg7ZcaFi8l",
        "outputId": "c475d2f9-9fab-4672-dda9-41cf018deef0"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "LogisticRegression()"
            ],
            "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>LogisticRegression()</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\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&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><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression()</pre></div> </div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.predict(X_test)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yTzxaEsKFmRT",
        "outputId": "3bad1763-2c74-456d-9338-a1356a0c5f74"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1, 1, 1])"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.score(X_test,y_test)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Em67Kv6CFl6V",
        "outputId": "30dce521-d06b-4831-d2bb-a87f4b839394"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1.0"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    }
  ]
}