Logistic__Regression.ipynb

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        "<a href=\"https://colab.research.google.com/github/RChandana/AI/blob/main/Logistic__Regression.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.metrics import accuracy_score\n",
        "classifier = LogisticRegression()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataframe = pd.read_csv(\"/content/ex1.txt\")\n",
        "X = dataframe.iloc[:, :-1].values\n",
        "y = dataframe.iloc[:, -1].values\n",
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)\n",
        "classifier.fit(X_train, y_train)\n",
        "test1 = classifier.predict([[55, 80]])\n",
        "test1"
      ],
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        "id": "tozsrf5VDHRo",
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      "execution_count": null,
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              "array([1])"
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          "execution_count": 2
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      "cell_type": "code",
      "source": [
        "accuracyTestSet = classifier.score(X_test, y_test)\n",
        "accuracyTrainSet = classifier.score(X_train, y_train)\n",
        "\n",
        "print(\"\\nThe accuracy of the 1st training dataset is: \", accuracyTrainSet)\n",
        "print(\"\\nThe accuracy of the 1st test dataset is: \", accuracyTestSet)"
      ],
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      "outputs": [
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          "text": [
            "\n",
            "The accuracy of the 1st training dataset is:  0.9130434782608695\n",
            "\n",
            "The accuracy of the 1st test dataset is:  0.9\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv(\"/content/ex2.txt\")\n",
        "X = df.iloc[:, :-1].values\n",
        "y = df.iloc[:, -1].values\n",
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)\n",
        "classifier.fit(X_train, y_train)\n",
        "accuracyTestSet = classifier.score(X_test, y_test)\n",
        "accuracyTrainSet = classifier.score(X_train, y_train)\n",
        "\n",
        "print(\"\\nThe accuracy of the 2nd training dataset is: \", accuracyTrainSet)\n",
        "print(\"\\nThe accuracy of the 2nd test dataset is: \", accuracyTestSet)"
      ],
      "metadata": {
        "colab": {
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      "execution_count": null,
      "outputs": [
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          "text": [
            "\n",
            "The accuracy of the 2nd training dataset is:  0.6049382716049383\n",
            "\n",
            "The accuracy of the 2nd test dataset is:  0.4166666666666667\n"
          ]
        }
      ]
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