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      "gpuType": "T4"
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    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "hs8DZR1MOVhB"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "data = pd.read_csv(\"/content/LoanApprovalPrediction.csv\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.head(5)"
      ],
      "metadata": {
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          "height": 206
        },
        "id": "bUg3H-eqOwxi",
        "outputId": "c95d4c03-8943-4315-c85f-79e82e742105"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Loan_ID Gender Married  Dependents     Education Self_Employed  \\\n",
              "0  LP001002   Male      No         0.0      Graduate            No   \n",
              "1  LP001003   Male     Yes         1.0      Graduate            No   \n",
              "2  LP001005   Male     Yes         0.0      Graduate           Yes   \n",
              "3  LP001006   Male     Yes         0.0  Not Graduate            No   \n",
              "4  LP001008   Male      No         0.0      Graduate            No   \n",
              "\n",
              "   ApplicantIncome  CoapplicantIncome  LoanAmount  Loan_Amount_Term  \\\n",
              "0             5849                0.0         NaN             360.0   \n",
              "1             4583             1508.0       128.0             360.0   \n",
              "2             3000                0.0        66.0             360.0   \n",
              "3             2583             2358.0       120.0             360.0   \n",
              "4             6000                0.0       141.0             360.0   \n",
              "\n",
              "   Credit_History Property_Area Loan_Status  \n",
              "0             1.0         Urban           Y  \n",
              "1             1.0         Rural           N  \n",
              "2             1.0         Urban           Y  \n",
              "3             1.0         Urban           Y  \n",
              "4             1.0         Urban           Y  "
            ],
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Loan_ID</th>\n",
              "      <th>Gender</th>\n",
              "      <th>Married</th>\n",
              "      <th>Dependents</th>\n",
              "      <th>Education</th>\n",
              "      <th>Self_Employed</th>\n",
              "      <th>ApplicantIncome</th>\n",
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              "      <th>LoanAmount</th>\n",
              "      <th>Loan_Amount_Term</th>\n",
              "      <th>Credit_History</th>\n",
              "      <th>Property_Area</th>\n",
              "      <th>Loan_Status</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>LP001002</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Graduate</td>\n",
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              "      <td>5849</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "      <td>Y</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>LP001003</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
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              "      <td>1508.0</td>\n",
              "      <td>128.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Rural</td>\n",
              "      <td>N</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>LP001005</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>Yes</td>\n",
              "      <td>3000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>66.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "      <td>Y</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>LP001006</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Not Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>2583</td>\n",
              "      <td>2358.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "      <td>Y</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>LP001008</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>6000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>141.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "data",
              "summary": "{\n  \"name\": \"data\",\n  \"rows\": 598,\n  \"fields\": [\n    {\n      \"column\": \"Loan_ID\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 598,\n        \"samples\": [\n          \"LP001391\",\n          \"LP001945\",\n          \"LP002874\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Gender\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Female\",\n          \"Male\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Married\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Yes\",\n          \"No\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Dependents\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.0077512374183324,\n        \"min\": 0.0,\n        \"max\": 3.0,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          1.0,\n          3.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Education\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Not Graduate\",\n          \"Graduate\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Self_Employed\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Yes\",\n          \"No\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ApplicantIncome\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 5807,\n        \"min\": 150,\n        \"max\": 81000,\n        \"num_unique_values\": 491,\n        \"samples\": [\n          10139,\n          1977\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CoapplicantIncome\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2953.315784678732,\n        \"min\": 0.0,\n        \"max\": 41667.0,\n        \"num_unique_values\": 283,\n        \"samples\": [\n          1840.0,\n          1424.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"LoanAmount\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 82.7041816598101,\n        \"min\": 9.0,\n        \"max\": 650.0,\n        \"num_unique_values\": 199,\n        \"samples\": [\n          102.0,\n          100.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Loan_Amount_Term\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 65.20599440493994,\n        \"min\": 12.0,\n        \"max\": 480.0,\n        \"num_unique_values\": 10,\n        \"samples\": [\n          84.0,\n          120.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Credit_History\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.3638004816130247,\n        \"min\": 0.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0.0,\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Property_Area\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Urban\",\n          \"Rural\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Loan_Status\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"N\",\n          \"Y\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "obj = (data.dtypes == 'object')\n",
        "print(\"Categorical variables:\",len(list(obj[obj].index)))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rlG4j0wUOz_e",
        "outputId": "e89dc6cd-8828-4288-c637-d25ca72b5ae7"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Categorical variables: 7\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.drop(['Loan_ID'],axis=1,inplace=True)"
      ],
      "metadata": {
        "id": "OAFe590PO_qf"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "obj = (data.dtypes == 'object')\n",
        "object_cols = list(obj[obj].index)\n",
        "plt.figure(figsize=(18,36))\n",
        "index = 1\n",
        "\n",
        "for col in object_cols:\n",
        "  y = data[col].value_counts()\n",
        "  plt.subplot(11,4,index)\n",
        "  plt.xticks(rotation=90)\n",
        "  sns.barplot(x=list(y.index), y=y)\n",
        "  index +=1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 592
        },
        "id": "rIt4-xv0PF1z",
        "outputId": "3dac92d2-6e50-4a6c-cbf2-4d13df7f4fc3"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1800x3600 with 6 Axes>"
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            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Import label encoder\n",
        "from sklearn import preprocessing\n",
        "\n",
        "# label_encoder object knows how\n",
        "# to understand word labels.\n",
        "label_encoder = preprocessing.LabelEncoder()\n",
        "obj = (data.dtypes == 'object')\n",
        "for col in list(obj[obj].index):\n",
        "  data[col] = label_encoder.fit_transform(data[col])"
      ],
      "metadata": {
        "id": "pZFdwaiyPTbL"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# To find the number of columns with\n",
        "# datatype==object\n",
        "obj = (data.dtypes == 'object')\n",
        "print(\"Categorical variables:\",len(list(obj[obj].index)))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bZBs8Un8PXp8",
        "outputId": "006e50b8-21f0-4a1c-f997-7072150bf49d"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Categorical variables: 0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,6))\n",
        "\n",
        "sns.heatmap(data.corr(),cmap='BrBG',fmt='.2f',\n",
        "            linewidths=2,annot=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 666
        },
        "id": "iX6cE8ffPetx",
        "outputId": "ba4f6687-58ad-49ca-ba29-bebaba8f0db2"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 8
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.catplot(x=\"Gender\", y=\"Married\",\n",
        "            hue=\"Loan_Status\",\n",
        "            kind=\"bar\",\n",
        "            data=data)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 523
        },
        "id": "f2hVdQopPke0",
        "outputId": "b91afd2e-db15-43c8-b7bf-d925d2f37c89"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x79bd9586e390>"
            ]
          },
          "metadata": {},
          "execution_count": 9
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 595.736x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for col in data.columns:\n",
        "  data[col] = data[col].fillna(data[col].mean())\n",
        "\n",
        "data.isna().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 460
        },
        "id": "R6Kd9EoAPqrD",
        "outputId": "586d6245-6f6e-4684-ffad-bb86c85ca7c2"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Gender               0\n",
              "Married              0\n",
              "Dependents           0\n",
              "Education            0\n",
              "Self_Employed        0\n",
              "ApplicantIncome      0\n",
              "CoapplicantIncome    0\n",
              "LoanAmount           0\n",
              "Loan_Amount_Term     0\n",
              "Credit_History       0\n",
              "Property_Area        0\n",
              "Loan_Status          0\n",
              "dtype: int64"
            ],
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>0</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Gender</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Married</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dependents</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Education</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Self_Employed</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ApplicantIncome</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CoapplicantIncome</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LoanAmount</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Loan_Amount_Term</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Credit_History</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Property_Area</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Loan_Status</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> int64</label>"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "X = data.drop(['Loan_Status'],axis=1)\n",
        "Y = data['Loan_Status']\n",
        "X.shape,Y.shape\n",
        "\n",
        "X_train, X_test, Y_train, Y_test = train_test_split(X, Y,\n",
        "                                                    test_size=0.4,\n",
        "                                                    random_state=1)\n",
        "X_train.shape, X_test.shape, Y_train.shape, Y_test.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pthWzHj8QDGM",
        "outputId": "53961bfc-0b2c-4c76-c608-c673947f7f55"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((358, 11), (240, 11), (358,), (240,))"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.neighbors import KNeighborsClassifier\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.svm import SVC\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "\n",
        "from sklearn import metrics\n",
        "\n",
        "knn = KNeighborsClassifier(n_neighbors=3)\n",
        "rfc = RandomForestClassifier(n_estimators = 7,\n",
        "                             criterion = 'entropy',\n",
        "                             random_state =7)\n",
        "svc = SVC()\n",
        "lc = LogisticRegression()\n",
        "\n",
        "# making predictions on the training set\n",
        "for clf in (rfc, knn, svc,lc):\n",
        "    clf.fit(X_train, Y_train)\n",
        "    Y_pred = clf.predict(X_train)\n",
        "    print(\"Accuracy score of \",\n",
        "          clf.__class__.__name__,\n",
        "          \"=\",100*metrics.accuracy_score(Y_train,\n",
        "                                         Y_pred))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nvJGCGQvQzAq",
        "outputId": "8f0ad92b-ad25-47bf-ef4f-e639f97ca9c6"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy score of  RandomForestClassifier = 98.04469273743017\n",
            "Accuracy score of  KNeighborsClassifier = 78.49162011173185\n",
            "Accuracy score of  SVC = 68.71508379888269\n",
            "Accuracy score of  LogisticRegression = 79.60893854748603\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.11/dist-packages/sklearn/linear_model/_logistic.py:465: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
            "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
            "\n",
            "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
            "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
            "Please also refer to the documentation for alternative solver options:\n",
            "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
            "  n_iter_i = _check_optimize_result(\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# making predictions on the testing set\n",
        "for clf in (rfc, knn, svc,lc):\n",
        "    clf.fit(X_train, Y_train)\n",
        "    Y_pred = clf.predict(X_test)\n",
        "    print(\"Accuracy score of \",\n",
        "          clf.__class__.__name__,\"=\",\n",
        "          100*metrics.accuracy_score(Y_test,\n",
        "                                     Y_pred))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5A1Al3x8Q3ZC",
        "outputId": "28db2495-712a-4854-fc5c-f61afc47984f"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy score of  RandomForestClassifier = 82.5\n",
            "Accuracy score of  KNeighborsClassifier = 63.74999999999999\n",
            "Accuracy score of  SVC = 69.16666666666667\n",
            "Accuracy score of  LogisticRegression = 80.83333333333333\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.11/dist-packages/sklearn/linear_model/_logistic.py:465: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
            "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
            "\n",
            "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
            "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
            "Please also refer to the documentation for alternative solver options:\n",
            "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
            "  n_iter_i = _check_optimize_result(\n"
          ]
        }
      ]
    }
  ]
}