customer_ANN.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "import tensorflow as tf\n",
        "from tensorflow import keras\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from sklearn.model_selection import train_test_split\n",
        "import math,random\n",
        "from sklearn.preprocessing import OneHotEncoder,LabelEncoder\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "from sklearn.metrics import confusion_matrix,classification_report"
      ],
      "metadata": {
        "id": "CBhaXjtXm_EJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "SYOu6yfhm0HX"
      },
      "outputs": [],
      "source": [
        "churn_data=pd.read_csv('/content/drive/MyDrive/customer_churn')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 342
        },
        "id": "Mn3hCoK6m39s",
        "outputId": "70119665-3db0-4207-ac0f-8d677e119ae8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   customerID  gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
              "0  7590-VHVEG  Female              0     Yes         No       1           No   \n",
              "1  5575-GNVDE    Male              0      No         No      34          Yes   \n",
              "2  3668-QPYBK    Male              0      No         No       2          Yes   \n",
              "3  7795-CFOCW    Male              0      No         No      45           No   \n",
              "4  9237-HQITU  Female              0      No         No       2          Yes   \n",
              "\n",
              "      MultipleLines InternetService OnlineSecurity  ... DeviceProtection  \\\n",
              "0  No phone service             DSL             No  ...               No   \n",
              "1                No             DSL            Yes  ...              Yes   \n",
              "2                No             DSL            Yes  ...               No   \n",
              "3  No phone service             DSL            Yes  ...              Yes   \n",
              "4                No     Fiber optic             No  ...               No   \n",
              "\n",
              "  TechSupport StreamingTV StreamingMovies        Contract PaperlessBilling  \\\n",
              "0          No          No              No  Month-to-month              Yes   \n",
              "1          No          No              No        One year               No   \n",
              "2          No          No              No  Month-to-month              Yes   \n",
              "3         Yes          No              No        One year               No   \n",
              "4          No          No              No  Month-to-month              Yes   \n",
              "\n",
              "               PaymentMethod MonthlyCharges  TotalCharges Churn  \n",
              "0           Electronic check          29.85         29.85    No  \n",
              "1               Mailed check          56.95        1889.5    No  \n",
              "2               Mailed check          53.85        108.15   Yes  \n",
              "3  Bank transfer (automatic)          42.30       1840.75    No  \n",
              "4           Electronic check          70.70        151.65   Yes  \n",
              "\n",
              "[5 rows x 21 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-ea5a607f-11b3-4ca2-b587-6e680825476e\" 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>customerID</th>\n",
              "      <th>gender</th>\n",
              "      <th>SeniorCitizen</th>\n",
              "      <th>Partner</th>\n",
              "      <th>Dependents</th>\n",
              "      <th>tenure</th>\n",
              "      <th>PhoneService</th>\n",
              "      <th>MultipleLines</th>\n",
              "      <th>InternetService</th>\n",
              "      <th>OnlineSecurity</th>\n",
              "      <th>...</th>\n",
              "      <th>DeviceProtection</th>\n",
              "      <th>TechSupport</th>\n",
              "      <th>StreamingTV</th>\n",
              "      <th>StreamingMovies</th>\n",
              "      <th>Contract</th>\n",
              "      <th>PaperlessBilling</th>\n",
              "      <th>PaymentMethod</th>\n",
              "      <th>MonthlyCharges</th>\n",
              "      <th>TotalCharges</th>\n",
              "      <th>Churn</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>7590-VHVEG</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>1</td>\n",
              "      <td>No</td>\n",
              "      <td>No phone service</td>\n",
              "      <td>DSL</td>\n",
              "      <td>No</td>\n",
              "      <td>...</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>29.85</td>\n",
              "      <td>29.85</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>5575-GNVDE</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>34</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>...</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>One year</td>\n",
              "      <td>No</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>56.95</td>\n",
              "      <td>1889.5</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3668-QPYBK</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>2</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>...</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>53.85</td>\n",
              "      <td>108.15</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>7795-CFOCW</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>45</td>\n",
              "      <td>No</td>\n",
              "      <td>No phone service</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>...</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>One year</td>\n",
              "      <td>No</td>\n",
              "      <td>Bank transfer (automatic)</td>\n",
              "      <td>42.30</td>\n",
              "      <td>1840.75</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>9237-HQITU</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>2</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>...</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>70.70</td>\n",
              "      <td>151.65</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 21 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ea5a607f-11b3-4ca2-b587-6e680825476e')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-ea5a607f-11b3-4ca2-b587-6e680825476e 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-ea5a607f-11b3-4ca2-b587-6e680825476e');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-2040dcdf-7646-4e51-adce-c6ff5ea5b99c\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-2040dcdf-7646-4e51-adce-c6ff5ea5b99c')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-2040dcdf-7646-4e51-adce-c6ff5ea5b99c button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 349
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ITiviMa2nDfO",
        "outputId": "9116cbc2-aa41-4aff-e26f-3fc34a53ae2c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "customerID          0\n",
              "gender              0\n",
              "SeniorCitizen       0\n",
              "Partner             0\n",
              "Dependents          0\n",
              "tenure              0\n",
              "PhoneService        0\n",
              "MultipleLines       0\n",
              "InternetService     0\n",
              "OnlineSecurity      0\n",
              "OnlineBackup        0\n",
              "DeviceProtection    0\n",
              "TechSupport         0\n",
              "StreamingTV         0\n",
              "StreamingMovies     0\n",
              "Contract            0\n",
              "PaperlessBilling    0\n",
              "PaymentMethod       0\n",
              "MonthlyCharges      0\n",
              "TotalCharges        0\n",
              "Churn               0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 350
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6hbOz4Y7paVR",
        "outputId": "148ed90a-d470-41d4-fcd6-4786f91e2c28"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "customerID           object\n",
              "gender               object\n",
              "SeniorCitizen         int64\n",
              "Partner              object\n",
              "Dependents           object\n",
              "tenure                int64\n",
              "PhoneService         object\n",
              "MultipleLines        object\n",
              "InternetService      object\n",
              "OnlineSecurity       object\n",
              "OnlineBackup         object\n",
              "DeviceProtection     object\n",
              "TechSupport          object\n",
              "StreamingTV          object\n",
              "StreamingMovies      object\n",
              "Contract             object\n",
              "PaperlessBilling     object\n",
              "PaymentMethod        object\n",
              "MonthlyCharges      float64\n",
              "TotalCharges         object\n",
              "Churn                object\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 351
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data=churn_data.drop(['customerID'],axis=1)"
      ],
      "metadata": {
        "id": "ZZPPl8BEoBe3"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "_cWvNXOeo0mr",
        "outputId": "e673f86d-ef59-498f-e4a7-872c7550eae5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
              "0  Female              0     Yes         No       1           No   \n",
              "1    Male              0      No         No      34          Yes   \n",
              "2    Male              0      No         No       2          Yes   \n",
              "3    Male              0      No         No      45           No   \n",
              "4  Female              0      No         No       2          Yes   \n",
              "\n",
              "      MultipleLines InternetService OnlineSecurity OnlineBackup  \\\n",
              "0  No phone service             DSL             No          Yes   \n",
              "1                No             DSL            Yes           No   \n",
              "2                No             DSL            Yes          Yes   \n",
              "3  No phone service             DSL            Yes           No   \n",
              "4                No     Fiber optic             No           No   \n",
              "\n",
              "  DeviceProtection TechSupport StreamingTV StreamingMovies        Contract  \\\n",
              "0               No          No          No              No  Month-to-month   \n",
              "1              Yes          No          No              No        One year   \n",
              "2               No          No          No              No  Month-to-month   \n",
              "3              Yes         Yes          No              No        One year   \n",
              "4               No          No          No              No  Month-to-month   \n",
              "\n",
              "  PaperlessBilling              PaymentMethod  MonthlyCharges TotalCharges  \\\n",
              "0              Yes           Electronic check           29.85        29.85   \n",
              "1               No               Mailed check           56.95       1889.5   \n",
              "2              Yes               Mailed check           53.85       108.15   \n",
              "3               No  Bank transfer (automatic)           42.30      1840.75   \n",
              "4              Yes           Electronic check           70.70       151.65   \n",
              "\n",
              "  Churn  \n",
              "0    No  \n",
              "1    No  \n",
              "2   Yes  \n",
              "3    No  \n",
              "4   Yes  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-0a93beca-a799-4d35-893a-729b9e21162e\" 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>gender</th>\n",
              "      <th>SeniorCitizen</th>\n",
              "      <th>Partner</th>\n",
              "      <th>Dependents</th>\n",
              "      <th>tenure</th>\n",
              "      <th>PhoneService</th>\n",
              "      <th>MultipleLines</th>\n",
              "      <th>InternetService</th>\n",
              "      <th>OnlineSecurity</th>\n",
              "      <th>OnlineBackup</th>\n",
              "      <th>DeviceProtection</th>\n",
              "      <th>TechSupport</th>\n",
              "      <th>StreamingTV</th>\n",
              "      <th>StreamingMovies</th>\n",
              "      <th>Contract</th>\n",
              "      <th>PaperlessBilling</th>\n",
              "      <th>PaymentMethod</th>\n",
              "      <th>MonthlyCharges</th>\n",
              "      <th>TotalCharges</th>\n",
              "      <th>Churn</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>1</td>\n",
              "      <td>No</td>\n",
              "      <td>No phone service</td>\n",
              "      <td>DSL</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>29.85</td>\n",
              "      <td>29.85</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>34</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>One year</td>\n",
              "      <td>No</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>56.95</td>\n",
              "      <td>1889.5</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>2</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>53.85</td>\n",
              "      <td>108.15</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>45</td>\n",
              "      <td>No</td>\n",
              "      <td>No phone service</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>One year</td>\n",
              "      <td>No</td>\n",
              "      <td>Bank transfer (automatic)</td>\n",
              "      <td>42.30</td>\n",
              "      <td>1840.75</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>2</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>70.70</td>\n",
              "      <td>151.65</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0a93beca-a799-4d35-893a-729b9e21162e')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-0a93beca-a799-4d35-893a-729b9e21162e 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-0a93beca-a799-4d35-893a-729b9e21162e');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-816ff32d-0db8-411a-aa8a-0f5328ba9386\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-816ff32d-0db8-411a-aa8a-0f5328ba9386')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-816ff32d-0db8-411a-aa8a-0f5328ba9386 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 353
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JfYi6Tooo5oi",
        "outputId": "e134e813-4a72-4f82-8dfb-c0c1d54e9b30"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(7043, 20)"
            ]
          },
          "metadata": {},
          "execution_count": 354
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data['InternetService'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NxTxGH4fpLSi",
        "outputId": "94187530-bc7b-40fe-a2ea-e2392e0f274e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Fiber optic    3096\n",
              "DSL            2421\n",
              "No             1526\n",
              "Name: InternetService, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 355
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data['gender'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UoeIpZkYpziP",
        "outputId": "d55feda7-299b-4051-bb20-e0c77ccb5766"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Male      3555\n",
              "Female    3488\n",
              "Name: gender, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 356
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data['TotalCharges'].values"
      ],
      "metadata": {
        "id": "QXJvcVaiqXyc",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "10ec44c4-1a06-4809-ad1c-a3c7d0a17088"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['29.85', '1889.5', '108.15', ..., '346.45', '306.6', '6844.5'],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 357
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data[churn_data['TotalCharges']==' ']=0"
      ],
      "metadata": {
        "id": "89C7QkX9r-kn"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data['TotalCharges']=pd.to_numeric(churn_data['TotalCharges'])"
      ],
      "metadata": {
        "id": "LtUf8hW5rKR0"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data[churn_data['TotalCharges']==' ']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 73
        },
        "id": "FviIVUH1rlMk",
        "outputId": "846352d6-3d2f-495f-d053-a0836a133bdb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Empty DataFrame\n",
              "Columns: [gender, SeniorCitizen, Partner, Dependents, tenure, PhoneService, MultipleLines, InternetService, OnlineSecurity, OnlineBackup, DeviceProtection, TechSupport, StreamingTV, StreamingMovies, Contract, PaperlessBilling, PaymentMethod, MonthlyCharges, TotalCharges, Churn]\n",
              "Index: []"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-03731525-1a17-4126-b7d2-67df4c2056db\" 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>gender</th>\n",
              "      <th>SeniorCitizen</th>\n",
              "      <th>Partner</th>\n",
              "      <th>Dependents</th>\n",
              "      <th>tenure</th>\n",
              "      <th>PhoneService</th>\n",
              "      <th>MultipleLines</th>\n",
              "      <th>InternetService</th>\n",
              "      <th>OnlineSecurity</th>\n",
              "      <th>OnlineBackup</th>\n",
              "      <th>DeviceProtection</th>\n",
              "      <th>TechSupport</th>\n",
              "      <th>StreamingTV</th>\n",
              "      <th>StreamingMovies</th>\n",
              "      <th>Contract</th>\n",
              "      <th>PaperlessBilling</th>\n",
              "      <th>PaymentMethod</th>\n",
              "      <th>MonthlyCharges</th>\n",
              "      <th>TotalCharges</th>\n",
              "      <th>Churn</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-03731525-1a17-4126-b7d2-67df4c2056db')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-03731525-1a17-4126-b7d2-67df4c2056db 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-03731525-1a17-4126-b7d2-67df4c2056db');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 360
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data.reset_index()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 582
        },
        "id": "iotNNtKrtwSM",
        "outputId": "359e8edd-a242-4423-b27b-237e074aabac"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      index  gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
              "0         0  Female              0     Yes         No       1           No   \n",
              "1         1    Male              0      No         No      34          Yes   \n",
              "2         2    Male              0      No         No       2          Yes   \n",
              "3         3    Male              0      No         No      45           No   \n",
              "4         4  Female              0      No         No       2          Yes   \n",
              "...     ...     ...            ...     ...        ...     ...          ...   \n",
              "7038   7038    Male              0     Yes        Yes      24          Yes   \n",
              "7039   7039  Female              0     Yes        Yes      72          Yes   \n",
              "7040   7040  Female              0     Yes        Yes      11           No   \n",
              "7041   7041    Male              1     Yes         No       4          Yes   \n",
              "7042   7042    Male              0      No         No      66          Yes   \n",
              "\n",
              "         MultipleLines InternetService OnlineSecurity  ... DeviceProtection  \\\n",
              "0     No phone service             DSL             No  ...               No   \n",
              "1                   No             DSL            Yes  ...              Yes   \n",
              "2                   No             DSL            Yes  ...               No   \n",
              "3     No phone service             DSL            Yes  ...              Yes   \n",
              "4                   No     Fiber optic             No  ...               No   \n",
              "...                ...             ...            ...  ...              ...   \n",
              "7038               Yes             DSL            Yes  ...              Yes   \n",
              "7039               Yes     Fiber optic             No  ...              Yes   \n",
              "7040  No phone service             DSL            Yes  ...               No   \n",
              "7041               Yes     Fiber optic             No  ...               No   \n",
              "7042                No     Fiber optic            Yes  ...              Yes   \n",
              "\n",
              "     TechSupport StreamingTV StreamingMovies        Contract PaperlessBilling  \\\n",
              "0             No          No              No  Month-to-month              Yes   \n",
              "1             No          No              No        One year               No   \n",
              "2             No          No              No  Month-to-month              Yes   \n",
              "3            Yes          No              No        One year               No   \n",
              "4             No          No              No  Month-to-month              Yes   \n",
              "...          ...         ...             ...             ...              ...   \n",
              "7038         Yes         Yes             Yes        One year              Yes   \n",
              "7039          No         Yes             Yes        One year              Yes   \n",
              "7040          No          No              No  Month-to-month              Yes   \n",
              "7041          No          No              No  Month-to-month              Yes   \n",
              "7042         Yes         Yes             Yes        Two year              Yes   \n",
              "\n",
              "                  PaymentMethod MonthlyCharges  TotalCharges  Churn  \n",
              "0              Electronic check          29.85         29.85     No  \n",
              "1                  Mailed check          56.95       1889.50     No  \n",
              "2                  Mailed check          53.85        108.15    Yes  \n",
              "3     Bank transfer (automatic)          42.30       1840.75     No  \n",
              "4              Electronic check          70.70        151.65    Yes  \n",
              "...                         ...            ...           ...    ...  \n",
              "7038               Mailed check          84.80       1990.50     No  \n",
              "7039    Credit card (automatic)         103.20       7362.90     No  \n",
              "7040           Electronic check          29.60        346.45     No  \n",
              "7041               Mailed check          74.40        306.60    Yes  \n",
              "7042  Bank transfer (automatic)         105.65       6844.50     No  \n",
              "\n",
              "[7043 rows x 21 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b7ca3b45-fe8c-4f7a-b595-51308e036645\" 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>index</th>\n",
              "      <th>gender</th>\n",
              "      <th>SeniorCitizen</th>\n",
              "      <th>Partner</th>\n",
              "      <th>Dependents</th>\n",
              "      <th>tenure</th>\n",
              "      <th>PhoneService</th>\n",
              "      <th>MultipleLines</th>\n",
              "      <th>InternetService</th>\n",
              "      <th>OnlineSecurity</th>\n",
              "      <th>...</th>\n",
              "      <th>DeviceProtection</th>\n",
              "      <th>TechSupport</th>\n",
              "      <th>StreamingTV</th>\n",
              "      <th>StreamingMovies</th>\n",
              "      <th>Contract</th>\n",
              "      <th>PaperlessBilling</th>\n",
              "      <th>PaymentMethod</th>\n",
              "      <th>MonthlyCharges</th>\n",
              "      <th>TotalCharges</th>\n",
              "      <th>Churn</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>1</td>\n",
              "      <td>No</td>\n",
              "      <td>No phone service</td>\n",
              "      <td>DSL</td>\n",
              "      <td>No</td>\n",
              "      <td>...</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>29.85</td>\n",
              "      <td>29.85</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>34</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>...</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>One year</td>\n",
              "      <td>No</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>56.95</td>\n",
              "      <td>1889.50</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>2</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>...</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>53.85</td>\n",
              "      <td>108.15</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>45</td>\n",
              "      <td>No</td>\n",
              "      <td>No phone service</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>...</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>One year</td>\n",
              "      <td>No</td>\n",
              "      <td>Bank transfer (automatic)</td>\n",
              "      <td>42.30</td>\n",
              "      <td>1840.75</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>2</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>...</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>70.70</td>\n",
              "      <td>151.65</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7038</th>\n",
              "      <td>7038</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>24</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>...</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>One year</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>84.80</td>\n",
              "      <td>1990.50</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7039</th>\n",
              "      <td>7039</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>72</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>...</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>One year</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Credit card (automatic)</td>\n",
              "      <td>103.20</td>\n",
              "      <td>7362.90</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7040</th>\n",
              "      <td>7040</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>11</td>\n",
              "      <td>No</td>\n",
              "      <td>No phone service</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>...</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>29.60</td>\n",
              "      <td>346.45</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7041</th>\n",
              "      <td>7041</td>\n",
              "      <td>Male</td>\n",
              "      <td>1</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>4</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>...</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>74.40</td>\n",
              "      <td>306.60</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7042</th>\n",
              "      <td>7042</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>66</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>Yes</td>\n",
              "      <td>...</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Two year</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Bank transfer (automatic)</td>\n",
              "      <td>105.65</td>\n",
              "      <td>6844.50</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>7043 rows × 21 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b7ca3b45-fe8c-4f7a-b595-51308e036645')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-b7ca3b45-fe8c-4f7a-b595-51308e036645 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-b7ca3b45-fe8c-4f7a-b595-51308e036645');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-08825294-5302-41d2-ab8c-8af337abb6d1\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-08825294-5302-41d2-ab8c-8af337abb6d1')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-08825294-5302-41d2-ab8c-8af337abb6d1 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 361
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vO1kUaKKuXEe",
        "outputId": "72ac0cfd-38e5-4db8-c9f1-c064e5f94b1f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "gender               object\n",
              "SeniorCitizen         int64\n",
              "Partner              object\n",
              "Dependents           object\n",
              "tenure                int64\n",
              "PhoneService         object\n",
              "MultipleLines        object\n",
              "InternetService      object\n",
              "OnlineSecurity       object\n",
              "OnlineBackup         object\n",
              "DeviceProtection     object\n",
              "TechSupport          object\n",
              "StreamingTV          object\n",
              "StreamingMovies      object\n",
              "Contract             object\n",
              "PaperlessBilling     object\n",
              "PaymentMethod        object\n",
              "MonthlyCharges      float64\n",
              "TotalCharges        float64\n",
              "Churn                object\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 362
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data['TotalCharges'].values"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ad7khzI8vKzQ",
        "outputId": "7e0c99af-cc36-4ff5-aa0a-c9094ff5b25c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([  29.85, 1889.5 ,  108.15, ...,  346.45,  306.6 , 6844.5 ])"
            ]
          },
          "metadata": {},
          "execution_count": 363
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data[churn_data.Churn=='Yes']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 617
        },
        "id": "B8eh2qVawONA",
        "outputId": "2a26ea3c-83e8-4ce2-b76e-b7a3d2c2854c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
              "2       Male              0      No         No       2          Yes   \n",
              "4     Female              0      No         No       2          Yes   \n",
              "5     Female              0      No         No       8          Yes   \n",
              "8     Female              0     Yes         No      28          Yes   \n",
              "13      Male              0      No         No      49          Yes   \n",
              "...      ...            ...     ...        ...     ...          ...   \n",
              "7021    Male              0      No         No      12          Yes   \n",
              "7026  Female              0      No         No       9          Yes   \n",
              "7032    Male              1      No         No       1          Yes   \n",
              "7034  Female              0      No         No      67          Yes   \n",
              "7041    Male              1     Yes         No       4          Yes   \n",
              "\n",
              "     MultipleLines InternetService OnlineSecurity OnlineBackup  \\\n",
              "2               No             DSL            Yes          Yes   \n",
              "4               No     Fiber optic             No           No   \n",
              "5              Yes     Fiber optic             No           No   \n",
              "8              Yes     Fiber optic             No           No   \n",
              "13             Yes     Fiber optic             No          Yes   \n",
              "...            ...             ...            ...          ...   \n",
              "7021            No             DSL             No           No   \n",
              "7026            No             DSL             No           No   \n",
              "7032           Yes     Fiber optic             No           No   \n",
              "7034           Yes     Fiber optic            Yes          Yes   \n",
              "7041           Yes     Fiber optic             No           No   \n",
              "\n",
              "     DeviceProtection TechSupport StreamingTV StreamingMovies        Contract  \\\n",
              "2                  No          No          No              No  Month-to-month   \n",
              "4                  No          No          No              No  Month-to-month   \n",
              "5                 Yes          No         Yes             Yes  Month-to-month   \n",
              "8                 Yes         Yes         Yes             Yes  Month-to-month   \n",
              "13                Yes          No         Yes             Yes  Month-to-month   \n",
              "...               ...         ...         ...             ...             ...   \n",
              "7021               No         Yes         Yes              No        One year   \n",
              "7026               No          No          No              No  Month-to-month   \n",
              "7032               No          No          No              No  Month-to-month   \n",
              "7034              Yes          No         Yes              No  Month-to-month   \n",
              "7041               No          No          No              No  Month-to-month   \n",
              "\n",
              "     PaperlessBilling              PaymentMethod  MonthlyCharges  \\\n",
              "2                 Yes               Mailed check           53.85   \n",
              "4                 Yes           Electronic check           70.70   \n",
              "5                 Yes           Electronic check           99.65   \n",
              "8                 Yes           Electronic check          104.80   \n",
              "13                Yes  Bank transfer (automatic)          103.70   \n",
              "...               ...                        ...             ...   \n",
              "7021              Yes           Electronic check           59.80   \n",
              "7026              Yes  Bank transfer (automatic)           44.20   \n",
              "7032              Yes           Electronic check           75.75   \n",
              "7034              Yes    Credit card (automatic)          102.95   \n",
              "7041              Yes               Mailed check           74.40   \n",
              "\n",
              "      TotalCharges Churn  \n",
              "2           108.15   Yes  \n",
              "4           151.65   Yes  \n",
              "5           820.50   Yes  \n",
              "8          3046.05   Yes  \n",
              "13         5036.30   Yes  \n",
              "...            ...   ...  \n",
              "7021        727.80   Yes  \n",
              "7026        403.35   Yes  \n",
              "7032         75.75   Yes  \n",
              "7034       6886.25   Yes  \n",
              "7041        306.60   Yes  \n",
              "\n",
              "[1869 rows x 20 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b7ddb7ce-aa9b-4478-97d4-05e5c98352fa\" 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>gender</th>\n",
              "      <th>SeniorCitizen</th>\n",
              "      <th>Partner</th>\n",
              "      <th>Dependents</th>\n",
              "      <th>tenure</th>\n",
              "      <th>PhoneService</th>\n",
              "      <th>MultipleLines</th>\n",
              "      <th>InternetService</th>\n",
              "      <th>OnlineSecurity</th>\n",
              "      <th>OnlineBackup</th>\n",
              "      <th>DeviceProtection</th>\n",
              "      <th>TechSupport</th>\n",
              "      <th>StreamingTV</th>\n",
              "      <th>StreamingMovies</th>\n",
              "      <th>Contract</th>\n",
              "      <th>PaperlessBilling</th>\n",
              "      <th>PaymentMethod</th>\n",
              "      <th>MonthlyCharges</th>\n",
              "      <th>TotalCharges</th>\n",
              "      <th>Churn</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>2</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>53.85</td>\n",
              "      <td>108.15</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>2</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>70.70</td>\n",
              "      <td>151.65</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>8</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>99.65</td>\n",
              "      <td>820.50</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>28</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>104.80</td>\n",
              "      <td>3046.05</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>49</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Bank transfer (automatic)</td>\n",
              "      <td>103.70</td>\n",
              "      <td>5036.30</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7021</th>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>12</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>DSL</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>One year</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>59.80</td>\n",
              "      <td>727.80</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7026</th>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>9</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>DSL</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Bank transfer (automatic)</td>\n",
              "      <td>44.20</td>\n",
              "      <td>403.35</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7032</th>\n",
              "      <td>Male</td>\n",
              "      <td>1</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>1</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>75.75</td>\n",
              "      <td>75.75</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7034</th>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>67</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Credit card (automatic)</td>\n",
              "      <td>102.95</td>\n",
              "      <td>6886.25</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7041</th>\n",
              "      <td>Male</td>\n",
              "      <td>1</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>4</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>74.40</td>\n",
              "      <td>306.60</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1869 rows × 20 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b7ddb7ce-aa9b-4478-97d4-05e5c98352fa')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-b7ddb7ce-aa9b-4478-97d4-05e5c98352fa 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-b7ddb7ce-aa9b-4478-97d4-05e5c98352fa');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-17ab48d0-dfdb-4a2e-abe9-93ed10a8da01\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-17ab48d0-dfdb-4a2e-abe9-93ed10a8da01')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-17ab48d0-dfdb-4a2e-abe9-93ed10a8da01 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 364
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data=churn_data[churn_data['TotalCharges']!=0]"
      ],
      "metadata": {
        "id": "0BdhZs-PwfsQ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data.Churn.value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nHqFbvC5zNzj",
        "outputId": "9ab2cd0f-b87b-4103-9103-92293ff7bdc7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "No     5163\n",
              "Yes    1869\n",
              "Name: Churn, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 366
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data[churn_data.Churn=='Yes'].shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fRiVtK_dzSqO",
        "outputId": "9c10e0ba-4cb5-4dc1-c3e2-9c1740a91bdb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1869, 20)"
            ]
          },
          "metadata": {},
          "execution_count": 369
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "t_c_no=churn_data[churn_data['Churn']=='No'].tenure\n",
        "t_c_yes=churn_data[churn_data['Churn']=='Yes'].tenure\n",
        "\n",
        "plt.xlabel('Tenure')\n",
        "plt.ylabel(\"No of customer churd\")\n",
        "plt.title(\"Tenure v/s Number of cust churd\")\n",
        "\n",
        "plt.hist([t_c_no,t_c_yes],color=[\"green\",\"red\"])\n",
        "plt.legend()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 507
        },
        "id": "_1PT8h_10R4Z",
        "outputId": "7bd17706-5dfd-43f1-e252-1952e696c823"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:matplotlib.legend:No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x794fcb869360>"
            ]
          },
          "metadata": {},
          "execution_count": 370
        },
        {
          "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": [
        "m_c_no=churn_data[churn_data['Churn']=='No'].MonthlyCharges\n",
        "m_c_yes=churn_data[churn_data['Churn']=='Yes'].MonthlyCharges\n",
        "\n",
        "plt.xlabel('Monthly Charges')\n",
        "plt.ylabel(\"No of customer churd\")\n",
        "plt.title(\"Monthly Charges v/s Number of cust churd\")\n",
        "\n",
        "plt.hist([m_c_no,m_c_yes],color=[\"green\",\"red\"])\n",
        "plt.legend()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 507
        },
        "id": "1RQKFtEO2OJt",
        "outputId": "1ca295c4-0a0f-410b-b1a8-defa8cceef7a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:matplotlib.legend:No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x794fcb6ffa00>"
            ]
          },
          "metadata": {},
          "execution_count": 371
        },
        {
          "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": [
        "total_c_no=churn_data[churn_data['Churn']=='No'].TotalCharges\n",
        "total_c_yes=churn_data[churn_data['Churn']=='Yes'].TotalCharges\n",
        "\n",
        "plt.xlabel('Total Charges')\n",
        "plt.ylabel(\"No of customer churd\")\n",
        "plt.title(\"Total Charges v/s Number of cust churd\")\n",
        "\n",
        "plt.hist([total_c_no,total_c_yes],color=[\"green\",\"red\"])\n",
        "\n",
        "plt.legend()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 507
        },
        "id": "6XUUB8SrDeWe",
        "outputId": "39ba3e06-cb71-4ac5-ef2f-e3ed3e836cad"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:matplotlib.legend:No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x794fcb79f7f0>"
            ]
          },
          "metadata": {},
          "execution_count": 372
        },
        {
          "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": [],
      "metadata": {
        "id": "qbpbCIDKR5aR"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "Duf2oF2lODtT",
        "outputId": "5fea9664-beb4-421f-8d2a-3bb151dd2b2c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
              "0  Female              0     Yes         No       1           No   \n",
              "1    Male              0      No         No      34          Yes   \n",
              "2    Male              0      No         No       2          Yes   \n",
              "3    Male              0      No         No      45           No   \n",
              "4  Female              0      No         No       2          Yes   \n",
              "\n",
              "      MultipleLines InternetService OnlineSecurity OnlineBackup  \\\n",
              "0  No phone service             DSL             No          Yes   \n",
              "1                No             DSL            Yes           No   \n",
              "2                No             DSL            Yes          Yes   \n",
              "3  No phone service             DSL            Yes           No   \n",
              "4                No     Fiber optic             No           No   \n",
              "\n",
              "  DeviceProtection TechSupport StreamingTV StreamingMovies        Contract  \\\n",
              "0               No          No          No              No  Month-to-month   \n",
              "1              Yes          No          No              No        One year   \n",
              "2               No          No          No              No  Month-to-month   \n",
              "3              Yes         Yes          No              No        One year   \n",
              "4               No          No          No              No  Month-to-month   \n",
              "\n",
              "  PaperlessBilling              PaymentMethod  MonthlyCharges  TotalCharges  \\\n",
              "0              Yes           Electronic check           29.85         29.85   \n",
              "1               No               Mailed check           56.95       1889.50   \n",
              "2              Yes               Mailed check           53.85        108.15   \n",
              "3               No  Bank transfer (automatic)           42.30       1840.75   \n",
              "4              Yes           Electronic check           70.70        151.65   \n",
              "\n",
              "  Churn  \n",
              "0    No  \n",
              "1    No  \n",
              "2   Yes  \n",
              "3    No  \n",
              "4   Yes  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5bd0ddb8-8f88-4c33-9942-ca779dd036cc\" 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>gender</th>\n",
              "      <th>SeniorCitizen</th>\n",
              "      <th>Partner</th>\n",
              "      <th>Dependents</th>\n",
              "      <th>tenure</th>\n",
              "      <th>PhoneService</th>\n",
              "      <th>MultipleLines</th>\n",
              "      <th>InternetService</th>\n",
              "      <th>OnlineSecurity</th>\n",
              "      <th>OnlineBackup</th>\n",
              "      <th>DeviceProtection</th>\n",
              "      <th>TechSupport</th>\n",
              "      <th>StreamingTV</th>\n",
              "      <th>StreamingMovies</th>\n",
              "      <th>Contract</th>\n",
              "      <th>PaperlessBilling</th>\n",
              "      <th>PaymentMethod</th>\n",
              "      <th>MonthlyCharges</th>\n",
              "      <th>TotalCharges</th>\n",
              "      <th>Churn</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>1</td>\n",
              "      <td>No</td>\n",
              "      <td>No phone service</td>\n",
              "      <td>DSL</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>29.85</td>\n",
              "      <td>29.85</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>34</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>One year</td>\n",
              "      <td>No</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>56.95</td>\n",
              "      <td>1889.50</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>2</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>53.85</td>\n",
              "      <td>108.15</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>45</td>\n",
              "      <td>No</td>\n",
              "      <td>No phone service</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>One year</td>\n",
              "      <td>No</td>\n",
              "      <td>Bank transfer (automatic)</td>\n",
              "      <td>42.30</td>\n",
              "      <td>1840.75</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>2</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>70.70</td>\n",
              "      <td>151.65</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5bd0ddb8-8f88-4c33-9942-ca779dd036cc')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-5bd0ddb8-8f88-4c33-9942-ca779dd036cc 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-5bd0ddb8-8f88-4c33-9942-ca779dd036cc');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-a8de7527-d7fa-4351-9d0c-a57b39133b7b\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-a8de7527-d7fa-4351-9d0c-a57b39133b7b')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-a8de7527-d7fa-4351-9d0c-a57b39133b7b button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 373
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def col_unique(d):\n",
        "  for col in d:\n",
        "    print(col,\":\",d[col].unique())"
      ],
      "metadata": {
        "id": "ejm7CZ7mOLJ2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "col_unique(churn_data)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SFwhKQ7fQdDb",
        "outputId": "21fde2e0-0439-4c59-c483-de4a41b8e19a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "gender : ['Female' 'Male']\n",
            "SeniorCitizen : [0 1]\n",
            "Partner : ['Yes' 'No']\n",
            "Dependents : ['No' 'Yes']\n",
            "tenure : [ 1 34  2 45  8 22 10 28 62 13 16 58 49 25 69 52 71 21 12 30 47 72 17 27\n",
            "  5 46 11 70 63 43 15 60 18 66  9  3 31 50 64 56  7 42 35 48 29 65 38 68\n",
            " 32 55 37 36 41  6  4 33 67 23 57 61 14 20 53 40 59 24 44 19 54 51 26 39]\n",
            "PhoneService : ['No' 'Yes']\n",
            "MultipleLines : ['No phone service' 'No' 'Yes']\n",
            "InternetService : ['DSL' 'Fiber optic' 'No']\n",
            "OnlineSecurity : ['No' 'Yes' 'No internet service']\n",
            "OnlineBackup : ['Yes' 'No' 'No internet service']\n",
            "DeviceProtection : ['No' 'Yes' 'No internet service']\n",
            "TechSupport : ['No' 'Yes' 'No internet service']\n",
            "StreamingTV : ['No' 'Yes' 'No internet service']\n",
            "StreamingMovies : ['No' 'Yes' 'No internet service']\n",
            "Contract : ['Month-to-month' 'One year' 'Two year']\n",
            "PaperlessBilling : ['Yes' 'No']\n",
            "PaymentMethod : ['Electronic check' 'Mailed check' 'Bank transfer (automatic)'\n",
            " 'Credit card (automatic)']\n",
            "MonthlyCharges : [29.85 56.95 53.85 ... 63.1  44.2  78.7 ]\n",
            "TotalCharges : [  29.85 1889.5   108.15 ...  346.45  306.6  6844.5 ]\n",
            "Churn : ['No' 'Yes']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "-nEmGTpbXWWA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data[[churn_data['MultipleLines']=='No phone service']]= 'No'"
      ],
      "metadata": {
        "id": "_viz1XjGQgB3"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "bvG8NY5QXo-R"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "churn_data.replace('No internet service',\"No\",inplace=True)\n",
        "churn_data.replace('No phone service',\"No\",inplace=True)\n"
      ],
      "metadata": {
        "id": "P5A5vTBZSjcg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "col_unique(churn_data)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "s6xGWQFiTPeO",
        "outputId": "c2669e40-f700-4862-ff64-dce6f74b2302"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "gender : ['Female' 'Male']\n",
            "SeniorCitizen : [0 1]\n",
            "Partner : ['Yes' 'No']\n",
            "Dependents : ['No' 'Yes']\n",
            "tenure : [1 34 2 45 8 22 10 28 62 13 16 58 49 25 69 52 71 21 12 30 47 72 17 27 5 46\n",
            " 11 70 63 43 15 60 18 66 9 3 31 50 64 56 7 42 35 48 29 65 38 68 32 55 37\n",
            " 36 41 6 4 33 67 23 57 61 14 20 53 40 59 24 44 19 54 51 26 39]\n",
            "PhoneService : ['No' 'Yes']\n",
            "MultipleLines : ['No' 'Yes']\n",
            "InternetService : ['DSL' 'Fiber optic' 'No']\n",
            "OnlineSecurity : ['No' 'Yes']\n",
            "OnlineBackup : ['Yes' 'No']\n",
            "DeviceProtection : ['No' 'Yes']\n",
            "TechSupport : ['No' 'Yes']\n",
            "StreamingTV : ['No' 'Yes']\n",
            "StreamingMovies : ['No' 'Yes']\n",
            "Contract : ['Month-to-month' 'One year' 'Two year']\n",
            "PaperlessBilling : ['Yes' 'No']\n",
            "PaymentMethod : ['Electronic check' 'Mailed check' 'Bank transfer (automatic)'\n",
            " 'Credit card (automatic)']\n",
            "MonthlyCharges : [29.85 56.95 53.85 ... 63.1 44.2 78.7]\n",
            "TotalCharges : [29.85 1889.5 108.15 ... 346.45 306.6 6844.5]\n",
            "Churn : ['No' 'Yes']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "yes_no_col=['SeniorCitizen','Partner','Dependents','PhoneService','MultipleLines','OnlineSecurity','OnlineSecurity','OnlineBackup','DeviceProtection','TechSupport','StreamingTV','StreamingTV','StreamingMovies','PaperlessBilling','Churn']\n"
      ],
      "metadata": {
        "id": "QqeAGklLTRkf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for col in yes_no_col:\n",
        "  churn_data[col].replace({'Yes':1,'No':0},inplace=True)"
      ],
      "metadata": {
        "id": "Y16OXRlqVEdY"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "col_unique(churn_data)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YBjClozQWRXi",
        "outputId": "09338e6c-57df-4cb3-da29-d027fe571d55"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "gender : ['Female' 'Male']\n",
            "SeniorCitizen : [0 1]\n",
            "Partner : [1 0]\n",
            "Dependents : [0 1]\n",
            "tenure : [1 34 2 45 8 22 10 28 62 13 16 58 49 25 69 52 71 21 12 30 47 72 17 27 5 46\n",
            " 11 70 63 43 15 60 18 66 9 3 31 50 64 56 7 42 35 48 29 65 38 68 32 55 37\n",
            " 36 41 6 4 33 67 23 57 61 14 20 53 40 59 24 44 19 54 51 26 39]\n",
            "PhoneService : [0 1]\n",
            "MultipleLines : [0 1]\n",
            "InternetService : ['DSL' 'Fiber optic' 'No']\n",
            "OnlineSecurity : [0 1]\n",
            "OnlineBackup : [1 0]\n",
            "DeviceProtection : [0 1]\n",
            "TechSupport : [0 1]\n",
            "StreamingTV : [0 1]\n",
            "StreamingMovies : [0 1]\n",
            "Contract : ['Month-to-month' 'One year' 'Two year']\n",
            "PaperlessBilling : [1 0]\n",
            "PaymentMethod : ['Electronic check' 'Mailed check' 'Bank transfer (automatic)'\n",
            " 'Credit card (automatic)']\n",
            "MonthlyCharges : [29.85 56.95 53.85 ... 63.1 44.2 78.7]\n",
            "TotalCharges : [29.85 1889.5 108.15 ... 346.45 306.6 6844.5]\n",
            "Churn : [0 1]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "aPWyZubuWTYy"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "cols=['gender','InternetService','Contract','PaymentMethod']\n",
        "churn_data=pd.get_dummies(data=churn_data,columns=cols)"
      ],
      "metadata": {
        "id": "dNLQM8MXI_2H"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "columns_to_scale = ['tenure', 'MonthlyCharges', 'TotalCharges']\n",
        "scaler=MinMaxScaler()\n",
        "churn_data[columns_to_scale] = scaler.fit_transform(churn_data[columns_to_scale])"
      ],
      "metadata": {
        "id": "1XCNMVgcY_gj"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X=churn_data.drop(\"Churn\",axis='columns')\n",
        "y=churn_data['Churn']"
      ],
      "metadata": {
        "id": "WsXLkITqZxZ0"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "yXD1GUdfxdG_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 478
        },
        "id": "uwo1hDa64phA",
        "outputId": "79025986-ab22-4519-d07d-3881a18f3882"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      SeniorCitizen  Partner  Dependents    tenure  PhoneService  \\\n",
              "0                 0        1           0  0.000000             0   \n",
              "1                 0        0           0  0.464789             1   \n",
              "2                 0        0           0  0.014085             1   \n",
              "3                 0        0           0  0.619718             0   \n",
              "4                 0        0           0  0.014085             1   \n",
              "...             ...      ...         ...       ...           ...   \n",
              "7038              0        1           1  0.323944             1   \n",
              "7039              0        1           1  1.000000             1   \n",
              "7040              0        1           1  0.140845             0   \n",
              "7041              1        1           0  0.042254             1   \n",
              "7042              0        0           0  0.915493             1   \n",
              "\n",
              "      MultipleLines  OnlineSecurity  OnlineBackup  DeviceProtection  \\\n",
              "0                 0               0             1                 0   \n",
              "1                 0               1             0                 1   \n",
              "2                 0               1             1                 0   \n",
              "3                 0               1             0                 1   \n",
              "4                 0               0             0                 0   \n",
              "...             ...             ...           ...               ...   \n",
              "7038              1               1             0                 1   \n",
              "7039              1               0             1                 1   \n",
              "7040              0               1             0                 0   \n",
              "7041              1               0             0                 0   \n",
              "7042              0               1             0                 1   \n",
              "\n",
              "      TechSupport  ...  InternetService_DSL  InternetService_Fiber optic  \\\n",
              "0               0  ...                    1                            0   \n",
              "1               0  ...                    1                            0   \n",
              "2               0  ...                    1                            0   \n",
              "3               1  ...                    1                            0   \n",
              "4               0  ...                    0                            1   \n",
              "...           ...  ...                  ...                          ...   \n",
              "7038            1  ...                    1                            0   \n",
              "7039            0  ...                    0                            1   \n",
              "7040            0  ...                    1                            0   \n",
              "7041            0  ...                    0                            1   \n",
              "7042            1  ...                    0                            1   \n",
              "\n",
              "      InternetService_No  Contract_Month-to-month  Contract_One year  \\\n",
              "0                      0                        1                  0   \n",
              "1                      0                        0                  1   \n",
              "2                      0                        1                  0   \n",
              "3                      0                        0                  1   \n",
              "4                      0                        1                  0   \n",
              "...                  ...                      ...                ...   \n",
              "7038                   0                        0                  1   \n",
              "7039                   0                        0                  1   \n",
              "7040                   0                        1                  0   \n",
              "7041                   0                        1                  0   \n",
              "7042                   0                        0                  0   \n",
              "\n",
              "      Contract_Two year  PaymentMethod_Bank transfer (automatic)  \\\n",
              "0                     0                                        0   \n",
              "1                     0                                        0   \n",
              "2                     0                                        0   \n",
              "3                     0                                        1   \n",
              "4                     0                                        0   \n",
              "...                 ...                                      ...   \n",
              "7038                  0                                        0   \n",
              "7039                  0                                        0   \n",
              "7040                  0                                        0   \n",
              "7041                  0                                        0   \n",
              "7042                  1                                        1   \n",
              "\n",
              "      PaymentMethod_Credit card (automatic)  PaymentMethod_Electronic check  \\\n",
              "0                                         0                               1   \n",
              "1                                         0                               0   \n",
              "2                                         0                               0   \n",
              "3                                         0                               0   \n",
              "4                                         0                               1   \n",
              "...                                     ...                             ...   \n",
              "7038                                      0                               0   \n",
              "7039                                      1                               0   \n",
              "7040                                      0                               1   \n",
              "7041                                      0                               0   \n",
              "7042                                      0                               0   \n",
              "\n",
              "      PaymentMethod_Mailed check  \n",
              "0                              0  \n",
              "1                              1  \n",
              "2                              1  \n",
              "3                              0  \n",
              "4                              0  \n",
              "...                          ...  \n",
              "7038                           1  \n",
              "7039                           0  \n",
              "7040                           0  \n",
              "7041                           1  \n",
              "7042                           0  \n",
              "\n",
              "[7032 rows x 27 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b235e290-c0c7-4f99-8913-ca9f69d87531\" 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>SeniorCitizen</th>\n",
              "      <th>Partner</th>\n",
              "      <th>Dependents</th>\n",
              "      <th>tenure</th>\n",
              "      <th>PhoneService</th>\n",
              "      <th>MultipleLines</th>\n",
              "      <th>OnlineSecurity</th>\n",
              "      <th>OnlineBackup</th>\n",
              "      <th>DeviceProtection</th>\n",
              "      <th>TechSupport</th>\n",
              "      <th>...</th>\n",
              "      <th>InternetService_DSL</th>\n",
              "      <th>InternetService_Fiber optic</th>\n",
              "      <th>InternetService_No</th>\n",
              "      <th>Contract_Month-to-month</th>\n",
              "      <th>Contract_One year</th>\n",
              "      <th>Contract_Two year</th>\n",
              "      <th>PaymentMethod_Bank transfer (automatic)</th>\n",
              "      <th>PaymentMethod_Credit card (automatic)</th>\n",
              "      <th>PaymentMethod_Electronic check</th>\n",
              "      <th>PaymentMethod_Mailed check</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.464789</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.014085</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.619718</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.014085</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7038</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.323944</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7039</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7040</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.140845</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7041</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0.042254</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7042</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.915493</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>7032 rows × 27 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b235e290-c0c7-4f99-8913-ca9f69d87531')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-b235e290-c0c7-4f99-8913-ca9f69d87531 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-b235e290-c0c7-4f99-8913-ca9f69d87531');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-016fd90f-9222-4623-885d-78d4b470bb6e\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-016fd90f-9222-4623-885d-78d4b470bb6e')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-016fd90f-9222-4623-885d-78d4b470bb6e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_3e49dbdc-d09e-4ca7-809f-20859327b200\">\n",
              "    <style>\n",
              "      .colab-df-generate {\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-generate: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-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate: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",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('X')\"\n",
              "            title=\"Generate code using this dataframe.\"\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=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_3e49dbdc-d09e-4ca7-809f-20859327b200 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('X');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 386
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.2,random_state=30)"
      ],
      "metadata": {
        "id": "oD8dmq34ZcW0"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train.shape,X_test.shape,y_train.shape,y_test.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OJTbhGkdaN4f",
        "outputId": "49c1e6c0-2658-4332-e4ba-23b424b022cd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((5625, 27), (1407, 27), (5625,), (1407,))"
            ]
          },
          "metadata": {},
          "execution_count": 388
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "S"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zirZfhpex-sV",
        "outputId": "a039834b-b6d3-4714-aa4f-17fc713a22d3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/50\n",
            "12/12 [==============================] - 1s 4ms/step - loss: 0.6736 - accuracy: 0.5812\n",
            "Epoch 2/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5847 - accuracy: 0.7301\n",
            "Epoch 3/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5655 - accuracy: 0.7348\n",
            "Epoch 4/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5463 - accuracy: 0.7351\n",
            "Epoch 5/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5308 - accuracy: 0.7394\n",
            "Epoch 6/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5160 - accuracy: 0.7433\n",
            "Epoch 7/50\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5050 - accuracy: 0.7449\n",
            "Epoch 8/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4937 - accuracy: 0.7483\n",
            "Epoch 9/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4854 - accuracy: 0.7534\n",
            "Epoch 10/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4780 - accuracy: 0.7607\n",
            "Epoch 11/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4735 - accuracy: 0.7689\n",
            "Epoch 12/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4663 - accuracy: 0.7742\n",
            "Epoch 13/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4599 - accuracy: 0.7698\n",
            "Epoch 14/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4591 - accuracy: 0.7714\n",
            "Epoch 15/50\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4549 - accuracy: 0.7840\n",
            "Epoch 16/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4509 - accuracy: 0.7797\n",
            "Epoch 17/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4494 - accuracy: 0.7815\n",
            "Epoch 18/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4463 - accuracy: 0.7845\n",
            "Epoch 19/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4436 - accuracy: 0.7886\n",
            "Epoch 20/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4442 - accuracy: 0.7856\n",
            "Epoch 21/50\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4367 - accuracy: 0.7941\n",
            "Epoch 22/50\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4407 - accuracy: 0.7865\n",
            "Epoch 23/50\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4386 - accuracy: 0.7881\n",
            "Epoch 24/50\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4384 - accuracy: 0.7881\n",
            "Epoch 25/50\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4392 - accuracy: 0.7876\n",
            "Epoch 26/50\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4368 - accuracy: 0.7883\n",
            "Epoch 27/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4355 - accuracy: 0.7911\n",
            "Epoch 28/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4328 - accuracy: 0.7945\n",
            "Epoch 29/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4334 - accuracy: 0.7867\n",
            "Epoch 30/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4317 - accuracy: 0.7897\n",
            "Epoch 31/50\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4329 - accuracy: 0.7943\n",
            "Epoch 32/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4330 - accuracy: 0.7927\n",
            "Epoch 33/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4308 - accuracy: 0.7870\n",
            "Epoch 34/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4314 - accuracy: 0.7906\n",
            "Epoch 35/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4280 - accuracy: 0.7929\n",
            "Epoch 36/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4275 - accuracy: 0.7940\n",
            "Epoch 37/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4270 - accuracy: 0.7943\n",
            "Epoch 38/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4278 - accuracy: 0.7970\n",
            "Epoch 39/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4283 - accuracy: 0.7950\n",
            "Epoch 40/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4295 - accuracy: 0.7929\n",
            "Epoch 41/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4272 - accuracy: 0.7968\n",
            "Epoch 42/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4261 - accuracy: 0.7973\n",
            "Epoch 43/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4272 - accuracy: 0.7938\n",
            "Epoch 44/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4252 - accuracy: 0.7982\n",
            "Epoch 45/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4287 - accuracy: 0.7948\n",
            "Epoch 46/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4268 - accuracy: 0.7980\n",
            "Epoch 47/50\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4261 - accuracy: 0.7972\n",
            "Epoch 48/50\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4276 - accuracy: 0.7948\n",
            "Epoch 49/50\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4244 - accuracy: 0.7989\n",
            "Epoch 50/50\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4280 - accuracy: 0.7929\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.src.callbacks.History at 0x794fc7ac8f70>"
            ]
          },
          "metadata": {},
          "execution_count": 407
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model2 = keras.Sequential([\n",
        "    keras.layers.Dense(100, input_shape=(27,), activation='sigmoid',kernel_initializer=keras.initializers.GlorotNormal()),\n",
        "    keras.layers.Dense(1,activation='sigmoid')\n",
        "])\n",
        "\n",
        "model2.compile(\n",
        "    optimizer='SGD',\n",
        "    loss='binary_crossentropy',\n",
        "    metrics=['accuracy']\n",
        ")\n",
        "\n",
        "# Fit the model\n",
        "model2.fit(X_train, y_train, epochs=500, batch_size = 500)\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NnIfrUtI_rIR",
        "outputId": "89e82bf5-a76d-4406-c5a3-55b710b51832"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/500\n",
            "12/12 [==============================] - 1s 3ms/step - loss: 0.6280 - accuracy: 0.7339\n",
            "Epoch 2/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5904 - accuracy: 0.7346\n",
            "Epoch 3/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5825 - accuracy: 0.7346\n",
            "Epoch 4/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5800 - accuracy: 0.7346\n",
            "Epoch 5/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5789 - accuracy: 0.7346\n",
            "Epoch 6/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5779 - accuracy: 0.7346\n",
            "Epoch 7/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5770 - accuracy: 0.7346\n",
            "Epoch 8/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5762 - accuracy: 0.7346\n",
            "Epoch 9/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5754 - accuracy: 0.7346\n",
            "Epoch 10/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5746 - accuracy: 0.7346\n",
            "Epoch 11/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5737 - accuracy: 0.7346\n",
            "Epoch 12/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5729 - accuracy: 0.7346\n",
            "Epoch 13/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5721 - accuracy: 0.7346\n",
            "Epoch 14/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5713 - accuracy: 0.7346\n",
            "Epoch 15/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5704 - accuracy: 0.7346\n",
            "Epoch 16/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5697 - accuracy: 0.7346\n",
            "Epoch 17/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5689 - accuracy: 0.7346\n",
            "Epoch 18/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5681 - accuracy: 0.7346\n",
            "Epoch 19/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5673 - accuracy: 0.7346\n",
            "Epoch 20/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5665 - accuracy: 0.7346\n",
            "Epoch 21/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5657 - accuracy: 0.7346\n",
            "Epoch 22/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5649 - accuracy: 0.7346\n",
            "Epoch 23/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5641 - accuracy: 0.7346\n",
            "Epoch 24/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5634 - accuracy: 0.7346\n",
            "Epoch 25/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5626 - accuracy: 0.7346\n",
            "Epoch 26/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5618 - accuracy: 0.7346\n",
            "Epoch 27/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5611 - accuracy: 0.7346\n",
            "Epoch 28/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5604 - accuracy: 0.7346\n",
            "Epoch 29/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5596 - accuracy: 0.7346\n",
            "Epoch 30/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5588 - accuracy: 0.7346\n",
            "Epoch 31/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5581 - accuracy: 0.7346\n",
            "Epoch 32/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5573 - accuracy: 0.7346\n",
            "Epoch 33/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5566 - accuracy: 0.7346\n",
            "Epoch 34/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5559 - accuracy: 0.7346\n",
            "Epoch 35/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5551 - accuracy: 0.7346\n",
            "Epoch 36/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5544 - accuracy: 0.7346\n",
            "Epoch 37/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5537 - accuracy: 0.7346\n",
            "Epoch 38/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5529 - accuracy: 0.7346\n",
            "Epoch 39/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5522 - accuracy: 0.7346\n",
            "Epoch 40/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5515 - accuracy: 0.7346\n",
            "Epoch 41/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5507 - accuracy: 0.7346\n",
            "Epoch 42/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5500 - accuracy: 0.7346\n",
            "Epoch 43/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5493 - accuracy: 0.7346\n",
            "Epoch 44/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5486 - accuracy: 0.7346\n",
            "Epoch 45/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5478 - accuracy: 0.7346\n",
            "Epoch 46/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5471 - accuracy: 0.7346\n",
            "Epoch 47/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5464 - accuracy: 0.7346\n",
            "Epoch 48/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5457 - accuracy: 0.7346\n",
            "Epoch 49/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5450 - accuracy: 0.7346\n",
            "Epoch 50/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5443 - accuracy: 0.7346\n",
            "Epoch 51/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5436 - accuracy: 0.7346\n",
            "Epoch 52/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5429 - accuracy: 0.7346\n",
            "Epoch 53/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5422 - accuracy: 0.7346\n",
            "Epoch 54/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5416 - accuracy: 0.7346\n",
            "Epoch 55/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5409 - accuracy: 0.7346\n",
            "Epoch 56/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5402 - accuracy: 0.7346\n",
            "Epoch 57/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5395 - accuracy: 0.7346\n",
            "Epoch 58/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5388 - accuracy: 0.7346\n",
            "Epoch 59/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.5381 - accuracy: 0.7346\n",
            "Epoch 60/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.5375 - accuracy: 0.7346\n",
            "Epoch 61/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5368 - accuracy: 0.7346\n",
            "Epoch 62/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5361 - accuracy: 0.7346\n",
            "Epoch 63/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5354 - accuracy: 0.7346\n",
            "Epoch 64/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5348 - accuracy: 0.7346\n",
            "Epoch 65/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5341 - accuracy: 0.7346\n",
            "Epoch 66/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5334 - accuracy: 0.7346\n",
            "Epoch 67/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5328 - accuracy: 0.7346\n",
            "Epoch 68/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5321 - accuracy: 0.7346\n",
            "Epoch 69/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5315 - accuracy: 0.7346\n",
            "Epoch 70/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5308 - accuracy: 0.7346\n",
            "Epoch 71/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5302 - accuracy: 0.7346\n",
            "Epoch 72/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5295 - accuracy: 0.7346\n",
            "Epoch 73/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5289 - accuracy: 0.7346\n",
            "Epoch 74/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5282 - accuracy: 0.7346\n",
            "Epoch 75/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5276 - accuracy: 0.7346\n",
            "Epoch 76/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5269 - accuracy: 0.7346\n",
            "Epoch 77/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5263 - accuracy: 0.7346\n",
            "Epoch 78/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5256 - accuracy: 0.7346\n",
            "Epoch 79/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5250 - accuracy: 0.7346\n",
            "Epoch 80/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5244 - accuracy: 0.7346\n",
            "Epoch 81/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5237 - accuracy: 0.7346\n",
            "Epoch 82/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.5231 - accuracy: 0.7346\n",
            "Epoch 83/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5224 - accuracy: 0.7346\n",
            "Epoch 84/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.5218 - accuracy: 0.7346\n",
            "Epoch 85/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5212 - accuracy: 0.7346\n",
            "Epoch 86/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5205 - accuracy: 0.7346\n",
            "Epoch 87/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5200 - accuracy: 0.7346\n",
            "Epoch 88/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5193 - accuracy: 0.7346\n",
            "Epoch 89/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5188 - accuracy: 0.7346\n",
            "Epoch 90/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5181 - accuracy: 0.7346\n",
            "Epoch 91/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5175 - accuracy: 0.7346\n",
            "Epoch 92/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.5168 - accuracy: 0.7346\n",
            "Epoch 93/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.5162 - accuracy: 0.7346\n",
            "Epoch 94/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5157 - accuracy: 0.7346\n",
            "Epoch 95/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5151 - accuracy: 0.7346\n",
            "Epoch 96/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5144 - accuracy: 0.7346\n",
            "Epoch 97/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5138 - accuracy: 0.7346\n",
            "Epoch 98/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5132 - accuracy: 0.7346\n",
            "Epoch 99/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5126 - accuracy: 0.7346\n",
            "Epoch 100/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5120 - accuracy: 0.7346\n",
            "Epoch 101/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5114 - accuracy: 0.7346\n",
            "Epoch 102/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5108 - accuracy: 0.7346\n",
            "Epoch 103/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5102 - accuracy: 0.7346\n",
            "Epoch 104/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5096 - accuracy: 0.7346\n",
            "Epoch 105/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5090 - accuracy: 0.7346\n",
            "Epoch 106/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5085 - accuracy: 0.7346\n",
            "Epoch 107/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5078 - accuracy: 0.7346\n",
            "Epoch 108/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.5073 - accuracy: 0.7346\n",
            "Epoch 109/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5067 - accuracy: 0.7346\n",
            "Epoch 110/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5061 - accuracy: 0.7346\n",
            "Epoch 111/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5055 - accuracy: 0.7346\n",
            "Epoch 112/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5049 - accuracy: 0.7346\n",
            "Epoch 113/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.5044 - accuracy: 0.7346\n",
            "Epoch 114/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5038 - accuracy: 0.7346\n",
            "Epoch 115/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5032 - accuracy: 0.7346\n",
            "Epoch 116/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5026 - accuracy: 0.7346\n",
            "Epoch 117/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5021 - accuracy: 0.7346\n",
            "Epoch 118/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5015 - accuracy: 0.7346\n",
            "Epoch 119/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5009 - accuracy: 0.7346\n",
            "Epoch 120/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.5004 - accuracy: 0.7346\n",
            "Epoch 121/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4999 - accuracy: 0.7346\n",
            "Epoch 122/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4993 - accuracy: 0.7346\n",
            "Epoch 123/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4988 - accuracy: 0.7346\n",
            "Epoch 124/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4982 - accuracy: 0.7346\n",
            "Epoch 125/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4976 - accuracy: 0.7346\n",
            "Epoch 126/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4971 - accuracy: 0.7346\n",
            "Epoch 127/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4966 - accuracy: 0.7346\n",
            "Epoch 128/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4960 - accuracy: 0.7346\n",
            "Epoch 129/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4955 - accuracy: 0.7346\n",
            "Epoch 130/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4949 - accuracy: 0.7346\n",
            "Epoch 131/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4944 - accuracy: 0.7348\n",
            "Epoch 132/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4939 - accuracy: 0.7351\n",
            "Epoch 133/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4933 - accuracy: 0.7351\n",
            "Epoch 134/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4927 - accuracy: 0.7355\n",
            "Epoch 135/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4922 - accuracy: 0.7355\n",
            "Epoch 136/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4917 - accuracy: 0.7356\n",
            "Epoch 137/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4912 - accuracy: 0.7360\n",
            "Epoch 138/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4907 - accuracy: 0.7356\n",
            "Epoch 139/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4902 - accuracy: 0.7360\n",
            "Epoch 140/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4897 - accuracy: 0.7360\n",
            "Epoch 141/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4891 - accuracy: 0.7360\n",
            "Epoch 142/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4886 - accuracy: 0.7367\n",
            "Epoch 143/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4881 - accuracy: 0.7367\n",
            "Epoch 144/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4876 - accuracy: 0.7367\n",
            "Epoch 145/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4872 - accuracy: 0.7378\n",
            "Epoch 146/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4866 - accuracy: 0.7385\n",
            "Epoch 147/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4861 - accuracy: 0.7380\n",
            "Epoch 148/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4856 - accuracy: 0.7380\n",
            "Epoch 149/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4852 - accuracy: 0.7369\n",
            "Epoch 150/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4847 - accuracy: 0.7387\n",
            "Epoch 151/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4842 - accuracy: 0.7388\n",
            "Epoch 152/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4837 - accuracy: 0.7385\n",
            "Epoch 153/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4832 - accuracy: 0.7392\n",
            "Epoch 154/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4827 - accuracy: 0.7396\n",
            "Epoch 155/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4823 - accuracy: 0.7399\n",
            "Epoch 156/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4818 - accuracy: 0.7394\n",
            "Epoch 157/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4813 - accuracy: 0.7396\n",
            "Epoch 158/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4809 - accuracy: 0.7404\n",
            "Epoch 159/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4804 - accuracy: 0.7404\n",
            "Epoch 160/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4799 - accuracy: 0.7415\n",
            "Epoch 161/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4794 - accuracy: 0.7415\n",
            "Epoch 162/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4790 - accuracy: 0.7420\n",
            "Epoch 163/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4785 - accuracy: 0.7424\n",
            "Epoch 164/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4781 - accuracy: 0.7431\n",
            "Epoch 165/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4777 - accuracy: 0.7444\n",
            "Epoch 166/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4772 - accuracy: 0.7449\n",
            "Epoch 167/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4767 - accuracy: 0.7452\n",
            "Epoch 168/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4763 - accuracy: 0.7461\n",
            "Epoch 169/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4758 - accuracy: 0.7472\n",
            "Epoch 170/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4754 - accuracy: 0.7474\n",
            "Epoch 171/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4750 - accuracy: 0.7468\n",
            "Epoch 172/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4746 - accuracy: 0.7477\n",
            "Epoch 173/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4741 - accuracy: 0.7497\n",
            "Epoch 174/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4737 - accuracy: 0.7474\n",
            "Epoch 175/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4733 - accuracy: 0.7477\n",
            "Epoch 176/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4729 - accuracy: 0.7499\n",
            "Epoch 177/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4725 - accuracy: 0.7500\n",
            "Epoch 178/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4721 - accuracy: 0.7488\n",
            "Epoch 179/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4716 - accuracy: 0.7495\n",
            "Epoch 180/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4712 - accuracy: 0.7499\n",
            "Epoch 181/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4708 - accuracy: 0.7527\n",
            "Epoch 182/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4704 - accuracy: 0.7543\n",
            "Epoch 183/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4700 - accuracy: 0.7557\n",
            "Epoch 184/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4696 - accuracy: 0.7557\n",
            "Epoch 185/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4692 - accuracy: 0.7563\n",
            "Epoch 186/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4688 - accuracy: 0.7579\n",
            "Epoch 187/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4684 - accuracy: 0.7577\n",
            "Epoch 188/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4680 - accuracy: 0.7582\n",
            "Epoch 189/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4677 - accuracy: 0.7604\n",
            "Epoch 190/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4673 - accuracy: 0.7591\n",
            "Epoch 191/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4669 - accuracy: 0.7595\n",
            "Epoch 192/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4665 - accuracy: 0.7604\n",
            "Epoch 193/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4662 - accuracy: 0.7604\n",
            "Epoch 194/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4658 - accuracy: 0.7602\n",
            "Epoch 195/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4655 - accuracy: 0.7612\n",
            "Epoch 196/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4650 - accuracy: 0.7630\n",
            "Epoch 197/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4647 - accuracy: 0.7653\n",
            "Epoch 198/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4643 - accuracy: 0.7641\n",
            "Epoch 199/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4640 - accuracy: 0.7657\n",
            "Epoch 200/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4636 - accuracy: 0.7650\n",
            "Epoch 201/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4632 - accuracy: 0.7655\n",
            "Epoch 202/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4629 - accuracy: 0.7657\n",
            "Epoch 203/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4626 - accuracy: 0.7652\n",
            "Epoch 204/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4622 - accuracy: 0.7659\n",
            "Epoch 205/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4619 - accuracy: 0.7673\n",
            "Epoch 206/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4615 - accuracy: 0.7685\n",
            "Epoch 207/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4612 - accuracy: 0.7698\n",
            "Epoch 208/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4608 - accuracy: 0.7675\n",
            "Epoch 209/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4605 - accuracy: 0.7703\n",
            "Epoch 210/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4602 - accuracy: 0.7703\n",
            "Epoch 211/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4598 - accuracy: 0.7701\n",
            "Epoch 212/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4595 - accuracy: 0.7705\n",
            "Epoch 213/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4592 - accuracy: 0.7710\n",
            "Epoch 214/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4589 - accuracy: 0.7707\n",
            "Epoch 215/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4586 - accuracy: 0.7712\n",
            "Epoch 216/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4582 - accuracy: 0.7714\n",
            "Epoch 217/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4579 - accuracy: 0.7710\n",
            "Epoch 218/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4576 - accuracy: 0.7728\n",
            "Epoch 219/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4573 - accuracy: 0.7742\n",
            "Epoch 220/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4570 - accuracy: 0.7726\n",
            "Epoch 221/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4567 - accuracy: 0.7723\n",
            "Epoch 222/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4564 - accuracy: 0.7744\n",
            "Epoch 223/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4561 - accuracy: 0.7755\n",
            "Epoch 224/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4558 - accuracy: 0.7776\n",
            "Epoch 225/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4555 - accuracy: 0.7774\n",
            "Epoch 226/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4552 - accuracy: 0.7756\n",
            "Epoch 227/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4550 - accuracy: 0.7758\n",
            "Epoch 228/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4547 - accuracy: 0.7772\n",
            "Epoch 229/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4544 - accuracy: 0.7771\n",
            "Epoch 230/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4542 - accuracy: 0.7767\n",
            "Epoch 231/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4538 - accuracy: 0.7787\n",
            "Epoch 232/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4535 - accuracy: 0.7785\n",
            "Epoch 233/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4533 - accuracy: 0.7788\n",
            "Epoch 234/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4530 - accuracy: 0.7781\n",
            "Epoch 235/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4528 - accuracy: 0.7774\n",
            "Epoch 236/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4525 - accuracy: 0.7790\n",
            "Epoch 237/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4522 - accuracy: 0.7797\n",
            "Epoch 238/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4519 - accuracy: 0.7797\n",
            "Epoch 239/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4517 - accuracy: 0.7797\n",
            "Epoch 240/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4515 - accuracy: 0.7808\n",
            "Epoch 241/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4512 - accuracy: 0.7801\n",
            "Epoch 242/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4509 - accuracy: 0.7808\n",
            "Epoch 243/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4507 - accuracy: 0.7801\n",
            "Epoch 244/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4504 - accuracy: 0.7810\n",
            "Epoch 245/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4501 - accuracy: 0.7808\n",
            "Epoch 246/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4499 - accuracy: 0.7808\n",
            "Epoch 247/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4497 - accuracy: 0.7813\n",
            "Epoch 248/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4494 - accuracy: 0.7801\n",
            "Epoch 249/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4492 - accuracy: 0.7819\n",
            "Epoch 250/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4489 - accuracy: 0.7806\n",
            "Epoch 251/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4487 - accuracy: 0.7806\n",
            "Epoch 252/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4485 - accuracy: 0.7812\n",
            "Epoch 253/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4482 - accuracy: 0.7828\n",
            "Epoch 254/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4480 - accuracy: 0.7829\n",
            "Epoch 255/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4478 - accuracy: 0.7826\n",
            "Epoch 256/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4475 - accuracy: 0.7824\n",
            "Epoch 257/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4473 - accuracy: 0.7835\n",
            "Epoch 258/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4471 - accuracy: 0.7826\n",
            "Epoch 259/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4469 - accuracy: 0.7826\n",
            "Epoch 260/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4467 - accuracy: 0.7831\n",
            "Epoch 261/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4464 - accuracy: 0.7826\n",
            "Epoch 262/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4462 - accuracy: 0.7829\n",
            "Epoch 263/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4460 - accuracy: 0.7822\n",
            "Epoch 264/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4458 - accuracy: 0.7829\n",
            "Epoch 265/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4456 - accuracy: 0.7847\n",
            "Epoch 266/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4454 - accuracy: 0.7835\n",
            "Epoch 267/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4452 - accuracy: 0.7828\n",
            "Epoch 268/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4450 - accuracy: 0.7840\n",
            "Epoch 269/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4447 - accuracy: 0.7847\n",
            "Epoch 270/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4445 - accuracy: 0.7847\n",
            "Epoch 271/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4443 - accuracy: 0.7852\n",
            "Epoch 272/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4442 - accuracy: 0.7854\n",
            "Epoch 273/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4440 - accuracy: 0.7842\n",
            "Epoch 274/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4438 - accuracy: 0.7845\n",
            "Epoch 275/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4436 - accuracy: 0.7842\n",
            "Epoch 276/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4434 - accuracy: 0.7844\n",
            "Epoch 277/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4432 - accuracy: 0.7849\n",
            "Epoch 278/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4430 - accuracy: 0.7845\n",
            "Epoch 279/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4429 - accuracy: 0.7844\n",
            "Epoch 280/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4427 - accuracy: 0.7851\n",
            "Epoch 281/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4425 - accuracy: 0.7852\n",
            "Epoch 282/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4423 - accuracy: 0.7849\n",
            "Epoch 283/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4421 - accuracy: 0.7854\n",
            "Epoch 284/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4420 - accuracy: 0.7847\n",
            "Epoch 285/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4418 - accuracy: 0.7847\n",
            "Epoch 286/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4416 - accuracy: 0.7852\n",
            "Epoch 287/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4414 - accuracy: 0.7851\n",
            "Epoch 288/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4413 - accuracy: 0.7852\n",
            "Epoch 289/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4411 - accuracy: 0.7854\n",
            "Epoch 290/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4410 - accuracy: 0.7845\n",
            "Epoch 291/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4408 - accuracy: 0.7851\n",
            "Epoch 292/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4406 - accuracy: 0.7851\n",
            "Epoch 293/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4405 - accuracy: 0.7858\n",
            "Epoch 294/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4403 - accuracy: 0.7858\n",
            "Epoch 295/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4401 - accuracy: 0.7860\n",
            "Epoch 296/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4400 - accuracy: 0.7861\n",
            "Epoch 297/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4398 - accuracy: 0.7856\n",
            "Epoch 298/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4396 - accuracy: 0.7849\n",
            "Epoch 299/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4395 - accuracy: 0.7858\n",
            "Epoch 300/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4394 - accuracy: 0.7863\n",
            "Epoch 301/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4392 - accuracy: 0.7861\n",
            "Epoch 302/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4391 - accuracy: 0.7860\n",
            "Epoch 303/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4389 - accuracy: 0.7858\n",
            "Epoch 304/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4388 - accuracy: 0.7861\n",
            "Epoch 305/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4386 - accuracy: 0.7867\n",
            "Epoch 306/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4384 - accuracy: 0.7867\n",
            "Epoch 307/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4383 - accuracy: 0.7865\n",
            "Epoch 308/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4382 - accuracy: 0.7872\n",
            "Epoch 309/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4380 - accuracy: 0.7872\n",
            "Epoch 310/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4379 - accuracy: 0.7870\n",
            "Epoch 311/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4378 - accuracy: 0.7867\n",
            "Epoch 312/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4376 - accuracy: 0.7874\n",
            "Epoch 313/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4375 - accuracy: 0.7865\n",
            "Epoch 314/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4374 - accuracy: 0.7874\n",
            "Epoch 315/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4372 - accuracy: 0.7870\n",
            "Epoch 316/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4371 - accuracy: 0.7872\n",
            "Epoch 317/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4370 - accuracy: 0.7874\n",
            "Epoch 318/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4368 - accuracy: 0.7874\n",
            "Epoch 319/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4367 - accuracy: 0.7877\n",
            "Epoch 320/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4366 - accuracy: 0.7870\n",
            "Epoch 321/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4365 - accuracy: 0.7872\n",
            "Epoch 322/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4363 - accuracy: 0.7872\n",
            "Epoch 323/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4362 - accuracy: 0.7877\n",
            "Epoch 324/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4361 - accuracy: 0.7876\n",
            "Epoch 325/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4360 - accuracy: 0.7876\n",
            "Epoch 326/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4358 - accuracy: 0.7879\n",
            "Epoch 327/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4357 - accuracy: 0.7884\n",
            "Epoch 328/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4356 - accuracy: 0.7886\n",
            "Epoch 329/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4355 - accuracy: 0.7879\n",
            "Epoch 330/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4354 - accuracy: 0.7895\n",
            "Epoch 331/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4353 - accuracy: 0.7895\n",
            "Epoch 332/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4352 - accuracy: 0.7899\n",
            "Epoch 333/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4351 - accuracy: 0.7893\n",
            "Epoch 334/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4349 - accuracy: 0.7906\n",
            "Epoch 335/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4348 - accuracy: 0.7899\n",
            "Epoch 336/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4347 - accuracy: 0.7902\n",
            "Epoch 337/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4346 - accuracy: 0.7900\n",
            "Epoch 338/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4345 - accuracy: 0.7916\n",
            "Epoch 339/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4344 - accuracy: 0.7900\n",
            "Epoch 340/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4343 - accuracy: 0.7895\n",
            "Epoch 341/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4342 - accuracy: 0.7902\n",
            "Epoch 342/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4341 - accuracy: 0.7904\n",
            "Epoch 343/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4340 - accuracy: 0.7900\n",
            "Epoch 344/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4339 - accuracy: 0.7902\n",
            "Epoch 345/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4338 - accuracy: 0.7892\n",
            "Epoch 346/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4337 - accuracy: 0.7913\n",
            "Epoch 347/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4336 - accuracy: 0.7920\n",
            "Epoch 348/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4335 - accuracy: 0.7922\n",
            "Epoch 349/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4334 - accuracy: 0.7911\n",
            "Epoch 350/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4333 - accuracy: 0.7915\n",
            "Epoch 351/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4332 - accuracy: 0.7916\n",
            "Epoch 352/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4331 - accuracy: 0.7913\n",
            "Epoch 353/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4330 - accuracy: 0.7906\n",
            "Epoch 354/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4329 - accuracy: 0.7918\n",
            "Epoch 355/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4328 - accuracy: 0.7920\n",
            "Epoch 356/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4328 - accuracy: 0.7925\n",
            "Epoch 357/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4327 - accuracy: 0.7922\n",
            "Epoch 358/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4325 - accuracy: 0.7924\n",
            "Epoch 359/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4325 - accuracy: 0.7924\n",
            "Epoch 360/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4324 - accuracy: 0.7920\n",
            "Epoch 361/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4323 - accuracy: 0.7929\n",
            "Epoch 362/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4322 - accuracy: 0.7924\n",
            "Epoch 363/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4321 - accuracy: 0.7920\n",
            "Epoch 364/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4320 - accuracy: 0.7927\n",
            "Epoch 365/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4320 - accuracy: 0.7924\n",
            "Epoch 366/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4319 - accuracy: 0.7925\n",
            "Epoch 367/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4318 - accuracy: 0.7915\n",
            "Epoch 368/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4317 - accuracy: 0.7924\n",
            "Epoch 369/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4316 - accuracy: 0.7920\n",
            "Epoch 370/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4315 - accuracy: 0.7925\n",
            "Epoch 371/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4315 - accuracy: 0.7918\n",
            "Epoch 372/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4314 - accuracy: 0.7916\n",
            "Epoch 373/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4313 - accuracy: 0.7916\n",
            "Epoch 374/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4312 - accuracy: 0.7924\n",
            "Epoch 375/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4311 - accuracy: 0.7920\n",
            "Epoch 376/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4310 - accuracy: 0.7916\n",
            "Epoch 377/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4310 - accuracy: 0.7913\n",
            "Epoch 378/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4309 - accuracy: 0.7925\n",
            "Epoch 379/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4308 - accuracy: 0.7922\n",
            "Epoch 380/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4308 - accuracy: 0.7927\n",
            "Epoch 381/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4307 - accuracy: 0.7924\n",
            "Epoch 382/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4306 - accuracy: 0.7924\n",
            "Epoch 383/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4306 - accuracy: 0.7920\n",
            "Epoch 384/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4305 - accuracy: 0.7920\n",
            "Epoch 385/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4304 - accuracy: 0.7931\n",
            "Epoch 386/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4303 - accuracy: 0.7931\n",
            "Epoch 387/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4302 - accuracy: 0.7925\n",
            "Epoch 388/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4302 - accuracy: 0.7931\n",
            "Epoch 389/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4301 - accuracy: 0.7940\n",
            "Epoch 390/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4301 - accuracy: 0.7934\n",
            "Epoch 391/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4300 - accuracy: 0.7934\n",
            "Epoch 392/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4299 - accuracy: 0.7938\n",
            "Epoch 393/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4298 - accuracy: 0.7938\n",
            "Epoch 394/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4298 - accuracy: 0.7938\n",
            "Epoch 395/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4297 - accuracy: 0.7932\n",
            "Epoch 396/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4297 - accuracy: 0.7934\n",
            "Epoch 397/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4296 - accuracy: 0.7929\n",
            "Epoch 398/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4295 - accuracy: 0.7934\n",
            "Epoch 399/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4295 - accuracy: 0.7932\n",
            "Epoch 400/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4294 - accuracy: 0.7936\n",
            "Epoch 401/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4293 - accuracy: 0.7940\n",
            "Epoch 402/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4293 - accuracy: 0.7938\n",
            "Epoch 403/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4292 - accuracy: 0.7934\n",
            "Epoch 404/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4292 - accuracy: 0.7936\n",
            "Epoch 405/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4291 - accuracy: 0.7940\n",
            "Epoch 406/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4291 - accuracy: 0.7934\n",
            "Epoch 407/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4290 - accuracy: 0.7936\n",
            "Epoch 408/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4289 - accuracy: 0.7934\n",
            "Epoch 409/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4288 - accuracy: 0.7932\n",
            "Epoch 410/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4288 - accuracy: 0.7941\n",
            "Epoch 411/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4287 - accuracy: 0.7940\n",
            "Epoch 412/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4287 - accuracy: 0.7943\n",
            "Epoch 413/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4286 - accuracy: 0.7938\n",
            "Epoch 414/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4286 - accuracy: 0.7940\n",
            "Epoch 415/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4286 - accuracy: 0.7947\n",
            "Epoch 416/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4285 - accuracy: 0.7947\n",
            "Epoch 417/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4284 - accuracy: 0.7936\n",
            "Epoch 418/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4284 - accuracy: 0.7943\n",
            "Epoch 419/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4283 - accuracy: 0.7940\n",
            "Epoch 420/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4282 - accuracy: 0.7936\n",
            "Epoch 421/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4282 - accuracy: 0.7932\n",
            "Epoch 422/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4282 - accuracy: 0.7940\n",
            "Epoch 423/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4281 - accuracy: 0.7934\n",
            "Epoch 424/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4281 - accuracy: 0.7938\n",
            "Epoch 425/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4280 - accuracy: 0.7936\n",
            "Epoch 426/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4280 - accuracy: 0.7941\n",
            "Epoch 427/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4279 - accuracy: 0.7932\n",
            "Epoch 428/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4279 - accuracy: 0.7948\n",
            "Epoch 429/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4278 - accuracy: 0.7950\n",
            "Epoch 430/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4277 - accuracy: 0.7941\n",
            "Epoch 431/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4277 - accuracy: 0.7954\n",
            "Epoch 432/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4277 - accuracy: 0.7950\n",
            "Epoch 433/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4276 - accuracy: 0.7929\n",
            "Epoch 434/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4276 - accuracy: 0.7941\n",
            "Epoch 435/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4275 - accuracy: 0.7954\n",
            "Epoch 436/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4275 - accuracy: 0.7954\n",
            "Epoch 437/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4274 - accuracy: 0.7952\n",
            "Epoch 438/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4274 - accuracy: 0.7950\n",
            "Epoch 439/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4273 - accuracy: 0.7954\n",
            "Epoch 440/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4273 - accuracy: 0.7950\n",
            "Epoch 441/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4272 - accuracy: 0.7952\n",
            "Epoch 442/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4272 - accuracy: 0.7948\n",
            "Epoch 443/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4271 - accuracy: 0.7948\n",
            "Epoch 444/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4271 - accuracy: 0.7948\n",
            "Epoch 445/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4270 - accuracy: 0.7956\n",
            "Epoch 446/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4270 - accuracy: 0.7956\n",
            "Epoch 447/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4270 - accuracy: 0.7952\n",
            "Epoch 448/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4269 - accuracy: 0.7954\n",
            "Epoch 449/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4269 - accuracy: 0.7952\n",
            "Epoch 450/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4269 - accuracy: 0.7952\n",
            "Epoch 451/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4268 - accuracy: 0.7954\n",
            "Epoch 452/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4268 - accuracy: 0.7952\n",
            "Epoch 453/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4267 - accuracy: 0.7950\n",
            "Epoch 454/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4267 - accuracy: 0.7954\n",
            "Epoch 455/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4267 - accuracy: 0.7957\n",
            "Epoch 456/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4266 - accuracy: 0.7950\n",
            "Epoch 457/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4266 - accuracy: 0.7948\n",
            "Epoch 458/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4265 - accuracy: 0.7952\n",
            "Epoch 459/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4266 - accuracy: 0.7954\n",
            "Epoch 460/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4265 - accuracy: 0.7952\n",
            "Epoch 461/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4264 - accuracy: 0.7952\n",
            "Epoch 462/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4264 - accuracy: 0.7945\n",
            "Epoch 463/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4264 - accuracy: 0.7941\n",
            "Epoch 464/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4263 - accuracy: 0.7956\n",
            "Epoch 465/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4263 - accuracy: 0.7952\n",
            "Epoch 466/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4262 - accuracy: 0.7947\n",
            "Epoch 467/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4262 - accuracy: 0.7948\n",
            "Epoch 468/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4261 - accuracy: 0.7950\n",
            "Epoch 469/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4261 - accuracy: 0.7956\n",
            "Epoch 470/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4261 - accuracy: 0.7956\n",
            "Epoch 471/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4261 - accuracy: 0.7950\n",
            "Epoch 472/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4260 - accuracy: 0.7950\n",
            "Epoch 473/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4260 - accuracy: 0.7952\n",
            "Epoch 474/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4259 - accuracy: 0.7952\n",
            "Epoch 475/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4259 - accuracy: 0.7956\n",
            "Epoch 476/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4259 - accuracy: 0.7956\n",
            "Epoch 477/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4258 - accuracy: 0.7954\n",
            "Epoch 478/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4258 - accuracy: 0.7952\n",
            "Epoch 479/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4257 - accuracy: 0.7956\n",
            "Epoch 480/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4257 - accuracy: 0.7954\n",
            "Epoch 481/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4257 - accuracy: 0.7952\n",
            "Epoch 482/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4257 - accuracy: 0.7956\n",
            "Epoch 483/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4256 - accuracy: 0.7957\n",
            "Epoch 484/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4256 - accuracy: 0.7956\n",
            "Epoch 485/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4256 - accuracy: 0.7954\n",
            "Epoch 486/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4255 - accuracy: 0.7947\n",
            "Epoch 487/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4255 - accuracy: 0.7956\n",
            "Epoch 488/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4255 - accuracy: 0.7959\n",
            "Epoch 489/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4254 - accuracy: 0.7959\n",
            "Epoch 490/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4254 - accuracy: 0.7950\n",
            "Epoch 491/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4254 - accuracy: 0.7956\n",
            "Epoch 492/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4253 - accuracy: 0.7950\n",
            "Epoch 493/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4253 - accuracy: 0.7956\n",
            "Epoch 494/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4253 - accuracy: 0.7959\n",
            "Epoch 495/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4252 - accuracy: 0.7957\n",
            "Epoch 496/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4252 - accuracy: 0.7959\n",
            "Epoch 497/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4251 - accuracy: 0.7952\n",
            "Epoch 498/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4251 - accuracy: 0.7964\n",
            "Epoch 499/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4251 - accuracy: 0.7956\n",
            "Epoch 500/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4251 - accuracy: 0.7959\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.src.callbacks.History at 0x794fc77f4f70>"
            ]
          },
          "metadata": {},
          "execution_count": 408
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model3 = keras.Sequential([\n",
        "    keras.layers.Dense(100, input_shape=(27,), activation='sigmoid',kernel_initializer=tf.keras.initializers.GlorotUniform(seed=None)),\n",
        "    keras.layers.Dense(1,activation='sigmoid')\n",
        "])\n",
        "\n",
        "model3.compile(\n",
        "    optimizer='adam',\n",
        "    loss='binary_crossentropy',\n",
        "    metrics=['accuracy']\n",
        ")\n",
        "\n",
        "# Fit the model\n",
        "model3.fit(X_train, y_train, epochs=500, batch_size = 500)\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uoZ4qJ_0B_2p",
        "outputId": "00e4c5c6-aeba-435a-8485-a26307e22b2b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/500\n",
            "12/12 [==============================] - 1s 8ms/step - loss: 0.6219 - accuracy: 0.7136\n",
            "Epoch 2/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.5641 - accuracy: 0.7346\n",
            "Epoch 3/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.5430 - accuracy: 0.7346\n",
            "Epoch 4/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.5225 - accuracy: 0.7346\n",
            "Epoch 5/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.5062 - accuracy: 0.7346\n",
            "Epoch 6/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4918 - accuracy: 0.7356\n",
            "Epoch 7/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4796 - accuracy: 0.7454\n",
            "Epoch 8/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4694 - accuracy: 0.7547\n",
            "Epoch 9/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4607 - accuracy: 0.7692\n",
            "Epoch 10/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4536 - accuracy: 0.7781\n",
            "Epoch 11/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4476 - accuracy: 0.7844\n",
            "Epoch 12/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4429 - accuracy: 0.7867\n",
            "Epoch 13/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4392 - accuracy: 0.7925\n",
            "Epoch 14/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4359 - accuracy: 0.7925\n",
            "Epoch 15/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4335 - accuracy: 0.7929\n",
            "Epoch 16/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4314 - accuracy: 0.7947\n",
            "Epoch 17/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4297 - accuracy: 0.7968\n",
            "Epoch 18/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4283 - accuracy: 0.7964\n",
            "Epoch 19/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4271 - accuracy: 0.7963\n",
            "Epoch 20/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4260 - accuracy: 0.7980\n",
            "Epoch 21/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4250 - accuracy: 0.7982\n",
            "Epoch 22/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4248 - accuracy: 0.7972\n",
            "Epoch 23/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4235 - accuracy: 0.7998\n",
            "Epoch 24/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4232 - accuracy: 0.7970\n",
            "Epoch 25/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4223 - accuracy: 0.7991\n",
            "Epoch 26/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4219 - accuracy: 0.7984\n",
            "Epoch 27/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4211 - accuracy: 0.7998\n",
            "Epoch 28/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4208 - accuracy: 0.8011\n",
            "Epoch 29/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4203 - accuracy: 0.8023\n",
            "Epoch 30/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4199 - accuracy: 0.8020\n",
            "Epoch 31/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4196 - accuracy: 0.8007\n",
            "Epoch 32/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4192 - accuracy: 0.8028\n",
            "Epoch 33/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4189 - accuracy: 0.8034\n",
            "Epoch 34/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4187 - accuracy: 0.8037\n",
            "Epoch 35/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4185 - accuracy: 0.8039\n",
            "Epoch 36/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4181 - accuracy: 0.8041\n",
            "Epoch 37/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4180 - accuracy: 0.8034\n",
            "Epoch 38/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4180 - accuracy: 0.8039\n",
            "Epoch 39/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4175 - accuracy: 0.8041\n",
            "Epoch 40/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4173 - accuracy: 0.8044\n",
            "Epoch 41/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4171 - accuracy: 0.8039\n",
            "Epoch 42/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4170 - accuracy: 0.8048\n",
            "Epoch 43/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4168 - accuracy: 0.8044\n",
            "Epoch 44/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4167 - accuracy: 0.8055\n",
            "Epoch 45/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4167 - accuracy: 0.8062\n",
            "Epoch 46/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4164 - accuracy: 0.8055\n",
            "Epoch 47/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4164 - accuracy: 0.8060\n",
            "Epoch 48/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4162 - accuracy: 0.8048\n",
            "Epoch 49/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4161 - accuracy: 0.8055\n",
            "Epoch 50/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4164 - accuracy: 0.8039\n",
            "Epoch 51/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4161 - accuracy: 0.8052\n",
            "Epoch 52/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4163 - accuracy: 0.8055\n",
            "Epoch 53/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4161 - accuracy: 0.8062\n",
            "Epoch 54/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4155 - accuracy: 0.8068\n",
            "Epoch 55/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4156 - accuracy: 0.8060\n",
            "Epoch 56/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4164 - accuracy: 0.8039\n",
            "Epoch 57/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4157 - accuracy: 0.8052\n",
            "Epoch 58/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4159 - accuracy: 0.8048\n",
            "Epoch 59/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4153 - accuracy: 0.8060\n",
            "Epoch 60/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4155 - accuracy: 0.8062\n",
            "Epoch 61/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4151 - accuracy: 0.8071\n",
            "Epoch 62/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.4156 - accuracy: 0.8059\n",
            "Epoch 63/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4158 - accuracy: 0.8059\n",
            "Epoch 64/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4151 - accuracy: 0.8068\n",
            "Epoch 65/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4154 - accuracy: 0.8052\n",
            "Epoch 66/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4154 - accuracy: 0.8053\n",
            "Epoch 67/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4148 - accuracy: 0.8075\n",
            "Epoch 68/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.4151 - accuracy: 0.8064\n",
            "Epoch 69/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4148 - accuracy: 0.8076\n",
            "Epoch 70/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4147 - accuracy: 0.8076\n",
            "Epoch 71/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.4148 - accuracy: 0.8071\n",
            "Epoch 72/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4148 - accuracy: 0.8062\n",
            "Epoch 73/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4148 - accuracy: 0.8082\n",
            "Epoch 74/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4153 - accuracy: 0.8057\n",
            "Epoch 75/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4147 - accuracy: 0.8066\n",
            "Epoch 76/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4146 - accuracy: 0.8064\n",
            "Epoch 77/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4146 - accuracy: 0.8082\n",
            "Epoch 78/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4144 - accuracy: 0.8082\n",
            "Epoch 79/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4144 - accuracy: 0.8073\n",
            "Epoch 80/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4144 - accuracy: 0.8069\n",
            "Epoch 81/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4146 - accuracy: 0.8073\n",
            "Epoch 82/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4144 - accuracy: 0.8073\n",
            "Epoch 83/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4145 - accuracy: 0.8069\n",
            "Epoch 84/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4143 - accuracy: 0.8075\n",
            "Epoch 85/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4144 - accuracy: 0.8080\n",
            "Epoch 86/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4145 - accuracy: 0.8087\n",
            "Epoch 87/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4150 - accuracy: 0.8066\n",
            "Epoch 88/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4148 - accuracy: 0.8060\n",
            "Epoch 89/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4142 - accuracy: 0.8053\n",
            "Epoch 90/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4144 - accuracy: 0.8071\n",
            "Epoch 91/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4142 - accuracy: 0.8069\n",
            "Epoch 92/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4143 - accuracy: 0.8062\n",
            "Epoch 93/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4141 - accuracy: 0.8069\n",
            "Epoch 94/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4141 - accuracy: 0.8082\n",
            "Epoch 95/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4141 - accuracy: 0.8082\n",
            "Epoch 96/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4153 - accuracy: 0.8059\n",
            "Epoch 97/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4145 - accuracy: 0.8080\n",
            "Epoch 98/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4142 - accuracy: 0.8084\n",
            "Epoch 99/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4141 - accuracy: 0.8071\n",
            "Epoch 100/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4140 - accuracy: 0.8082\n",
            "Epoch 101/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4140 - accuracy: 0.8087\n",
            "Epoch 102/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4139 - accuracy: 0.8076\n",
            "Epoch 103/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4140 - accuracy: 0.8069\n",
            "Epoch 104/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4140 - accuracy: 0.8080\n",
            "Epoch 105/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4147 - accuracy: 0.8071\n",
            "Epoch 106/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4145 - accuracy: 0.8078\n",
            "Epoch 107/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4141 - accuracy: 0.8068\n",
            "Epoch 108/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4139 - accuracy: 0.8066\n",
            "Epoch 109/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4139 - accuracy: 0.8071\n",
            "Epoch 110/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4138 - accuracy: 0.8075\n",
            "Epoch 111/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4137 - accuracy: 0.8078\n",
            "Epoch 112/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4138 - accuracy: 0.8066\n",
            "Epoch 113/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4137 - accuracy: 0.8062\n",
            "Epoch 114/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4138 - accuracy: 0.8069\n",
            "Epoch 115/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4138 - accuracy: 0.8078\n",
            "Epoch 116/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4139 - accuracy: 0.8068\n",
            "Epoch 117/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4140 - accuracy: 0.8073\n",
            "Epoch 118/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4140 - accuracy: 0.8075\n",
            "Epoch 119/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4138 - accuracy: 0.8075\n",
            "Epoch 120/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4136 - accuracy: 0.8091\n",
            "Epoch 121/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4139 - accuracy: 0.8085\n",
            "Epoch 122/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4137 - accuracy: 0.8071\n",
            "Epoch 123/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4136 - accuracy: 0.8076\n",
            "Epoch 124/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4136 - accuracy: 0.8078\n",
            "Epoch 125/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4135 - accuracy: 0.8082\n",
            "Epoch 126/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4137 - accuracy: 0.8076\n",
            "Epoch 127/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4141 - accuracy: 0.8060\n",
            "Epoch 128/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4139 - accuracy: 0.8073\n",
            "Epoch 129/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4142 - accuracy: 0.8059\n",
            "Epoch 130/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4134 - accuracy: 0.8066\n",
            "Epoch 131/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4137 - accuracy: 0.8091\n",
            "Epoch 132/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4134 - accuracy: 0.8076\n",
            "Epoch 133/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4135 - accuracy: 0.8075\n",
            "Epoch 134/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4139 - accuracy: 0.8075\n",
            "Epoch 135/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4135 - accuracy: 0.8071\n",
            "Epoch 136/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4133 - accuracy: 0.8076\n",
            "Epoch 137/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4136 - accuracy: 0.8055\n",
            "Epoch 138/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4132 - accuracy: 0.8078\n",
            "Epoch 139/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4132 - accuracy: 0.8080\n",
            "Epoch 140/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4132 - accuracy: 0.8080\n",
            "Epoch 141/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4134 - accuracy: 0.8066\n",
            "Epoch 142/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4132 - accuracy: 0.8069\n",
            "Epoch 143/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4132 - accuracy: 0.8089\n",
            "Epoch 144/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4146 - accuracy: 0.8085\n",
            "Epoch 145/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4143 - accuracy: 0.8060\n",
            "Epoch 146/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4131 - accuracy: 0.8087\n",
            "Epoch 147/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4131 - accuracy: 0.8096\n",
            "Epoch 148/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4130 - accuracy: 0.8085\n",
            "Epoch 149/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4132 - accuracy: 0.8076\n",
            "Epoch 150/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4130 - accuracy: 0.8078\n",
            "Epoch 151/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4133 - accuracy: 0.8057\n",
            "Epoch 152/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4132 - accuracy: 0.8092\n",
            "Epoch 153/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4134 - accuracy: 0.8069\n",
            "Epoch 154/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.4143 - accuracy: 0.8068\n",
            "Epoch 155/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.4129 - accuracy: 0.8071\n",
            "Epoch 156/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4130 - accuracy: 0.8084\n",
            "Epoch 157/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4128 - accuracy: 0.8087\n",
            "Epoch 158/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4133 - accuracy: 0.8098\n",
            "Epoch 159/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4127 - accuracy: 0.8075\n",
            "Epoch 160/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4128 - accuracy: 0.8084\n",
            "Epoch 161/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4126 - accuracy: 0.8068\n",
            "Epoch 162/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4127 - accuracy: 0.8073\n",
            "Epoch 163/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4129 - accuracy: 0.8076\n",
            "Epoch 164/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4126 - accuracy: 0.8089\n",
            "Epoch 165/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4131 - accuracy: 0.8069\n",
            "Epoch 166/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4127 - accuracy: 0.8069\n",
            "Epoch 167/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4129 - accuracy: 0.8075\n",
            "Epoch 168/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4132 - accuracy: 0.8062\n",
            "Epoch 169/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4136 - accuracy: 0.8075\n",
            "Epoch 170/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4126 - accuracy: 0.8089\n",
            "Epoch 171/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4125 - accuracy: 0.8092\n",
            "Epoch 172/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4125 - accuracy: 0.8089\n",
            "Epoch 173/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4124 - accuracy: 0.8082\n",
            "Epoch 174/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4127 - accuracy: 0.8087\n",
            "Epoch 175/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4129 - accuracy: 0.8092\n",
            "Epoch 176/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4128 - accuracy: 0.8092\n",
            "Epoch 177/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4126 - accuracy: 0.8085\n",
            "Epoch 178/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4123 - accuracy: 0.8094\n",
            "Epoch 179/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4124 - accuracy: 0.8085\n",
            "Epoch 180/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4123 - accuracy: 0.8098\n",
            "Epoch 181/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4123 - accuracy: 0.8087\n",
            "Epoch 182/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4124 - accuracy: 0.8084\n",
            "Epoch 183/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4126 - accuracy: 0.8082\n",
            "Epoch 184/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4121 - accuracy: 0.8085\n",
            "Epoch 185/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4122 - accuracy: 0.8080\n",
            "Epoch 186/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4127 - accuracy: 0.8078\n",
            "Epoch 187/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4120 - accuracy: 0.8094\n",
            "Epoch 188/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4121 - accuracy: 0.8084\n",
            "Epoch 189/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4119 - accuracy: 0.8076\n",
            "Epoch 190/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.4119 - accuracy: 0.8087\n",
            "Epoch 191/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.4122 - accuracy: 0.8087\n",
            "Epoch 192/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4120 - accuracy: 0.8087\n",
            "Epoch 193/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4125 - accuracy: 0.8094\n",
            "Epoch 194/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4119 - accuracy: 0.8094\n",
            "Epoch 195/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.4118 - accuracy: 0.8078\n",
            "Epoch 196/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.4118 - accuracy: 0.8087\n",
            "Epoch 197/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.4129 - accuracy: 0.8069\n",
            "Epoch 198/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.4123 - accuracy: 0.8094\n",
            "Epoch 199/500\n",
            "12/12 [==============================] - 0s 18ms/step - loss: 0.4121 - accuracy: 0.8092\n",
            "Epoch 200/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.4121 - accuracy: 0.8078\n",
            "Epoch 201/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4122 - accuracy: 0.8080\n",
            "Epoch 202/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.4117 - accuracy: 0.8085\n",
            "Epoch 203/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4122 - accuracy: 0.8076\n",
            "Epoch 204/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4118 - accuracy: 0.8078\n",
            "Epoch 205/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4115 - accuracy: 0.8082\n",
            "Epoch 206/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4114 - accuracy: 0.8087\n",
            "Epoch 207/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.4116 - accuracy: 0.8085\n",
            "Epoch 208/500\n",
            "12/12 [==============================] - 0s 14ms/step - loss: 0.4114 - accuracy: 0.8082\n",
            "Epoch 209/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.4114 - accuracy: 0.8096\n",
            "Epoch 210/500\n",
            "12/12 [==============================] - 0s 19ms/step - loss: 0.4113 - accuracy: 0.8092\n",
            "Epoch 211/500\n",
            "12/12 [==============================] - 0s 19ms/step - loss: 0.4112 - accuracy: 0.8089\n",
            "Epoch 212/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4115 - accuracy: 0.8080\n",
            "Epoch 213/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.4114 - accuracy: 0.8098\n",
            "Epoch 214/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4114 - accuracy: 0.8092\n",
            "Epoch 215/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4113 - accuracy: 0.8087\n",
            "Epoch 216/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4116 - accuracy: 0.8089\n",
            "Epoch 217/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4116 - accuracy: 0.8092\n",
            "Epoch 218/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4120 - accuracy: 0.8084\n",
            "Epoch 219/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4126 - accuracy: 0.8085\n",
            "Epoch 220/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4115 - accuracy: 0.8073\n",
            "Epoch 221/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.4109 - accuracy: 0.8087\n",
            "Epoch 222/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.4110 - accuracy: 0.8082\n",
            "Epoch 223/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.4116 - accuracy: 0.8085\n",
            "Epoch 224/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.4117 - accuracy: 0.8055\n",
            "Epoch 225/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4110 - accuracy: 0.8087\n",
            "Epoch 226/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4109 - accuracy: 0.8082\n",
            "Epoch 227/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4112 - accuracy: 0.8100\n",
            "Epoch 228/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4113 - accuracy: 0.8085\n",
            "Epoch 229/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.4108 - accuracy: 0.8084\n",
            "Epoch 230/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4108 - accuracy: 0.8089\n",
            "Epoch 231/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.4108 - accuracy: 0.8085\n",
            "Epoch 232/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.4107 - accuracy: 0.8076\n",
            "Epoch 233/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.4109 - accuracy: 0.8080\n",
            "Epoch 234/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4108 - accuracy: 0.8091\n",
            "Epoch 235/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4110 - accuracy: 0.8092\n",
            "Epoch 236/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4110 - accuracy: 0.8092\n",
            "Epoch 237/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4105 - accuracy: 0.8084\n",
            "Epoch 238/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4108 - accuracy: 0.8092\n",
            "Epoch 239/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4108 - accuracy: 0.8098\n",
            "Epoch 240/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4107 - accuracy: 0.8082\n",
            "Epoch 241/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4105 - accuracy: 0.8094\n",
            "Epoch 242/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4113 - accuracy: 0.8092\n",
            "Epoch 243/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.4107 - accuracy: 0.8082\n",
            "Epoch 244/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.4104 - accuracy: 0.8075\n",
            "Epoch 245/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4106 - accuracy: 0.8107\n",
            "Epoch 246/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4107 - accuracy: 0.8082\n",
            "Epoch 247/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4102 - accuracy: 0.8075\n",
            "Epoch 248/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.4103 - accuracy: 0.8085\n",
            "Epoch 249/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4101 - accuracy: 0.8092\n",
            "Epoch 250/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4101 - accuracy: 0.8084\n",
            "Epoch 251/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.4105 - accuracy: 0.8082\n",
            "Epoch 252/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4103 - accuracy: 0.8091\n",
            "Epoch 253/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4104 - accuracy: 0.8084\n",
            "Epoch 254/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4102 - accuracy: 0.8076\n",
            "Epoch 255/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4102 - accuracy: 0.8073\n",
            "Epoch 256/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4101 - accuracy: 0.8069\n",
            "Epoch 257/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4105 - accuracy: 0.8078\n",
            "Epoch 258/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4114 - accuracy: 0.8094\n",
            "Epoch 259/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4109 - accuracy: 0.8069\n",
            "Epoch 260/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4100 - accuracy: 0.8107\n",
            "Epoch 261/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4105 - accuracy: 0.8087\n",
            "Epoch 262/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4099 - accuracy: 0.8100\n",
            "Epoch 263/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4102 - accuracy: 0.8078\n",
            "Epoch 264/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.4105 - accuracy: 0.8101\n",
            "Epoch 265/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4102 - accuracy: 0.8105\n",
            "Epoch 266/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4101 - accuracy: 0.8076\n",
            "Epoch 267/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4097 - accuracy: 0.8094\n",
            "Epoch 268/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4103 - accuracy: 0.8080\n",
            "Epoch 269/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4098 - accuracy: 0.8123\n",
            "Epoch 270/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4100 - accuracy: 0.8116\n",
            "Epoch 271/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4104 - accuracy: 0.8073\n",
            "Epoch 272/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4108 - accuracy: 0.8112\n",
            "Epoch 273/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4095 - accuracy: 0.8071\n",
            "Epoch 274/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4097 - accuracy: 0.8094\n",
            "Epoch 275/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4104 - accuracy: 0.8073\n",
            "Epoch 276/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4101 - accuracy: 0.8092\n",
            "Epoch 277/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4099 - accuracy: 0.8089\n",
            "Epoch 278/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4098 - accuracy: 0.8089\n",
            "Epoch 279/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.4095 - accuracy: 0.8085\n",
            "Epoch 280/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4094 - accuracy: 0.8084\n",
            "Epoch 281/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.4096 - accuracy: 0.8098\n",
            "Epoch 282/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4099 - accuracy: 0.8087\n",
            "Epoch 283/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.4094 - accuracy: 0.8098\n",
            "Epoch 284/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4093 - accuracy: 0.8092\n",
            "Epoch 285/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4098 - accuracy: 0.8087\n",
            "Epoch 286/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4100 - accuracy: 0.8103\n",
            "Epoch 287/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.4102 - accuracy: 0.8075\n",
            "Epoch 288/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.4093 - accuracy: 0.8103\n",
            "Epoch 289/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.4092 - accuracy: 0.8082\n",
            "Epoch 290/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4094 - accuracy: 0.8087\n",
            "Epoch 291/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4092 - accuracy: 0.8096\n",
            "Epoch 292/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4091 - accuracy: 0.8084\n",
            "Epoch 293/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4092 - accuracy: 0.8098\n",
            "Epoch 294/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4091 - accuracy: 0.8076\n",
            "Epoch 295/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4093 - accuracy: 0.8096\n",
            "Epoch 296/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4090 - accuracy: 0.8096\n",
            "Epoch 297/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4096 - accuracy: 0.8073\n",
            "Epoch 298/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4090 - accuracy: 0.8101\n",
            "Epoch 299/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4091 - accuracy: 0.8101\n",
            "Epoch 300/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4096 - accuracy: 0.8068\n",
            "Epoch 301/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4089 - accuracy: 0.8085\n",
            "Epoch 302/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4090 - accuracy: 0.8103\n",
            "Epoch 303/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4089 - accuracy: 0.8082\n",
            "Epoch 304/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4099 - accuracy: 0.8085\n",
            "Epoch 305/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4099 - accuracy: 0.8094\n",
            "Epoch 306/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4094 - accuracy: 0.8076\n",
            "Epoch 307/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4089 - accuracy: 0.8098\n",
            "Epoch 308/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4087 - accuracy: 0.8098\n",
            "Epoch 309/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4090 - accuracy: 0.8094\n",
            "Epoch 310/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4091 - accuracy: 0.8098\n",
            "Epoch 311/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4089 - accuracy: 0.8101\n",
            "Epoch 312/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4092 - accuracy: 0.8078\n",
            "Epoch 313/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4088 - accuracy: 0.8107\n",
            "Epoch 314/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4087 - accuracy: 0.8076\n",
            "Epoch 315/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4087 - accuracy: 0.8101\n",
            "Epoch 316/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4087 - accuracy: 0.8080\n",
            "Epoch 317/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4085 - accuracy: 0.8107\n",
            "Epoch 318/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4086 - accuracy: 0.8100\n",
            "Epoch 319/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4085 - accuracy: 0.8100\n",
            "Epoch 320/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4085 - accuracy: 0.8110\n",
            "Epoch 321/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4086 - accuracy: 0.8091\n",
            "Epoch 322/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4085 - accuracy: 0.8100\n",
            "Epoch 323/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4085 - accuracy: 0.8087\n",
            "Epoch 324/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4084 - accuracy: 0.8080\n",
            "Epoch 325/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4088 - accuracy: 0.8103\n",
            "Epoch 326/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4097 - accuracy: 0.8080\n",
            "Epoch 327/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4096 - accuracy: 0.8105\n",
            "Epoch 328/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4089 - accuracy: 0.8084\n",
            "Epoch 329/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4084 - accuracy: 0.8091\n",
            "Epoch 330/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4084 - accuracy: 0.8092\n",
            "Epoch 331/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4087 - accuracy: 0.8110\n",
            "Epoch 332/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4084 - accuracy: 0.8080\n",
            "Epoch 333/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4085 - accuracy: 0.8098\n",
            "Epoch 334/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4086 - accuracy: 0.8080\n",
            "Epoch 335/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4091 - accuracy: 0.8096\n",
            "Epoch 336/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4084 - accuracy: 0.8087\n",
            "Epoch 337/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4083 - accuracy: 0.8080\n",
            "Epoch 338/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4081 - accuracy: 0.8080\n",
            "Epoch 339/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4081 - accuracy: 0.8089\n",
            "Epoch 340/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4081 - accuracy: 0.8085\n",
            "Epoch 341/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4081 - accuracy: 0.8094\n",
            "Epoch 342/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4085 - accuracy: 0.8094\n",
            "Epoch 343/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4085 - accuracy: 0.8103\n",
            "Epoch 344/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4081 - accuracy: 0.8080\n",
            "Epoch 345/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4083 - accuracy: 0.8085\n",
            "Epoch 346/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4079 - accuracy: 0.8096\n",
            "Epoch 347/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4087 - accuracy: 0.8064\n",
            "Epoch 348/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4078 - accuracy: 0.8098\n",
            "Epoch 349/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4080 - accuracy: 0.8091\n",
            "Epoch 350/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4081 - accuracy: 0.8094\n",
            "Epoch 351/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4081 - accuracy: 0.8105\n",
            "Epoch 352/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4078 - accuracy: 0.8108\n",
            "Epoch 353/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4079 - accuracy: 0.8098\n",
            "Epoch 354/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4081 - accuracy: 0.8094\n",
            "Epoch 355/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4078 - accuracy: 0.8092\n",
            "Epoch 356/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4080 - accuracy: 0.8100\n",
            "Epoch 357/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4080 - accuracy: 0.8085\n",
            "Epoch 358/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4081 - accuracy: 0.8103\n",
            "Epoch 359/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4080 - accuracy: 0.8085\n",
            "Epoch 360/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4080 - accuracy: 0.8105\n",
            "Epoch 361/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4081 - accuracy: 0.8084\n",
            "Epoch 362/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4082 - accuracy: 0.8092\n",
            "Epoch 363/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4081 - accuracy: 0.8105\n",
            "Epoch 364/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4077 - accuracy: 0.8101\n",
            "Epoch 365/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4077 - accuracy: 0.8091\n",
            "Epoch 366/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4076 - accuracy: 0.8085\n",
            "Epoch 367/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4077 - accuracy: 0.8101\n",
            "Epoch 368/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4076 - accuracy: 0.8089\n",
            "Epoch 369/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4075 - accuracy: 0.8101\n",
            "Epoch 370/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4077 - accuracy: 0.8091\n",
            "Epoch 371/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4076 - accuracy: 0.8094\n",
            "Epoch 372/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4075 - accuracy: 0.8094\n",
            "Epoch 373/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4080 - accuracy: 0.8080\n",
            "Epoch 374/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4078 - accuracy: 0.8112\n",
            "Epoch 375/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4086 - accuracy: 0.8076\n",
            "Epoch 376/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4080 - accuracy: 0.8092\n",
            "Epoch 377/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4076 - accuracy: 0.8078\n",
            "Epoch 378/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4074 - accuracy: 0.8089\n",
            "Epoch 379/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4075 - accuracy: 0.8105\n",
            "Epoch 380/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4075 - accuracy: 0.8091\n",
            "Epoch 381/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4073 - accuracy: 0.8096\n",
            "Epoch 382/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4073 - accuracy: 0.8085\n",
            "Epoch 383/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4075 - accuracy: 0.8105\n",
            "Epoch 384/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4074 - accuracy: 0.8092\n",
            "Epoch 385/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4073 - accuracy: 0.8092\n",
            "Epoch 386/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4078 - accuracy: 0.8080\n",
            "Epoch 387/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4075 - accuracy: 0.8110\n",
            "Epoch 388/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4073 - accuracy: 0.8105\n",
            "Epoch 389/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4078 - accuracy: 0.8085\n",
            "Epoch 390/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4072 - accuracy: 0.8112\n",
            "Epoch 391/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4077 - accuracy: 0.8089\n",
            "Epoch 392/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4075 - accuracy: 0.8110\n",
            "Epoch 393/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4073 - accuracy: 0.8076\n",
            "Epoch 394/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4079 - accuracy: 0.8103\n",
            "Epoch 395/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4071 - accuracy: 0.8096\n",
            "Epoch 396/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4072 - accuracy: 0.8107\n",
            "Epoch 397/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4071 - accuracy: 0.8101\n",
            "Epoch 398/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4077 - accuracy: 0.8107\n",
            "Epoch 399/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4070 - accuracy: 0.8085\n",
            "Epoch 400/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4072 - accuracy: 0.8098\n",
            "Epoch 401/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4073 - accuracy: 0.8098\n",
            "Epoch 402/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4070 - accuracy: 0.8087\n",
            "Epoch 403/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4071 - accuracy: 0.8098\n",
            "Epoch 404/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4070 - accuracy: 0.8098\n",
            "Epoch 405/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4070 - accuracy: 0.8085\n",
            "Epoch 406/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4069 - accuracy: 0.8094\n",
            "Epoch 407/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4068 - accuracy: 0.8087\n",
            "Epoch 408/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4069 - accuracy: 0.8096\n",
            "Epoch 409/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4070 - accuracy: 0.8092\n",
            "Epoch 410/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4069 - accuracy: 0.8100\n",
            "Epoch 411/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4069 - accuracy: 0.8089\n",
            "Epoch 412/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4066 - accuracy: 0.8094\n",
            "Epoch 413/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4077 - accuracy: 0.8084\n",
            "Epoch 414/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4075 - accuracy: 0.8107\n",
            "Epoch 415/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4076 - accuracy: 0.8080\n",
            "Epoch 416/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4070 - accuracy: 0.8092\n",
            "Epoch 417/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4074 - accuracy: 0.8082\n",
            "Epoch 418/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4084 - accuracy: 0.8105\n",
            "Epoch 419/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4085 - accuracy: 0.8064\n",
            "Epoch 420/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4083 - accuracy: 0.8094\n",
            "Epoch 421/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4076 - accuracy: 0.8080\n",
            "Epoch 422/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4070 - accuracy: 0.8080\n",
            "Epoch 423/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4067 - accuracy: 0.8080\n",
            "Epoch 424/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4072 - accuracy: 0.8080\n",
            "Epoch 425/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4072 - accuracy: 0.8096\n",
            "Epoch 426/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4067 - accuracy: 0.8082\n",
            "Epoch 427/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4067 - accuracy: 0.8096\n",
            "Epoch 428/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4065 - accuracy: 0.8091\n",
            "Epoch 429/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4066 - accuracy: 0.8091\n",
            "Epoch 430/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4064 - accuracy: 0.8092\n",
            "Epoch 431/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4065 - accuracy: 0.8080\n",
            "Epoch 432/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4066 - accuracy: 0.8098\n",
            "Epoch 433/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4064 - accuracy: 0.8092\n",
            "Epoch 434/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4064 - accuracy: 0.8101\n",
            "Epoch 435/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4068 - accuracy: 0.8064\n",
            "Epoch 436/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4069 - accuracy: 0.8103\n",
            "Epoch 437/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4066 - accuracy: 0.8073\n",
            "Epoch 438/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4067 - accuracy: 0.8094\n",
            "Epoch 439/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4065 - accuracy: 0.8082\n",
            "Epoch 440/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4062 - accuracy: 0.8103\n",
            "Epoch 441/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4062 - accuracy: 0.8092\n",
            "Epoch 442/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4062 - accuracy: 0.8101\n",
            "Epoch 443/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4067 - accuracy: 0.8082\n",
            "Epoch 444/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4070 - accuracy: 0.8108\n",
            "Epoch 445/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4060 - accuracy: 0.8096\n",
            "Epoch 446/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4062 - accuracy: 0.8084\n",
            "Epoch 447/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4065 - accuracy: 0.8116\n",
            "Epoch 448/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4065 - accuracy: 0.8080\n",
            "Epoch 449/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4063 - accuracy: 0.8108\n",
            "Epoch 450/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4060 - accuracy: 0.8108\n",
            "Epoch 451/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4061 - accuracy: 0.8101\n",
            "Epoch 452/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4063 - accuracy: 0.8087\n",
            "Epoch 453/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4060 - accuracy: 0.8107\n",
            "Epoch 454/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4061 - accuracy: 0.8098\n",
            "Epoch 455/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4075 - accuracy: 0.8105\n",
            "Epoch 456/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4068 - accuracy: 0.8068\n",
            "Epoch 457/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4058 - accuracy: 0.8108\n",
            "Epoch 458/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4058 - accuracy: 0.8096\n",
            "Epoch 459/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4060 - accuracy: 0.8091\n",
            "Epoch 460/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4059 - accuracy: 0.8103\n",
            "Epoch 461/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4059 - accuracy: 0.8096\n",
            "Epoch 462/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4060 - accuracy: 0.8105\n",
            "Epoch 463/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4057 - accuracy: 0.8103\n",
            "Epoch 464/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4058 - accuracy: 0.8112\n",
            "Epoch 465/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4059 - accuracy: 0.8105\n",
            "Epoch 466/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4058 - accuracy: 0.8089\n",
            "Epoch 467/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4056 - accuracy: 0.8101\n",
            "Epoch 468/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4058 - accuracy: 0.8092\n",
            "Epoch 469/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4057 - accuracy: 0.8108\n",
            "Epoch 470/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4056 - accuracy: 0.8107\n",
            "Epoch 471/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4058 - accuracy: 0.8103\n",
            "Epoch 472/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4057 - accuracy: 0.8091\n",
            "Epoch 473/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4056 - accuracy: 0.8098\n",
            "Epoch 474/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4061 - accuracy: 0.8103\n",
            "Epoch 475/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4058 - accuracy: 0.8091\n",
            "Epoch 476/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4057 - accuracy: 0.8101\n",
            "Epoch 477/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4057 - accuracy: 0.8101\n",
            "Epoch 478/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4062 - accuracy: 0.8092\n",
            "Epoch 479/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4057 - accuracy: 0.8082\n",
            "Epoch 480/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4055 - accuracy: 0.8105\n",
            "Epoch 481/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4055 - accuracy: 0.8080\n",
            "Epoch 482/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4057 - accuracy: 0.8098\n",
            "Epoch 483/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4056 - accuracy: 0.8084\n",
            "Epoch 484/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4055 - accuracy: 0.8098\n",
            "Epoch 485/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4056 - accuracy: 0.8091\n",
            "Epoch 486/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4056 - accuracy: 0.8114\n",
            "Epoch 487/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4058 - accuracy: 0.8087\n",
            "Epoch 488/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4053 - accuracy: 0.8100\n",
            "Epoch 489/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4058 - accuracy: 0.8069\n",
            "Epoch 490/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4057 - accuracy: 0.8116\n",
            "Epoch 491/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4062 - accuracy: 0.8085\n",
            "Epoch 492/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4053 - accuracy: 0.8107\n",
            "Epoch 493/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4052 - accuracy: 0.8103\n",
            "Epoch 494/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4053 - accuracy: 0.8103\n",
            "Epoch 495/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4055 - accuracy: 0.8108\n",
            "Epoch 496/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4054 - accuracy: 0.8103\n",
            "Epoch 497/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4052 - accuracy: 0.8098\n",
            "Epoch 498/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4051 - accuracy: 0.8100\n",
            "Epoch 499/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4051 - accuracy: 0.8103\n",
            "Epoch 500/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4052 - accuracy: 0.8101\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.src.callbacks.History at 0x794fd9a95ff0>"
            ]
          },
          "metadata": {},
          "execution_count": 190
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model4 = keras.Sequential([\n",
        "    keras.layers.Dense(100, input_shape=(27,), activation='sigmoid',kernel_initializer = tf.keras.initializers.Zeros()),\n",
        "    keras.layers.Dense(1,activation='sigmoid')\n",
        "])\n",
        "\n",
        "model4.compile(\n",
        "    optimizer='adam',\n",
        "    loss='binary_crossentropy',\n",
        "    metrics=['accuracy']\n",
        ")\n",
        "\n",
        "# Fit the model\n",
        "model4.fit(X_train, y_train, epochs=500, batch_size = 500)\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XVPVJYxtC-eE",
        "outputId": "e3e7fd96-d186-4f83-c8a0-f096b58fb85d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/500\n",
            "12/12 [==============================] - 1s 3ms/step - loss: 0.6782 - accuracy: 0.5566\n",
            "Epoch 2/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5719 - accuracy: 0.7346\n",
            "Epoch 3/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5539 - accuracy: 0.7346\n",
            "Epoch 4/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.5354 - accuracy: 0.7346\n",
            "Epoch 5/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5188 - accuracy: 0.7346\n",
            "Epoch 6/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.5053 - accuracy: 0.7346\n",
            "Epoch 7/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4930 - accuracy: 0.7349\n",
            "Epoch 8/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4827 - accuracy: 0.7399\n",
            "Epoch 9/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4736 - accuracy: 0.7545\n",
            "Epoch 10/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4658 - accuracy: 0.7675\n",
            "Epoch 11/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4590 - accuracy: 0.7735\n",
            "Epoch 12/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4535 - accuracy: 0.7831\n",
            "Epoch 13/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4485 - accuracy: 0.7845\n",
            "Epoch 14/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4446 - accuracy: 0.7861\n",
            "Epoch 15/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4409 - accuracy: 0.7881\n",
            "Epoch 16/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4383 - accuracy: 0.7897\n",
            "Epoch 17/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4359 - accuracy: 0.7918\n",
            "Epoch 18/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4338 - accuracy: 0.7934\n",
            "Epoch 19/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4319 - accuracy: 0.7945\n",
            "Epoch 20/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4304 - accuracy: 0.7945\n",
            "Epoch 21/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4291 - accuracy: 0.7945\n",
            "Epoch 22/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4280 - accuracy: 0.7964\n",
            "Epoch 23/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4271 - accuracy: 0.7963\n",
            "Epoch 24/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4262 - accuracy: 0.7972\n",
            "Epoch 25/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4254 - accuracy: 0.7963\n",
            "Epoch 26/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4247 - accuracy: 0.7964\n",
            "Epoch 27/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4242 - accuracy: 0.7980\n",
            "Epoch 28/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4236 - accuracy: 0.7968\n",
            "Epoch 29/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4233 - accuracy: 0.7998\n",
            "Epoch 30/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4223 - accuracy: 0.8000\n",
            "Epoch 31/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4220 - accuracy: 0.7980\n",
            "Epoch 32/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4215 - accuracy: 0.8005\n",
            "Epoch 33/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4211 - accuracy: 0.8011\n",
            "Epoch 34/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4206 - accuracy: 0.8011\n",
            "Epoch 35/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4206 - accuracy: 0.8009\n",
            "Epoch 36/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4199 - accuracy: 0.8011\n",
            "Epoch 37/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4196 - accuracy: 0.8007\n",
            "Epoch 38/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4194 - accuracy: 0.8018\n",
            "Epoch 39/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4190 - accuracy: 0.8036\n",
            "Epoch 40/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4190 - accuracy: 0.8014\n",
            "Epoch 41/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4185 - accuracy: 0.8021\n",
            "Epoch 42/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4184 - accuracy: 0.8021\n",
            "Epoch 43/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4181 - accuracy: 0.8037\n",
            "Epoch 44/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4179 - accuracy: 0.8043\n",
            "Epoch 45/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4180 - accuracy: 0.8050\n",
            "Epoch 46/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4175 - accuracy: 0.8043\n",
            "Epoch 47/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4174 - accuracy: 0.8043\n",
            "Epoch 48/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4173 - accuracy: 0.8050\n",
            "Epoch 49/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4171 - accuracy: 0.8057\n",
            "Epoch 50/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4169 - accuracy: 0.8048\n",
            "Epoch 51/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4167 - accuracy: 0.8032\n",
            "Epoch 52/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4169 - accuracy: 0.8041\n",
            "Epoch 53/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4165 - accuracy: 0.8053\n",
            "Epoch 54/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4165 - accuracy: 0.8043\n",
            "Epoch 55/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4165 - accuracy: 0.8055\n",
            "Epoch 56/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4162 - accuracy: 0.8050\n",
            "Epoch 57/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4162 - accuracy: 0.8060\n",
            "Epoch 58/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4160 - accuracy: 0.8064\n",
            "Epoch 59/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4159 - accuracy: 0.8059\n",
            "Epoch 60/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4158 - accuracy: 0.8057\n",
            "Epoch 61/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4166 - accuracy: 0.8057\n",
            "Epoch 62/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4162 - accuracy: 0.8027\n",
            "Epoch 63/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4157 - accuracy: 0.8069\n",
            "Epoch 64/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4157 - accuracy: 0.8066\n",
            "Epoch 65/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4156 - accuracy: 0.8071\n",
            "Epoch 66/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4157 - accuracy: 0.8062\n",
            "Epoch 67/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4155 - accuracy: 0.8076\n",
            "Epoch 68/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4154 - accuracy: 0.8059\n",
            "Epoch 69/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4153 - accuracy: 0.8069\n",
            "Epoch 70/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4154 - accuracy: 0.8057\n",
            "Epoch 71/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4154 - accuracy: 0.8062\n",
            "Epoch 72/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4155 - accuracy: 0.8073\n",
            "Epoch 73/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4151 - accuracy: 0.8066\n",
            "Epoch 74/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4151 - accuracy: 0.8071\n",
            "Epoch 75/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4151 - accuracy: 0.8068\n",
            "Epoch 76/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4152 - accuracy: 0.8068\n",
            "Epoch 77/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4150 - accuracy: 0.8076\n",
            "Epoch 78/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4150 - accuracy: 0.8085\n",
            "Epoch 79/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4151 - accuracy: 0.8059\n",
            "Epoch 80/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4149 - accuracy: 0.8071\n",
            "Epoch 81/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4152 - accuracy: 0.8073\n",
            "Epoch 82/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4153 - accuracy: 0.8060\n",
            "Epoch 83/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4150 - accuracy: 0.8060\n",
            "Epoch 84/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4149 - accuracy: 0.8060\n",
            "Epoch 85/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4149 - accuracy: 0.8062\n",
            "Epoch 86/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4148 - accuracy: 0.8064\n",
            "Epoch 87/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4148 - accuracy: 0.8069\n",
            "Epoch 88/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4150 - accuracy: 0.8066\n",
            "Epoch 89/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4148 - accuracy: 0.8071\n",
            "Epoch 90/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4147 - accuracy: 0.8060\n",
            "Epoch 91/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4146 - accuracy: 0.8076\n",
            "Epoch 92/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4147 - accuracy: 0.8073\n",
            "Epoch 93/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4146 - accuracy: 0.8069\n",
            "Epoch 94/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4147 - accuracy: 0.8073\n",
            "Epoch 95/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4145 - accuracy: 0.8075\n",
            "Epoch 96/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4148 - accuracy: 0.8075\n",
            "Epoch 97/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4146 - accuracy: 0.8071\n",
            "Epoch 98/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4146 - accuracy: 0.8073\n",
            "Epoch 99/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4149 - accuracy: 0.8071\n",
            "Epoch 100/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4146 - accuracy: 0.8076\n",
            "Epoch 101/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4145 - accuracy: 0.8082\n",
            "Epoch 102/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4145 - accuracy: 0.8064\n",
            "Epoch 103/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4145 - accuracy: 0.8068\n",
            "Epoch 104/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4144 - accuracy: 0.8075\n",
            "Epoch 105/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4143 - accuracy: 0.8080\n",
            "Epoch 106/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4145 - accuracy: 0.8069\n",
            "Epoch 107/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4146 - accuracy: 0.8071\n",
            "Epoch 108/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4151 - accuracy: 0.8055\n",
            "Epoch 109/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4152 - accuracy: 0.8082\n",
            "Epoch 110/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4161 - accuracy: 0.8044\n",
            "Epoch 111/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4150 - accuracy: 0.8055\n",
            "Epoch 112/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4144 - accuracy: 0.8073\n",
            "Epoch 113/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4144 - accuracy: 0.8062\n",
            "Epoch 114/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4145 - accuracy: 0.8066\n",
            "Epoch 115/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4144 - accuracy: 0.8069\n",
            "Epoch 116/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4142 - accuracy: 0.8062\n",
            "Epoch 117/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4145 - accuracy: 0.8066\n",
            "Epoch 118/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4145 - accuracy: 0.8069\n",
            "Epoch 119/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4142 - accuracy: 0.8069\n",
            "Epoch 120/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4145 - accuracy: 0.8075\n",
            "Epoch 121/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4144 - accuracy: 0.8069\n",
            "Epoch 122/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4145 - accuracy: 0.8069\n",
            "Epoch 123/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4141 - accuracy: 0.8069\n",
            "Epoch 124/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4142 - accuracy: 0.8076\n",
            "Epoch 125/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4143 - accuracy: 0.8068\n",
            "Epoch 126/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4143 - accuracy: 0.8085\n",
            "Epoch 127/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4141 - accuracy: 0.8076\n",
            "Epoch 128/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4144 - accuracy: 0.8062\n",
            "Epoch 129/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4142 - accuracy: 0.8066\n",
            "Epoch 130/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4141 - accuracy: 0.8069\n",
            "Epoch 131/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4141 - accuracy: 0.8076\n",
            "Epoch 132/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4142 - accuracy: 0.8060\n",
            "Epoch 133/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4141 - accuracy: 0.8060\n",
            "Epoch 134/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4140 - accuracy: 0.8068\n",
            "Epoch 135/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4140 - accuracy: 0.8078\n",
            "Epoch 136/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4140 - accuracy: 0.8075\n",
            "Epoch 137/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4141 - accuracy: 0.8073\n",
            "Epoch 138/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4140 - accuracy: 0.8071\n",
            "Epoch 139/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4142 - accuracy: 0.8076\n",
            "Epoch 140/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4147 - accuracy: 0.8068\n",
            "Epoch 141/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4146 - accuracy: 0.8055\n",
            "Epoch 142/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4158 - accuracy: 0.8059\n",
            "Epoch 143/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4153 - accuracy: 0.8023\n",
            "Epoch 144/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4143 - accuracy: 0.8078\n",
            "Epoch 145/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4142 - accuracy: 0.8069\n",
            "Epoch 146/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4140 - accuracy: 0.8075\n",
            "Epoch 147/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4139 - accuracy: 0.8075\n",
            "Epoch 148/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4140 - accuracy: 0.8080\n",
            "Epoch 149/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4142 - accuracy: 0.8084\n",
            "Epoch 150/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4144 - accuracy: 0.8073\n",
            "Epoch 151/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4147 - accuracy: 0.8082\n",
            "Epoch 152/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4138 - accuracy: 0.8085\n",
            "Epoch 153/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4142 - accuracy: 0.8062\n",
            "Epoch 154/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4146 - accuracy: 0.8068\n",
            "Epoch 155/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4142 - accuracy: 0.8066\n",
            "Epoch 156/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4140 - accuracy: 0.8062\n",
            "Epoch 157/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4137 - accuracy: 0.8069\n",
            "Epoch 158/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4140 - accuracy: 0.8082\n",
            "Epoch 159/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4140 - accuracy: 0.8064\n",
            "Epoch 160/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4142 - accuracy: 0.8064\n",
            "Epoch 161/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4142 - accuracy: 0.8073\n",
            "Epoch 162/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4147 - accuracy: 0.8062\n",
            "Epoch 163/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4143 - accuracy: 0.8075\n",
            "Epoch 164/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4142 - accuracy: 0.8062\n",
            "Epoch 165/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4138 - accuracy: 0.8069\n",
            "Epoch 166/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4140 - accuracy: 0.8076\n",
            "Epoch 167/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4140 - accuracy: 0.8066\n",
            "Epoch 168/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4136 - accuracy: 0.8073\n",
            "Epoch 169/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4138 - accuracy: 0.8071\n",
            "Epoch 170/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4137 - accuracy: 0.8076\n",
            "Epoch 171/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4144 - accuracy: 0.8053\n",
            "Epoch 172/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4138 - accuracy: 0.8073\n",
            "Epoch 173/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4137 - accuracy: 0.8068\n",
            "Epoch 174/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4136 - accuracy: 0.8085\n",
            "Epoch 175/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4139 - accuracy: 0.8064\n",
            "Epoch 176/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4137 - accuracy: 0.8078\n",
            "Epoch 177/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4142 - accuracy: 0.8059\n",
            "Epoch 178/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4137 - accuracy: 0.8073\n",
            "Epoch 179/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4139 - accuracy: 0.8066\n",
            "Epoch 180/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4137 - accuracy: 0.8071\n",
            "Epoch 181/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4135 - accuracy: 0.8075\n",
            "Epoch 182/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4136 - accuracy: 0.8068\n",
            "Epoch 183/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4138 - accuracy: 0.8082\n",
            "Epoch 184/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4135 - accuracy: 0.8068\n",
            "Epoch 185/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4136 - accuracy: 0.8071\n",
            "Epoch 186/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4140 - accuracy: 0.8071\n",
            "Epoch 187/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4137 - accuracy: 0.8066\n",
            "Epoch 188/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4136 - accuracy: 0.8078\n",
            "Epoch 189/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4134 - accuracy: 0.8082\n",
            "Epoch 190/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4136 - accuracy: 0.8075\n",
            "Epoch 191/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4135 - accuracy: 0.8080\n",
            "Epoch 192/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4134 - accuracy: 0.8066\n",
            "Epoch 193/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4135 - accuracy: 0.8076\n",
            "Epoch 194/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4134 - accuracy: 0.8066\n",
            "Epoch 195/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4140 - accuracy: 0.8076\n",
            "Epoch 196/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4138 - accuracy: 0.8059\n",
            "Epoch 197/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4134 - accuracy: 0.8080\n",
            "Epoch 198/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4133 - accuracy: 0.8091\n",
            "Epoch 199/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4133 - accuracy: 0.8080\n",
            "Epoch 200/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4132 - accuracy: 0.8078\n",
            "Epoch 201/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4134 - accuracy: 0.8075\n",
            "Epoch 202/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4134 - accuracy: 0.8073\n",
            "Epoch 203/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4132 - accuracy: 0.8084\n",
            "Epoch 204/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4134 - accuracy: 0.8068\n",
            "Epoch 205/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4135 - accuracy: 0.8080\n",
            "Epoch 206/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4134 - accuracy: 0.8085\n",
            "Epoch 207/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4134 - accuracy: 0.8084\n",
            "Epoch 208/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4132 - accuracy: 0.8068\n",
            "Epoch 209/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4133 - accuracy: 0.8076\n",
            "Epoch 210/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4135 - accuracy: 0.8075\n",
            "Epoch 211/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4138 - accuracy: 0.8068\n",
            "Epoch 212/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4133 - accuracy: 0.8084\n",
            "Epoch 213/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4133 - accuracy: 0.8068\n",
            "Epoch 214/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4138 - accuracy: 0.8075\n",
            "Epoch 215/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4133 - accuracy: 0.8087\n",
            "Epoch 216/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4135 - accuracy: 0.8075\n",
            "Epoch 217/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4135 - accuracy: 0.8075\n",
            "Epoch 218/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4130 - accuracy: 0.8071\n",
            "Epoch 219/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4131 - accuracy: 0.8085\n",
            "Epoch 220/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4133 - accuracy: 0.8068\n",
            "Epoch 221/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4129 - accuracy: 0.8073\n",
            "Epoch 222/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4130 - accuracy: 0.8069\n",
            "Epoch 223/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4135 - accuracy: 0.8071\n",
            "Epoch 224/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4131 - accuracy: 0.8078\n",
            "Epoch 225/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4134 - accuracy: 0.8068\n",
            "Epoch 226/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4133 - accuracy: 0.8057\n",
            "Epoch 227/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4132 - accuracy: 0.8094\n",
            "Epoch 228/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4133 - accuracy: 0.8078\n",
            "Epoch 229/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4135 - accuracy: 0.8080\n",
            "Epoch 230/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4130 - accuracy: 0.8076\n",
            "Epoch 231/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4131 - accuracy: 0.8080\n",
            "Epoch 232/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4136 - accuracy: 0.8082\n",
            "Epoch 233/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4134 - accuracy: 0.8055\n",
            "Epoch 234/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4135 - accuracy: 0.8050\n",
            "Epoch 235/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4132 - accuracy: 0.8084\n",
            "Epoch 236/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4128 - accuracy: 0.8069\n",
            "Epoch 237/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4129 - accuracy: 0.8080\n",
            "Epoch 238/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4129 - accuracy: 0.8084\n",
            "Epoch 239/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4127 - accuracy: 0.8089\n",
            "Epoch 240/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4130 - accuracy: 0.8080\n",
            "Epoch 241/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4126 - accuracy: 0.8073\n",
            "Epoch 242/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4126 - accuracy: 0.8087\n",
            "Epoch 243/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4129 - accuracy: 0.8092\n",
            "Epoch 244/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4126 - accuracy: 0.8087\n",
            "Epoch 245/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4127 - accuracy: 0.8085\n",
            "Epoch 246/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4126 - accuracy: 0.8071\n",
            "Epoch 247/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4127 - accuracy: 0.8075\n",
            "Epoch 248/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4128 - accuracy: 0.8084\n",
            "Epoch 249/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4125 - accuracy: 0.8078\n",
            "Epoch 250/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4126 - accuracy: 0.8085\n",
            "Epoch 251/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4125 - accuracy: 0.8080\n",
            "Epoch 252/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4127 - accuracy: 0.8084\n",
            "Epoch 253/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4125 - accuracy: 0.8076\n",
            "Epoch 254/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4124 - accuracy: 0.8080\n",
            "Epoch 255/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4124 - accuracy: 0.8092\n",
            "Epoch 256/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4124 - accuracy: 0.8085\n",
            "Epoch 257/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4126 - accuracy: 0.8084\n",
            "Epoch 258/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4123 - accuracy: 0.8092\n",
            "Epoch 259/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4126 - accuracy: 0.8068\n",
            "Epoch 260/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4124 - accuracy: 0.8087\n",
            "Epoch 261/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4127 - accuracy: 0.8082\n",
            "Epoch 262/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4124 - accuracy: 0.8075\n",
            "Epoch 263/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4127 - accuracy: 0.8078\n",
            "Epoch 264/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4132 - accuracy: 0.8085\n",
            "Epoch 265/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4123 - accuracy: 0.8096\n",
            "Epoch 266/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4133 - accuracy: 0.8082\n",
            "Epoch 267/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4125 - accuracy: 0.8082\n",
            "Epoch 268/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4122 - accuracy: 0.8087\n",
            "Epoch 269/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4121 - accuracy: 0.8064\n",
            "Epoch 270/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4120 - accuracy: 0.8082\n",
            "Epoch 271/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4122 - accuracy: 0.8084\n",
            "Epoch 272/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4121 - accuracy: 0.8082\n",
            "Epoch 273/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4121 - accuracy: 0.8069\n",
            "Epoch 274/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4120 - accuracy: 0.8075\n",
            "Epoch 275/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4120 - accuracy: 0.8071\n",
            "Epoch 276/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4123 - accuracy: 0.8073\n",
            "Epoch 277/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4120 - accuracy: 0.8080\n",
            "Epoch 278/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4121 - accuracy: 0.8082\n",
            "Epoch 279/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4119 - accuracy: 0.8087\n",
            "Epoch 280/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4119 - accuracy: 0.8084\n",
            "Epoch 281/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4119 - accuracy: 0.8085\n",
            "Epoch 282/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4119 - accuracy: 0.8089\n",
            "Epoch 283/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4123 - accuracy: 0.8092\n",
            "Epoch 284/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4118 - accuracy: 0.8087\n",
            "Epoch 285/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4118 - accuracy: 0.8098\n",
            "Epoch 286/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4119 - accuracy: 0.8080\n",
            "Epoch 287/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4122 - accuracy: 0.8092\n",
            "Epoch 288/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4117 - accuracy: 0.8082\n",
            "Epoch 289/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4118 - accuracy: 0.8073\n",
            "Epoch 290/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4117 - accuracy: 0.8087\n",
            "Epoch 291/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4118 - accuracy: 0.8092\n",
            "Epoch 292/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4118 - accuracy: 0.8098\n",
            "Epoch 293/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4116 - accuracy: 0.8089\n",
            "Epoch 294/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4123 - accuracy: 0.8062\n",
            "Epoch 295/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4120 - accuracy: 0.8089\n",
            "Epoch 296/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4115 - accuracy: 0.8087\n",
            "Epoch 297/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4116 - accuracy: 0.8076\n",
            "Epoch 298/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4120 - accuracy: 0.8084\n",
            "Epoch 299/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4117 - accuracy: 0.8075\n",
            "Epoch 300/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4117 - accuracy: 0.8098\n",
            "Epoch 301/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4118 - accuracy: 0.8087\n",
            "Epoch 302/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4114 - accuracy: 0.8089\n",
            "Epoch 303/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4116 - accuracy: 0.8092\n",
            "Epoch 304/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4118 - accuracy: 0.8085\n",
            "Epoch 305/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4116 - accuracy: 0.8085\n",
            "Epoch 306/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4119 - accuracy: 0.8078\n",
            "Epoch 307/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4121 - accuracy: 0.8089\n",
            "Epoch 308/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4128 - accuracy: 0.8073\n",
            "Epoch 309/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4117 - accuracy: 0.8103\n",
            "Epoch 310/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4112 - accuracy: 0.8085\n",
            "Epoch 311/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4112 - accuracy: 0.8089\n",
            "Epoch 312/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4113 - accuracy: 0.8071\n",
            "Epoch 313/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4112 - accuracy: 0.8075\n",
            "Epoch 314/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4111 - accuracy: 0.8082\n",
            "Epoch 315/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4113 - accuracy: 0.8100\n",
            "Epoch 316/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4112 - accuracy: 0.8092\n",
            "Epoch 317/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4114 - accuracy: 0.8094\n",
            "Epoch 318/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4111 - accuracy: 0.8098\n",
            "Epoch 319/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4113 - accuracy: 0.8078\n",
            "Epoch 320/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4119 - accuracy: 0.8094\n",
            "Epoch 321/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4118 - accuracy: 0.8080\n",
            "Epoch 322/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4113 - accuracy: 0.8100\n",
            "Epoch 323/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4110 - accuracy: 0.8087\n",
            "Epoch 324/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4109 - accuracy: 0.8076\n",
            "Epoch 325/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4108 - accuracy: 0.8094\n",
            "Epoch 326/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4120 - accuracy: 0.8082\n",
            "Epoch 327/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4110 - accuracy: 0.8085\n",
            "Epoch 328/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4111 - accuracy: 0.8080\n",
            "Epoch 329/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4117 - accuracy: 0.8101\n",
            "Epoch 330/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4109 - accuracy: 0.8069\n",
            "Epoch 331/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4110 - accuracy: 0.8096\n",
            "Epoch 332/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4108 - accuracy: 0.8085\n",
            "Epoch 333/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4109 - accuracy: 0.8082\n",
            "Epoch 334/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4111 - accuracy: 0.8080\n",
            "Epoch 335/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4110 - accuracy: 0.8078\n",
            "Epoch 336/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4108 - accuracy: 0.8098\n",
            "Epoch 337/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4107 - accuracy: 0.8084\n",
            "Epoch 338/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4108 - accuracy: 0.8080\n",
            "Epoch 339/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4110 - accuracy: 0.8100\n",
            "Epoch 340/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4112 - accuracy: 0.8069\n",
            "Epoch 341/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4123 - accuracy: 0.8101\n",
            "Epoch 342/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4113 - accuracy: 0.8076\n",
            "Epoch 343/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4120 - accuracy: 0.8094\n",
            "Epoch 344/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4107 - accuracy: 0.8080\n",
            "Epoch 345/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4105 - accuracy: 0.8076\n",
            "Epoch 346/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4109 - accuracy: 0.8101\n",
            "Epoch 347/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4109 - accuracy: 0.8069\n",
            "Epoch 348/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4106 - accuracy: 0.8116\n",
            "Epoch 349/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4105 - accuracy: 0.8085\n",
            "Epoch 350/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4106 - accuracy: 0.8078\n",
            "Epoch 351/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4108 - accuracy: 0.8105\n",
            "Epoch 352/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4105 - accuracy: 0.8087\n",
            "Epoch 353/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4117 - accuracy: 0.8105\n",
            "Epoch 354/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4114 - accuracy: 0.8085\n",
            "Epoch 355/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4106 - accuracy: 0.8117\n",
            "Epoch 356/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4110 - accuracy: 0.8107\n",
            "Epoch 357/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4104 - accuracy: 0.8080\n",
            "Epoch 358/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4104 - accuracy: 0.8094\n",
            "Epoch 359/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4103 - accuracy: 0.8096\n",
            "Epoch 360/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4105 - accuracy: 0.8087\n",
            "Epoch 361/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4106 - accuracy: 0.8105\n",
            "Epoch 362/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4104 - accuracy: 0.8107\n",
            "Epoch 363/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4103 - accuracy: 0.8084\n",
            "Epoch 364/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4105 - accuracy: 0.8103\n",
            "Epoch 365/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4104 - accuracy: 0.8084\n",
            "Epoch 366/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4103 - accuracy: 0.8110\n",
            "Epoch 367/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4102 - accuracy: 0.8076\n",
            "Epoch 368/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4102 - accuracy: 0.8091\n",
            "Epoch 369/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4101 - accuracy: 0.8100\n",
            "Epoch 370/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4112 - accuracy: 0.8094\n",
            "Epoch 371/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4103 - accuracy: 0.8080\n",
            "Epoch 372/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4102 - accuracy: 0.8094\n",
            "Epoch 373/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4104 - accuracy: 0.8082\n",
            "Epoch 374/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4103 - accuracy: 0.8105\n",
            "Epoch 375/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4106 - accuracy: 0.8082\n",
            "Epoch 376/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4104 - accuracy: 0.8101\n",
            "Epoch 377/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4103 - accuracy: 0.8073\n",
            "Epoch 378/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4113 - accuracy: 0.8094\n",
            "Epoch 379/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4105 - accuracy: 0.8078\n",
            "Epoch 380/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4104 - accuracy: 0.8103\n",
            "Epoch 381/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4105 - accuracy: 0.8085\n",
            "Epoch 382/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4098 - accuracy: 0.8091\n",
            "Epoch 383/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4099 - accuracy: 0.8091\n",
            "Epoch 384/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4103 - accuracy: 0.8080\n",
            "Epoch 385/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4100 - accuracy: 0.8105\n",
            "Epoch 386/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4107 - accuracy: 0.8082\n",
            "Epoch 387/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4106 - accuracy: 0.8100\n",
            "Epoch 388/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4100 - accuracy: 0.8085\n",
            "Epoch 389/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4101 - accuracy: 0.8098\n",
            "Epoch 390/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4101 - accuracy: 0.8073\n",
            "Epoch 391/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4106 - accuracy: 0.8080\n",
            "Epoch 392/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4106 - accuracy: 0.8073\n",
            "Epoch 393/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4099 - accuracy: 0.8089\n",
            "Epoch 394/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4099 - accuracy: 0.8085\n",
            "Epoch 395/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4100 - accuracy: 0.8110\n",
            "Epoch 396/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4099 - accuracy: 0.8085\n",
            "Epoch 397/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4098 - accuracy: 0.8100\n",
            "Epoch 398/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4097 - accuracy: 0.8084\n",
            "Epoch 399/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4098 - accuracy: 0.8084\n",
            "Epoch 400/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4097 - accuracy: 0.8105\n",
            "Epoch 401/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4112 - accuracy: 0.8069\n",
            "Epoch 402/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4106 - accuracy: 0.8101\n",
            "Epoch 403/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4106 - accuracy: 0.8060\n",
            "Epoch 404/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4103 - accuracy: 0.8094\n",
            "Epoch 405/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4097 - accuracy: 0.8112\n",
            "Epoch 406/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4104 - accuracy: 0.8073\n",
            "Epoch 407/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4101 - accuracy: 0.8098\n",
            "Epoch 408/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4118 - accuracy: 0.8036\n",
            "Epoch 409/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4111 - accuracy: 0.8078\n",
            "Epoch 410/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4101 - accuracy: 0.8084\n",
            "Epoch 411/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4095 - accuracy: 0.8073\n",
            "Epoch 412/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4102 - accuracy: 0.8108\n",
            "Epoch 413/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4100 - accuracy: 0.8091\n",
            "Epoch 414/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4099 - accuracy: 0.8092\n",
            "Epoch 415/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4096 - accuracy: 0.8096\n",
            "Epoch 416/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4094 - accuracy: 0.8094\n",
            "Epoch 417/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4096 - accuracy: 0.8082\n",
            "Epoch 418/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4095 - accuracy: 0.8094\n",
            "Epoch 419/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4098 - accuracy: 0.8082\n",
            "Epoch 420/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4094 - accuracy: 0.8091\n",
            "Epoch 421/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4100 - accuracy: 0.8073\n",
            "Epoch 422/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4097 - accuracy: 0.8100\n",
            "Epoch 423/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4098 - accuracy: 0.8080\n",
            "Epoch 424/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4095 - accuracy: 0.8091\n",
            "Epoch 425/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4094 - accuracy: 0.8076\n",
            "Epoch 426/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4094 - accuracy: 0.8094\n",
            "Epoch 427/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4094 - accuracy: 0.8078\n",
            "Epoch 428/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4093 - accuracy: 0.8082\n",
            "Epoch 429/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4095 - accuracy: 0.8087\n",
            "Epoch 430/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4096 - accuracy: 0.8076\n",
            "Epoch 431/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4093 - accuracy: 0.8091\n",
            "Epoch 432/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4093 - accuracy: 0.8107\n",
            "Epoch 433/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4093 - accuracy: 0.8082\n",
            "Epoch 434/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4094 - accuracy: 0.8069\n",
            "Epoch 435/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4094 - accuracy: 0.8105\n",
            "Epoch 436/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4104 - accuracy: 0.8078\n",
            "Epoch 437/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4092 - accuracy: 0.8087\n",
            "Epoch 438/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4093 - accuracy: 0.8085\n",
            "Epoch 439/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4101 - accuracy: 0.8073\n",
            "Epoch 440/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4095 - accuracy: 0.8098\n",
            "Epoch 441/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4094 - accuracy: 0.8085\n",
            "Epoch 442/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4096 - accuracy: 0.8080\n",
            "Epoch 443/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4111 - accuracy: 0.8075\n",
            "Epoch 444/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4101 - accuracy: 0.8062\n",
            "Epoch 445/500\n",
            "12/12 [==============================] - 0s 3ms/step - loss: 0.4094 - accuracy: 0.8092\n",
            "Epoch 446/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4091 - accuracy: 0.8094\n",
            "Epoch 447/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4100 - accuracy: 0.8087\n",
            "Epoch 448/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4093 - accuracy: 0.8094\n",
            "Epoch 449/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4095 - accuracy: 0.8105\n",
            "Epoch 450/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4098 - accuracy: 0.8076\n",
            "Epoch 451/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4090 - accuracy: 0.8103\n",
            "Epoch 452/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4089 - accuracy: 0.8094\n",
            "Epoch 453/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4093 - accuracy: 0.8103\n",
            "Epoch 454/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4102 - accuracy: 0.8062\n",
            "Epoch 455/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4104 - accuracy: 0.8117\n",
            "Epoch 456/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4092 - accuracy: 0.8076\n",
            "Epoch 457/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4097 - accuracy: 0.8082\n",
            "Epoch 458/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4094 - accuracy: 0.8091\n",
            "Epoch 459/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4090 - accuracy: 0.8098\n",
            "Epoch 460/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4090 - accuracy: 0.8087\n",
            "Epoch 461/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4090 - accuracy: 0.8091\n",
            "Epoch 462/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4090 - accuracy: 0.8091\n",
            "Epoch 463/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4090 - accuracy: 0.8087\n",
            "Epoch 464/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4090 - accuracy: 0.8080\n",
            "Epoch 465/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4091 - accuracy: 0.8082\n",
            "Epoch 466/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4098 - accuracy: 0.8094\n",
            "Epoch 467/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4093 - accuracy: 0.8094\n",
            "Epoch 468/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4092 - accuracy: 0.8082\n",
            "Epoch 469/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4092 - accuracy: 0.8107\n",
            "Epoch 470/500\n",
            "12/12 [==============================] - 0s 4ms/step - loss: 0.4089 - accuracy: 0.8094\n",
            "Epoch 471/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4094 - accuracy: 0.8096\n",
            "Epoch 472/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4097 - accuracy: 0.8089\n",
            "Epoch 473/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4093 - accuracy: 0.8119\n",
            "Epoch 474/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4088 - accuracy: 0.8082\n",
            "Epoch 475/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4091 - accuracy: 0.8075\n",
            "Epoch 476/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.4095 - accuracy: 0.8105\n",
            "Epoch 477/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4089 - accuracy: 0.8076\n",
            "Epoch 478/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4089 - accuracy: 0.8082\n",
            "Epoch 479/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4087 - accuracy: 0.8094\n",
            "Epoch 480/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4089 - accuracy: 0.8094\n",
            "Epoch 481/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4088 - accuracy: 0.8094\n",
            "Epoch 482/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4087 - accuracy: 0.8089\n",
            "Epoch 483/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4090 - accuracy: 0.8094\n",
            "Epoch 484/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4091 - accuracy: 0.8101\n",
            "Epoch 485/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4090 - accuracy: 0.8094\n",
            "Epoch 486/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4089 - accuracy: 0.8100\n",
            "Epoch 487/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4088 - accuracy: 0.8075\n",
            "Epoch 488/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4086 - accuracy: 0.8084\n",
            "Epoch 489/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4087 - accuracy: 0.8096\n",
            "Epoch 490/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4088 - accuracy: 0.8082\n",
            "Epoch 491/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4093 - accuracy: 0.8094\n",
            "Epoch 492/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4093 - accuracy: 0.8073\n",
            "Epoch 493/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4090 - accuracy: 0.8100\n",
            "Epoch 494/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4089 - accuracy: 0.8073\n",
            "Epoch 495/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4093 - accuracy: 0.8112\n",
            "Epoch 496/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4095 - accuracy: 0.8080\n",
            "Epoch 497/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4086 - accuracy: 0.8100\n",
            "Epoch 498/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4086 - accuracy: 0.8094\n",
            "Epoch 499/500\n",
            "12/12 [==============================] - 0s 6ms/step - loss: 0.4086 - accuracy: 0.8091\n",
            "Epoch 500/500\n",
            "12/12 [==============================] - 0s 5ms/step - loss: 0.4087 - accuracy: 0.8092\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.src.callbacks.History at 0x794fd86b6320>"
            ]
          },
          "metadata": {},
          "execution_count": 191
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model5 = keras.Sequential([\n",
        "    keras.layers.Dense(100, input_shape=(27,)),\n",
        "    keras.layers.BatchNormalization(),\n",
        "    keras.layers.Activation('relu'),\n",
        "    keras.layers.Dropout(0.2),\n",
        "\n",
        "    keras.layers.Dense(100),\n",
        "    keras.layers.BatchNormalization(),\n",
        "    keras.layers.Activation('relu'),\n",
        "    keras.layers.Dropout(0.2),\n",
        "\n",
        "    keras.layers.Dense(1,activation='sigmoid')\n",
        "])\n",
        "\n",
        "model5.compile(\n",
        "    optimizer=keras.optimizers.AdamW(learning_rate=0.01),\n",
        "    loss='binary_crossentropy',\n",
        "    metrics=['accuracy']\n",
        ")\n",
        "\n",
        "# Fit the model\n",
        "model5.fit(X_train, y_train, epochs=500, batch_size = 500)\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZdEK7BWNbpIe",
        "outputId": "1659395b-7571-44b3-9133-cd7c950aa596"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/500\n",
            "12/12 [==============================] - 2s 12ms/step - loss: 0.5105 - accuracy: 0.7397\n",
            "Epoch 2/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.4387 - accuracy: 0.7884\n",
            "Epoch 3/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.4210 - accuracy: 0.8039\n",
            "Epoch 4/500\n",
            "12/12 [==============================] - 0s 14ms/step - loss: 0.4193 - accuracy: 0.8020\n",
            "Epoch 5/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.4103 - accuracy: 0.8060\n",
            "Epoch 6/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.4060 - accuracy: 0.8087\n",
            "Epoch 7/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.4001 - accuracy: 0.8101\n",
            "Epoch 8/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4075 - accuracy: 0.8064\n",
            "Epoch 9/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.4011 - accuracy: 0.8132\n",
            "Epoch 10/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.3961 - accuracy: 0.8078\n",
            "Epoch 11/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3937 - accuracy: 0.8140\n",
            "Epoch 12/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3946 - accuracy: 0.8149\n",
            "Epoch 13/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.3900 - accuracy: 0.8171\n",
            "Epoch 14/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3906 - accuracy: 0.8162\n",
            "Epoch 15/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.3872 - accuracy: 0.8208\n",
            "Epoch 16/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3904 - accuracy: 0.8171\n",
            "Epoch 17/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3869 - accuracy: 0.8137\n",
            "Epoch 18/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3815 - accuracy: 0.8203\n",
            "Epoch 19/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3786 - accuracy: 0.8215\n",
            "Epoch 20/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3819 - accuracy: 0.8203\n",
            "Epoch 21/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3765 - accuracy: 0.8194\n",
            "Epoch 22/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.3756 - accuracy: 0.8176\n",
            "Epoch 23/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.3789 - accuracy: 0.8238\n",
            "Epoch 24/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.3701 - accuracy: 0.8261\n",
            "Epoch 25/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.3767 - accuracy: 0.8233\n",
            "Epoch 26/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.3697 - accuracy: 0.8258\n",
            "Epoch 27/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.3651 - accuracy: 0.8236\n",
            "Epoch 28/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3699 - accuracy: 0.8274\n",
            "Epoch 29/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3656 - accuracy: 0.8222\n",
            "Epoch 30/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3644 - accuracy: 0.8290\n",
            "Epoch 31/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3618 - accuracy: 0.8249\n",
            "Epoch 32/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3587 - accuracy: 0.8274\n",
            "Epoch 33/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.3591 - accuracy: 0.8309\n",
            "Epoch 34/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3605 - accuracy: 0.8311\n",
            "Epoch 35/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.3593 - accuracy: 0.8286\n",
            "Epoch 36/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.3559 - accuracy: 0.8263\n",
            "Epoch 37/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3527 - accuracy: 0.8308\n",
            "Epoch 38/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3546 - accuracy: 0.8350\n",
            "Epoch 39/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3564 - accuracy: 0.8267\n",
            "Epoch 40/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3455 - accuracy: 0.8311\n",
            "Epoch 41/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.3458 - accuracy: 0.8393\n",
            "Epoch 42/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3488 - accuracy: 0.8338\n",
            "Epoch 43/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.3400 - accuracy: 0.8432\n",
            "Epoch 44/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3418 - accuracy: 0.8336\n",
            "Epoch 45/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.3406 - accuracy: 0.8348\n",
            "Epoch 46/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.3406 - accuracy: 0.8414\n",
            "Epoch 47/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3344 - accuracy: 0.8430\n",
            "Epoch 48/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3355 - accuracy: 0.8437\n",
            "Epoch 49/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3386 - accuracy: 0.8409\n",
            "Epoch 50/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3316 - accuracy: 0.8460\n",
            "Epoch 51/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3309 - accuracy: 0.8466\n",
            "Epoch 52/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3320 - accuracy: 0.8448\n",
            "Epoch 53/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.3330 - accuracy: 0.8396\n",
            "Epoch 54/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.3322 - accuracy: 0.8468\n",
            "Epoch 55/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.3287 - accuracy: 0.8420\n",
            "Epoch 56/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.3281 - accuracy: 0.8473\n",
            "Epoch 57/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.3242 - accuracy: 0.8480\n",
            "Epoch 58/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.3287 - accuracy: 0.8407\n",
            "Epoch 59/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.3235 - accuracy: 0.8427\n",
            "Epoch 60/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.3205 - accuracy: 0.8524\n",
            "Epoch 61/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.3193 - accuracy: 0.8517\n",
            "Epoch 62/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.3186 - accuracy: 0.8510\n",
            "Epoch 63/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.3140 - accuracy: 0.8512\n",
            "Epoch 64/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.3162 - accuracy: 0.8514\n",
            "Epoch 65/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.3060 - accuracy: 0.8517\n",
            "Epoch 66/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.3069 - accuracy: 0.8571\n",
            "Epoch 67/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.3009 - accuracy: 0.8572\n",
            "Epoch 68/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.3125 - accuracy: 0.8519\n",
            "Epoch 69/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.3130 - accuracy: 0.8546\n",
            "Epoch 70/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.3145 - accuracy: 0.8523\n",
            "Epoch 71/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.3109 - accuracy: 0.8558\n",
            "Epoch 72/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.3082 - accuracy: 0.8544\n",
            "Epoch 73/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.3028 - accuracy: 0.8628\n",
            "Epoch 74/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.3021 - accuracy: 0.8565\n",
            "Epoch 75/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2978 - accuracy: 0.8576\n",
            "Epoch 76/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2980 - accuracy: 0.8635\n",
            "Epoch 77/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2996 - accuracy: 0.8647\n",
            "Epoch 78/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2948 - accuracy: 0.8626\n",
            "Epoch 79/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2928 - accuracy: 0.8672\n",
            "Epoch 80/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.3049 - accuracy: 0.8560\n",
            "Epoch 81/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2940 - accuracy: 0.8686\n",
            "Epoch 82/500\n",
            "12/12 [==============================] - 0s 14ms/step - loss: 0.2941 - accuracy: 0.8672\n",
            "Epoch 83/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2903 - accuracy: 0.8668\n",
            "Epoch 84/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2929 - accuracy: 0.8631\n",
            "Epoch 85/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2967 - accuracy: 0.8647\n",
            "Epoch 86/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.3040 - accuracy: 0.8556\n",
            "Epoch 87/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2905 - accuracy: 0.8647\n",
            "Epoch 88/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2892 - accuracy: 0.8638\n",
            "Epoch 89/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2902 - accuracy: 0.8654\n",
            "Epoch 90/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2821 - accuracy: 0.8690\n",
            "Epoch 91/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2800 - accuracy: 0.8752\n",
            "Epoch 92/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2845 - accuracy: 0.8700\n",
            "Epoch 93/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2830 - accuracy: 0.8718\n",
            "Epoch 94/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2850 - accuracy: 0.8672\n",
            "Epoch 95/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2724 - accuracy: 0.8741\n",
            "Epoch 96/500\n",
            "12/12 [==============================] - 0s 14ms/step - loss: 0.2730 - accuracy: 0.8759\n",
            "Epoch 97/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2703 - accuracy: 0.8731\n",
            "Epoch 98/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2828 - accuracy: 0.8683\n",
            "Epoch 99/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2861 - accuracy: 0.8640\n",
            "Epoch 100/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.2781 - accuracy: 0.8748\n",
            "Epoch 101/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2792 - accuracy: 0.8709\n",
            "Epoch 102/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2876 - accuracy: 0.8681\n",
            "Epoch 103/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2771 - accuracy: 0.8750\n",
            "Epoch 104/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2749 - accuracy: 0.8697\n",
            "Epoch 105/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2741 - accuracy: 0.8748\n",
            "Epoch 106/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2780 - accuracy: 0.8724\n",
            "Epoch 107/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2743 - accuracy: 0.8764\n",
            "Epoch 108/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2763 - accuracy: 0.8716\n",
            "Epoch 109/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2765 - accuracy: 0.8727\n",
            "Epoch 110/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2629 - accuracy: 0.8777\n",
            "Epoch 111/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.2617 - accuracy: 0.8805\n",
            "Epoch 112/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2712 - accuracy: 0.8752\n",
            "Epoch 113/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2658 - accuracy: 0.8830\n",
            "Epoch 114/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2566 - accuracy: 0.8843\n",
            "Epoch 115/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2664 - accuracy: 0.8731\n",
            "Epoch 116/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2701 - accuracy: 0.8802\n",
            "Epoch 117/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.2811 - accuracy: 0.8695\n",
            "Epoch 118/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2658 - accuracy: 0.8780\n",
            "Epoch 119/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2550 - accuracy: 0.8852\n",
            "Epoch 120/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2697 - accuracy: 0.8802\n",
            "Epoch 121/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2637 - accuracy: 0.8757\n",
            "Epoch 122/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2674 - accuracy: 0.8748\n",
            "Epoch 123/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2630 - accuracy: 0.8809\n",
            "Epoch 124/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2655 - accuracy: 0.8782\n",
            "Epoch 125/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2614 - accuracy: 0.8793\n",
            "Epoch 126/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2596 - accuracy: 0.8788\n",
            "Epoch 127/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2603 - accuracy: 0.8786\n",
            "Epoch 128/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2637 - accuracy: 0.8821\n",
            "Epoch 129/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2710 - accuracy: 0.8784\n",
            "Epoch 130/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2584 - accuracy: 0.8844\n",
            "Epoch 131/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2621 - accuracy: 0.8807\n",
            "Epoch 132/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.2589 - accuracy: 0.8798\n",
            "Epoch 133/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.2608 - accuracy: 0.8791\n",
            "Epoch 134/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2542 - accuracy: 0.8825\n",
            "Epoch 135/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2566 - accuracy: 0.8862\n",
            "Epoch 136/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2553 - accuracy: 0.8782\n",
            "Epoch 137/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.2506 - accuracy: 0.8827\n",
            "Epoch 138/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2558 - accuracy: 0.8791\n",
            "Epoch 139/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2590 - accuracy: 0.8823\n",
            "Epoch 140/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2505 - accuracy: 0.8852\n",
            "Epoch 141/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2646 - accuracy: 0.8756\n",
            "Epoch 142/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2583 - accuracy: 0.8823\n",
            "Epoch 143/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2537 - accuracy: 0.8860\n",
            "Epoch 144/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.2606 - accuracy: 0.8796\n",
            "Epoch 145/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.2599 - accuracy: 0.8782\n",
            "Epoch 146/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2591 - accuracy: 0.8800\n",
            "Epoch 147/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2605 - accuracy: 0.8805\n",
            "Epoch 148/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.2468 - accuracy: 0.8887\n",
            "Epoch 149/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2486 - accuracy: 0.8871\n",
            "Epoch 150/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2546 - accuracy: 0.8850\n",
            "Epoch 151/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2547 - accuracy: 0.8821\n",
            "Epoch 152/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2465 - accuracy: 0.8882\n",
            "Epoch 153/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2522 - accuracy: 0.8830\n",
            "Epoch 154/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2510 - accuracy: 0.8843\n",
            "Epoch 155/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2546 - accuracy: 0.8802\n",
            "Epoch 156/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2574 - accuracy: 0.8839\n",
            "Epoch 157/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2508 - accuracy: 0.8841\n",
            "Epoch 158/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2534 - accuracy: 0.8830\n",
            "Epoch 159/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2458 - accuracy: 0.8889\n",
            "Epoch 160/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2412 - accuracy: 0.8910\n",
            "Epoch 161/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2401 - accuracy: 0.8928\n",
            "Epoch 162/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2419 - accuracy: 0.8923\n",
            "Epoch 163/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2466 - accuracy: 0.8896\n",
            "Epoch 164/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2520 - accuracy: 0.8798\n",
            "Epoch 165/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.2550 - accuracy: 0.8857\n",
            "Epoch 166/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2517 - accuracy: 0.8818\n",
            "Epoch 167/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2450 - accuracy: 0.8912\n",
            "Epoch 168/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2458 - accuracy: 0.8862\n",
            "Epoch 169/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2338 - accuracy: 0.8910\n",
            "Epoch 170/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2404 - accuracy: 0.8921\n",
            "Epoch 171/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2383 - accuracy: 0.8951\n",
            "Epoch 172/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2580 - accuracy: 0.8834\n",
            "Epoch 173/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.2453 - accuracy: 0.8885\n",
            "Epoch 174/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2464 - accuracy: 0.8876\n",
            "Epoch 175/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2484 - accuracy: 0.8873\n",
            "Epoch 176/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2412 - accuracy: 0.8912\n",
            "Epoch 177/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2355 - accuracy: 0.8878\n",
            "Epoch 178/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2449 - accuracy: 0.8892\n",
            "Epoch 179/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2376 - accuracy: 0.8923\n",
            "Epoch 180/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2378 - accuracy: 0.8924\n",
            "Epoch 181/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2352 - accuracy: 0.8921\n",
            "Epoch 182/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2429 - accuracy: 0.8876\n",
            "Epoch 183/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2479 - accuracy: 0.8887\n",
            "Epoch 184/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2377 - accuracy: 0.8944\n",
            "Epoch 185/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2455 - accuracy: 0.8878\n",
            "Epoch 186/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2392 - accuracy: 0.8926\n",
            "Epoch 187/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2450 - accuracy: 0.8880\n",
            "Epoch 188/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2384 - accuracy: 0.8889\n",
            "Epoch 189/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2402 - accuracy: 0.8932\n",
            "Epoch 190/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2395 - accuracy: 0.8930\n",
            "Epoch 191/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2469 - accuracy: 0.8848\n",
            "Epoch 192/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2419 - accuracy: 0.8871\n",
            "Epoch 193/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2402 - accuracy: 0.8844\n",
            "Epoch 194/500\n",
            "12/12 [==============================] - 0s 14ms/step - loss: 0.2345 - accuracy: 0.8942\n",
            "Epoch 195/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2524 - accuracy: 0.8786\n",
            "Epoch 196/500\n",
            "12/12 [==============================] - 0s 14ms/step - loss: 0.2385 - accuracy: 0.8921\n",
            "Epoch 197/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2300 - accuracy: 0.8974\n",
            "Epoch 198/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2390 - accuracy: 0.8939\n",
            "Epoch 199/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2377 - accuracy: 0.8924\n",
            "Epoch 200/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2395 - accuracy: 0.8917\n",
            "Epoch 201/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2305 - accuracy: 0.8969\n",
            "Epoch 202/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2318 - accuracy: 0.8960\n",
            "Epoch 203/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2355 - accuracy: 0.8923\n",
            "Epoch 204/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2389 - accuracy: 0.8955\n",
            "Epoch 205/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2347 - accuracy: 0.8921\n",
            "Epoch 206/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2292 - accuracy: 0.8949\n",
            "Epoch 207/500\n",
            "12/12 [==============================] - 0s 14ms/step - loss: 0.2304 - accuracy: 0.8955\n",
            "Epoch 208/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2269 - accuracy: 0.8960\n",
            "Epoch 209/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2302 - accuracy: 0.8928\n",
            "Epoch 210/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2343 - accuracy: 0.8944\n",
            "Epoch 211/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2424 - accuracy: 0.8926\n",
            "Epoch 212/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2424 - accuracy: 0.8898\n",
            "Epoch 213/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2306 - accuracy: 0.8946\n",
            "Epoch 214/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2424 - accuracy: 0.8933\n",
            "Epoch 215/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2369 - accuracy: 0.8946\n",
            "Epoch 216/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2270 - accuracy: 0.9008\n",
            "Epoch 217/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2302 - accuracy: 0.8962\n",
            "Epoch 218/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2256 - accuracy: 0.8953\n",
            "Epoch 219/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2258 - accuracy: 0.8987\n",
            "Epoch 220/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2303 - accuracy: 0.8932\n",
            "Epoch 221/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2275 - accuracy: 0.8985\n",
            "Epoch 222/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2302 - accuracy: 0.8992\n",
            "Epoch 223/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2410 - accuracy: 0.8926\n",
            "Epoch 224/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2347 - accuracy: 0.8960\n",
            "Epoch 225/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2305 - accuracy: 0.8956\n",
            "Epoch 226/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2415 - accuracy: 0.8894\n",
            "Epoch 227/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2333 - accuracy: 0.8967\n",
            "Epoch 228/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2320 - accuracy: 0.8937\n",
            "Epoch 229/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2329 - accuracy: 0.8962\n",
            "Epoch 230/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2371 - accuracy: 0.8923\n",
            "Epoch 231/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2319 - accuracy: 0.8940\n",
            "Epoch 232/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2216 - accuracy: 0.9026\n",
            "Epoch 233/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2225 - accuracy: 0.8976\n",
            "Epoch 234/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2259 - accuracy: 0.8985\n",
            "Epoch 235/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2350 - accuracy: 0.8910\n",
            "Epoch 236/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2295 - accuracy: 0.8969\n",
            "Epoch 237/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2305 - accuracy: 0.8967\n",
            "Epoch 238/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2283 - accuracy: 0.8978\n",
            "Epoch 239/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2232 - accuracy: 0.8969\n",
            "Epoch 240/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2210 - accuracy: 0.8990\n",
            "Epoch 241/500\n",
            "12/12 [==============================] - 0s 7ms/step - loss: 0.2242 - accuracy: 0.8981\n",
            "Epoch 242/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2249 - accuracy: 0.8987\n",
            "Epoch 243/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2268 - accuracy: 0.8999\n",
            "Epoch 244/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2235 - accuracy: 0.8969\n",
            "Epoch 245/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2286 - accuracy: 0.8921\n",
            "Epoch 246/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2382 - accuracy: 0.8924\n",
            "Epoch 247/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2326 - accuracy: 0.8914\n",
            "Epoch 248/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2305 - accuracy: 0.8969\n",
            "Epoch 249/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2293 - accuracy: 0.8965\n",
            "Epoch 250/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2248 - accuracy: 0.8949\n",
            "Epoch 251/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2252 - accuracy: 0.8983\n",
            "Epoch 252/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2212 - accuracy: 0.9013\n",
            "Epoch 253/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2242 - accuracy: 0.8999\n",
            "Epoch 254/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2220 - accuracy: 0.9022\n",
            "Epoch 255/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2200 - accuracy: 0.8987\n",
            "Epoch 256/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2278 - accuracy: 0.9013\n",
            "Epoch 257/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2269 - accuracy: 0.9004\n",
            "Epoch 258/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2273 - accuracy: 0.8971\n",
            "Epoch 259/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2244 - accuracy: 0.8942\n",
            "Epoch 260/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2218 - accuracy: 0.9013\n",
            "Epoch 261/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2290 - accuracy: 0.8965\n",
            "Epoch 262/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2266 - accuracy: 0.8949\n",
            "Epoch 263/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2204 - accuracy: 0.9028\n",
            "Epoch 264/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2193 - accuracy: 0.9045\n",
            "Epoch 265/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2183 - accuracy: 0.8996\n",
            "Epoch 266/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2122 - accuracy: 0.9051\n",
            "Epoch 267/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2213 - accuracy: 0.8971\n",
            "Epoch 268/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2198 - accuracy: 0.9049\n",
            "Epoch 269/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2112 - accuracy: 0.9028\n",
            "Epoch 270/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2198 - accuracy: 0.8988\n",
            "Epoch 271/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2271 - accuracy: 0.9003\n",
            "Epoch 272/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2186 - accuracy: 0.8980\n",
            "Epoch 273/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2163 - accuracy: 0.9008\n",
            "Epoch 274/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2238 - accuracy: 0.8972\n",
            "Epoch 275/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2218 - accuracy: 0.9013\n",
            "Epoch 276/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2157 - accuracy: 0.9022\n",
            "Epoch 277/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2183 - accuracy: 0.9013\n",
            "Epoch 278/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2185 - accuracy: 0.9047\n",
            "Epoch 279/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2257 - accuracy: 0.8985\n",
            "Epoch 280/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2220 - accuracy: 0.8964\n",
            "Epoch 281/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2186 - accuracy: 0.9008\n",
            "Epoch 282/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2293 - accuracy: 0.8971\n",
            "Epoch 283/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.2177 - accuracy: 0.9013\n",
            "Epoch 284/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2310 - accuracy: 0.8930\n",
            "Epoch 285/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2274 - accuracy: 0.8969\n",
            "Epoch 286/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2151 - accuracy: 0.8972\n",
            "Epoch 287/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2195 - accuracy: 0.8996\n",
            "Epoch 288/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2199 - accuracy: 0.8965\n",
            "Epoch 289/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2174 - accuracy: 0.9017\n",
            "Epoch 290/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2206 - accuracy: 0.8967\n",
            "Epoch 291/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2161 - accuracy: 0.8985\n",
            "Epoch 292/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2169 - accuracy: 0.9020\n",
            "Epoch 293/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2197 - accuracy: 0.8965\n",
            "Epoch 294/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2191 - accuracy: 0.9004\n",
            "Epoch 295/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2197 - accuracy: 0.9015\n",
            "Epoch 296/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2235 - accuracy: 0.8955\n",
            "Epoch 297/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2192 - accuracy: 0.9038\n",
            "Epoch 298/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2184 - accuracy: 0.9033\n",
            "Epoch 299/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2210 - accuracy: 0.9006\n",
            "Epoch 300/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2161 - accuracy: 0.8992\n",
            "Epoch 301/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2109 - accuracy: 0.9038\n",
            "Epoch 302/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2181 - accuracy: 0.9047\n",
            "Epoch 303/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2205 - accuracy: 0.8987\n",
            "Epoch 304/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2077 - accuracy: 0.9051\n",
            "Epoch 305/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2207 - accuracy: 0.8994\n",
            "Epoch 306/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2180 - accuracy: 0.8980\n",
            "Epoch 307/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2251 - accuracy: 0.8965\n",
            "Epoch 308/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2185 - accuracy: 0.9015\n",
            "Epoch 309/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2145 - accuracy: 0.9010\n",
            "Epoch 310/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2200 - accuracy: 0.9063\n",
            "Epoch 311/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2185 - accuracy: 0.8987\n",
            "Epoch 312/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2252 - accuracy: 0.8971\n",
            "Epoch 313/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2221 - accuracy: 0.9008\n",
            "Epoch 314/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2212 - accuracy: 0.9024\n",
            "Epoch 315/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2127 - accuracy: 0.9036\n",
            "Epoch 316/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2177 - accuracy: 0.9015\n",
            "Epoch 317/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2187 - accuracy: 0.8980\n",
            "Epoch 318/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2168 - accuracy: 0.9006\n",
            "Epoch 319/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2151 - accuracy: 0.9051\n",
            "Epoch 320/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2141 - accuracy: 0.9044\n",
            "Epoch 321/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2108 - accuracy: 0.9042\n",
            "Epoch 322/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2178 - accuracy: 0.8988\n",
            "Epoch 323/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2231 - accuracy: 0.8987\n",
            "Epoch 324/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2179 - accuracy: 0.9022\n",
            "Epoch 325/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2171 - accuracy: 0.8978\n",
            "Epoch 326/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2217 - accuracy: 0.8972\n",
            "Epoch 327/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2136 - accuracy: 0.9022\n",
            "Epoch 328/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2094 - accuracy: 0.9052\n",
            "Epoch 329/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2163 - accuracy: 0.9006\n",
            "Epoch 330/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2117 - accuracy: 0.9068\n",
            "Epoch 331/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2151 - accuracy: 0.9015\n",
            "Epoch 332/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.2153 - accuracy: 0.9035\n",
            "Epoch 333/500\n",
            "12/12 [==============================] - 0s 14ms/step - loss: 0.2203 - accuracy: 0.8980\n",
            "Epoch 334/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2152 - accuracy: 0.9028\n",
            "Epoch 335/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2152 - accuracy: 0.9020\n",
            "Epoch 336/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2116 - accuracy: 0.9054\n",
            "Epoch 337/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2141 - accuracy: 0.8987\n",
            "Epoch 338/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2148 - accuracy: 0.9058\n",
            "Epoch 339/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2198 - accuracy: 0.9003\n",
            "Epoch 340/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2105 - accuracy: 0.9020\n",
            "Epoch 341/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2154 - accuracy: 0.9004\n",
            "Epoch 342/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2066 - accuracy: 0.9074\n",
            "Epoch 343/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2191 - accuracy: 0.9022\n",
            "Epoch 344/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2190 - accuracy: 0.9040\n",
            "Epoch 345/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2236 - accuracy: 0.8949\n",
            "Epoch 346/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2144 - accuracy: 0.9013\n",
            "Epoch 347/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2103 - accuracy: 0.9040\n",
            "Epoch 348/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2061 - accuracy: 0.9083\n",
            "Epoch 349/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2131 - accuracy: 0.9019\n",
            "Epoch 350/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2076 - accuracy: 0.9072\n",
            "Epoch 351/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2125 - accuracy: 0.9054\n",
            "Epoch 352/500\n",
            "12/12 [==============================] - 0s 14ms/step - loss: 0.2182 - accuracy: 0.9006\n",
            "Epoch 353/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2180 - accuracy: 0.9006\n",
            "Epoch 354/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2141 - accuracy: 0.9033\n",
            "Epoch 355/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2076 - accuracy: 0.9049\n",
            "Epoch 356/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2111 - accuracy: 0.9079\n",
            "Epoch 357/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2068 - accuracy: 0.9049\n",
            "Epoch 358/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2191 - accuracy: 0.9019\n",
            "Epoch 359/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2074 - accuracy: 0.9081\n",
            "Epoch 360/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2091 - accuracy: 0.9049\n",
            "Epoch 361/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2132 - accuracy: 0.9077\n",
            "Epoch 362/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2134 - accuracy: 0.9051\n",
            "Epoch 363/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2070 - accuracy: 0.9079\n",
            "Epoch 364/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2125 - accuracy: 0.9074\n",
            "Epoch 365/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2094 - accuracy: 0.9074\n",
            "Epoch 366/500\n",
            "12/12 [==============================] - 0s 14ms/step - loss: 0.2093 - accuracy: 0.9040\n",
            "Epoch 367/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2062 - accuracy: 0.9077\n",
            "Epoch 368/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2129 - accuracy: 0.9056\n",
            "Epoch 369/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2141 - accuracy: 0.9072\n",
            "Epoch 370/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2173 - accuracy: 0.8997\n",
            "Epoch 371/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2085 - accuracy: 0.9058\n",
            "Epoch 372/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2136 - accuracy: 0.9051\n",
            "Epoch 373/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2092 - accuracy: 0.9058\n",
            "Epoch 374/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2086 - accuracy: 0.9031\n",
            "Epoch 375/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2072 - accuracy: 0.9051\n",
            "Epoch 376/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2108 - accuracy: 0.9068\n",
            "Epoch 377/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2206 - accuracy: 0.8987\n",
            "Epoch 378/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2089 - accuracy: 0.9013\n",
            "Epoch 379/500\n",
            "12/12 [==============================] - 0s 14ms/step - loss: 0.2172 - accuracy: 0.9031\n",
            "Epoch 380/500\n",
            "12/12 [==============================] - 0s 15ms/step - loss: 0.2140 - accuracy: 0.9010\n",
            "Epoch 381/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2160 - accuracy: 0.9040\n",
            "Epoch 382/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2149 - accuracy: 0.9042\n",
            "Epoch 383/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2149 - accuracy: 0.9045\n",
            "Epoch 384/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2066 - accuracy: 0.9047\n",
            "Epoch 385/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2103 - accuracy: 0.9079\n",
            "Epoch 386/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2061 - accuracy: 0.9076\n",
            "Epoch 387/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2066 - accuracy: 0.9124\n",
            "Epoch 388/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.2070 - accuracy: 0.9061\n",
            "Epoch 389/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2080 - accuracy: 0.9092\n",
            "Epoch 390/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2123 - accuracy: 0.8985\n",
            "Epoch 391/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2125 - accuracy: 0.9038\n",
            "Epoch 392/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2093 - accuracy: 0.9036\n",
            "Epoch 393/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2106 - accuracy: 0.9045\n",
            "Epoch 394/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2066 - accuracy: 0.9036\n",
            "Epoch 395/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2158 - accuracy: 0.9003\n",
            "Epoch 396/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2095 - accuracy: 0.9067\n",
            "Epoch 397/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2081 - accuracy: 0.9045\n",
            "Epoch 398/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2007 - accuracy: 0.9108\n",
            "Epoch 399/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2022 - accuracy: 0.9106\n",
            "Epoch 400/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2026 - accuracy: 0.9084\n",
            "Epoch 401/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2100 - accuracy: 0.9077\n",
            "Epoch 402/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2052 - accuracy: 0.9068\n",
            "Epoch 403/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2111 - accuracy: 0.9028\n",
            "Epoch 404/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2074 - accuracy: 0.9054\n",
            "Epoch 405/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2158 - accuracy: 0.9013\n",
            "Epoch 406/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.2097 - accuracy: 0.9031\n",
            "Epoch 407/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2133 - accuracy: 0.9026\n",
            "Epoch 408/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2157 - accuracy: 0.9036\n",
            "Epoch 409/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2136 - accuracy: 0.9047\n",
            "Epoch 410/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2128 - accuracy: 0.9074\n",
            "Epoch 411/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2038 - accuracy: 0.9047\n",
            "Epoch 412/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2028 - accuracy: 0.9081\n",
            "Epoch 413/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2027 - accuracy: 0.9058\n",
            "Epoch 414/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2051 - accuracy: 0.9079\n",
            "Epoch 415/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.2104 - accuracy: 0.9040\n",
            "Epoch 416/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2161 - accuracy: 0.8999\n",
            "Epoch 417/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2102 - accuracy: 0.9054\n",
            "Epoch 418/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2165 - accuracy: 0.9031\n",
            "Epoch 419/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2013 - accuracy: 0.9116\n",
            "Epoch 420/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2016 - accuracy: 0.9102\n",
            "Epoch 421/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2073 - accuracy: 0.9058\n",
            "Epoch 422/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2058 - accuracy: 0.9077\n",
            "Epoch 423/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2097 - accuracy: 0.9035\n",
            "Epoch 424/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2105 - accuracy: 0.9070\n",
            "Epoch 425/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2110 - accuracy: 0.9063\n",
            "Epoch 426/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2071 - accuracy: 0.9060\n",
            "Epoch 427/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2045 - accuracy: 0.9106\n",
            "Epoch 428/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2068 - accuracy: 0.9065\n",
            "Epoch 429/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2055 - accuracy: 0.9045\n",
            "Epoch 430/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2045 - accuracy: 0.9106\n",
            "Epoch 431/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.1995 - accuracy: 0.9088\n",
            "Epoch 432/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2060 - accuracy: 0.9086\n",
            "Epoch 433/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.2095 - accuracy: 0.9067\n",
            "Epoch 434/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2053 - accuracy: 0.9044\n",
            "Epoch 435/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2041 - accuracy: 0.9054\n",
            "Epoch 436/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2025 - accuracy: 0.9070\n",
            "Epoch 437/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2137 - accuracy: 0.9068\n",
            "Epoch 438/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2114 - accuracy: 0.9054\n",
            "Epoch 439/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2065 - accuracy: 0.9070\n",
            "Epoch 440/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2006 - accuracy: 0.9106\n",
            "Epoch 441/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2043 - accuracy: 0.9093\n",
            "Epoch 442/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.2087 - accuracy: 0.9022\n",
            "Epoch 443/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2075 - accuracy: 0.9038\n",
            "Epoch 444/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2042 - accuracy: 0.9076\n",
            "Epoch 445/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2078 - accuracy: 0.9060\n",
            "Epoch 446/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2031 - accuracy: 0.9077\n",
            "Epoch 447/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2058 - accuracy: 0.9084\n",
            "Epoch 448/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2094 - accuracy: 0.9001\n",
            "Epoch 449/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2088 - accuracy: 0.9042\n",
            "Epoch 450/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2103 - accuracy: 0.9042\n",
            "Epoch 451/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.2055 - accuracy: 0.9049\n",
            "Epoch 452/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2046 - accuracy: 0.9090\n",
            "Epoch 453/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2002 - accuracy: 0.9111\n",
            "Epoch 454/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.1976 - accuracy: 0.9118\n",
            "Epoch 455/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2026 - accuracy: 0.9104\n",
            "Epoch 456/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2091 - accuracy: 0.9042\n",
            "Epoch 457/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2009 - accuracy: 0.9150\n",
            "Epoch 458/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2056 - accuracy: 0.9108\n",
            "Epoch 459/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2034 - accuracy: 0.9090\n",
            "Epoch 460/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2116 - accuracy: 0.9015\n",
            "Epoch 461/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2158 - accuracy: 0.9003\n",
            "Epoch 462/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2040 - accuracy: 0.9063\n",
            "Epoch 463/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2161 - accuracy: 0.9038\n",
            "Epoch 464/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2003 - accuracy: 0.9111\n",
            "Epoch 465/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2032 - accuracy: 0.9077\n",
            "Epoch 466/500\n",
            "12/12 [==============================] - 0s 8ms/step - loss: 0.2063 - accuracy: 0.9044\n",
            "Epoch 467/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2093 - accuracy: 0.9063\n",
            "Epoch 468/500\n",
            "12/12 [==============================] - 0s 9ms/step - loss: 0.2101 - accuracy: 0.9056\n",
            "Epoch 469/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.2067 - accuracy: 0.9104\n",
            "Epoch 470/500\n",
            "12/12 [==============================] - 0s 14ms/step - loss: 0.2000 - accuracy: 0.9108\n",
            "Epoch 471/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.1985 - accuracy: 0.9122\n",
            "Epoch 472/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.1908 - accuracy: 0.9141\n",
            "Epoch 473/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2021 - accuracy: 0.9116\n",
            "Epoch 474/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.1969 - accuracy: 0.9068\n",
            "Epoch 475/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2091 - accuracy: 0.9061\n",
            "Epoch 476/500\n",
            "12/12 [==============================] - 0s 14ms/step - loss: 0.1972 - accuracy: 0.9111\n",
            "Epoch 477/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2085 - accuracy: 0.9052\n",
            "Epoch 478/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2087 - accuracy: 0.9038\n",
            "Epoch 479/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2024 - accuracy: 0.9099\n",
            "Epoch 480/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2042 - accuracy: 0.9072\n",
            "Epoch 481/500\n",
            "12/12 [==============================] - 0s 10ms/step - loss: 0.2098 - accuracy: 0.9019\n",
            "Epoch 482/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2045 - accuracy: 0.9102\n",
            "Epoch 483/500\n",
            "12/12 [==============================] - 0s 14ms/step - loss: 0.2063 - accuracy: 0.9095\n",
            "Epoch 484/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2005 - accuracy: 0.9067\n",
            "Epoch 485/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2069 - accuracy: 0.9108\n",
            "Epoch 486/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2026 - accuracy: 0.9088\n",
            "Epoch 487/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2016 - accuracy: 0.9102\n",
            "Epoch 488/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2090 - accuracy: 0.9086\n",
            "Epoch 489/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2033 - accuracy: 0.9084\n",
            "Epoch 490/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2094 - accuracy: 0.9040\n",
            "Epoch 491/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2082 - accuracy: 0.9086\n",
            "Epoch 492/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2024 - accuracy: 0.9108\n",
            "Epoch 493/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2056 - accuracy: 0.9081\n",
            "Epoch 494/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2059 - accuracy: 0.9072\n",
            "Epoch 495/500\n",
            "12/12 [==============================] - 0s 12ms/step - loss: 0.2043 - accuracy: 0.9068\n",
            "Epoch 496/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2081 - accuracy: 0.9038\n",
            "Epoch 497/500\n",
            "12/12 [==============================] - 0s 14ms/step - loss: 0.1998 - accuracy: 0.9090\n",
            "Epoch 498/500\n",
            "12/12 [==============================] - 0s 13ms/step - loss: 0.2027 - accuracy: 0.9115\n",
            "Epoch 499/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2013 - accuracy: 0.9070\n",
            "Epoch 500/500\n",
            "12/12 [==============================] - 0s 11ms/step - loss: 0.2025 - accuracy: 0.9083\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.src.callbacks.History at 0x794fbe20af80>"
            ]
          },
          "metadata": {},
          "execution_count": 416
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model5.evaluate(X_test,y_test)"
      ],
      "metadata": {
        "id": "Mj0liJb7yV9q",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "outputId": "86561b8c-8817-49b0-ab55-e37dc1ae07e5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "NameError",
          "evalue": "name 'model5' is not defined",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-1-73ed22435567>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmodel5\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mevaluate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_test\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my_test\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m: name 'model5' is not defined"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pre=model.predict(X_test)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XE-3lsv0-u15",
        "outputId": "9f9b167b-58dd-4979-86c1-a2700dfd6cfc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "44/44 [==============================] - 0s 2ms/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "YWVIsagQtQKM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y_pre"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jeotbQS8-vOr",
        "outputId": "8bc7457b-f8e7-44c3-ff4a-c57ae5f1b2d1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0.84574825],\n",
              "       [0.0081464 ],\n",
              "       [0.03969785],\n",
              "       ...,\n",
              "       [0.25373465],\n",
              "       [0.45167094],\n",
              "       [0.0566246 ]], dtype=float32)"
            ]
          },
          "metadata": {},
          "execution_count": 395
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_predict = []\n",
        "for i in y_pre:\n",
        "  if i > 0.5:\n",
        "    y_predict.append(1)\n",
        "  else:\n",
        "    y_predict.append(0)\n",
        "y_predict= np.array(y_predict)"
      ],
      "metadata": {
        "id": "UbSHqsGLotEE"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y_testt=np.array(y_test)"
      ],
      "metadata": {
        "id": "o3zsTtEQ-wsU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y_testt"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "80uf-v7r-yUJ",
        "outputId": "33457dcd-0744-4534-942f-46bacb6e4f4e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1, 0, 0, ..., 1, 0, 1])"
            ]
          },
          "metadata": {},
          "execution_count": 398
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_predict[200],y_testt[200]"
      ],
      "metadata": {
        "id": "l1Xt20XU-zt9",
        "outputId": "70eb589b-1708-4edf-8863-e8dd0156a227",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(0, 1)"
            ]
          },
          "metadata": {},
          "execution_count": 399
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(classification_report(y_testt,y_predict))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OX2g-TazyIuw",
        "outputId": "0a80a349-588b-4718-c320-013ce0f3f1ec"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.84      0.91      0.87      1031\n",
            "           1       0.67      0.51      0.58       376\n",
            "\n",
            "    accuracy                           0.80      1407\n",
            "   macro avg       0.75      0.71      0.72      1407\n",
            "weighted avg       0.79      0.80      0.79      1407\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cm=tf.math.confusion_matrix(y_testt,y_predict)\n",
        "type(cm)"
      ],
      "metadata": {
        "id": "3ag60Stg-1Fv",
        "outputId": "a2366065-cac1-48e5-dfa3-1cdd26c850cc",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensorflow.python.framework.ops.EagerTensor"
            ]
          },
          "metadata": {},
          "execution_count": 401
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.heatmap(cm, annot=True ,fmt='d')"
      ],
      "metadata": {
        "id": "SOZfF8D_-4G9",
        "outputId": "fcba4fae-88f1-4d1a-fa1e-15f001b7fc26",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 402
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cm=confusion_matrix(y_testt,y_predict)\n",
        "cm"
      ],
      "metadata": {
        "id": "9_ljEZLh-5ft",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "07d133f6-3dc6-427b-bf23-068019eb464e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[937,  94],\n",
              "       [185, 191]])"
            ]
          },
          "metadata": {},
          "execution_count": 403
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(5,5))\n",
        "sns.heatmap(cm,annot=True,fmt='d')\n",
        "plt.xlabel(\"Predicted\")\n",
        "plt.ylabel(\"True\")\n",
        "plt.legend()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 500
        },
        "id": "9xLP2GlfreK8",
        "outputId": "9b4a551c-c9dd-49d1-c456-e2134f85242b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:matplotlib.legend:No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x794fc7d4a230>"
            ]
          },
          "metadata": {},
          "execution_count": 404
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 500x500 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}