Cancer_AI.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Cancer-AI.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "CwQouagZEJSm"
      },
      "source": [
        "import pandas as pd\n",
        "\n",
        "dataset = pd.read_csv('cancer.csv')"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zychaM2VE6oF"
      },
      "source": [
        "x = dataset.drop(columns=[\"diagnosis(1=m, 0=b)\"])"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O_TcZBwzFVqJ"
      },
      "source": [
        "y = dataset[\"diagnosis(1=m, 0=b)\"]"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jQVFPaTgFke_"
      },
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2)"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7iJZZ4BYGGVQ"
      },
      "source": [
        "import tensorflow as tf\n",
        "\n",
        "model = tf.keras.models.Sequential()"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZPmToaIAGY6X"
      },
      "source": [
        "model.add(tf.keras.layers.Dense(256, input_shape=x_train.shape, activation='sigmoid'))\n",
        "model.add(tf.keras.layers.Dense(256, activation='sigmoid'))\n",
        "model.add(tf.keras.layers.Dense(1, activation='sigmoid'))"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AQS41P-1G-wf"
      },
      "source": [
        "model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6g50ckuXHR5f",
        "outputId": "23ac5533-493f-47cd-81f8-12b287c9f917"
      },
      "source": [
        "model.fit(x_train, y_train, epochs=1000)"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/1000\n",
            "WARNING:tensorflow:Model was constructed with shape (None, 455, 30) for input KerasTensor(type_spec=TensorSpec(shape=(None, 455, 30), dtype=tf.float32, name='dense_input'), name='dense_input', description=\"created by layer 'dense_input'\"), but it was called on an input with incompatible shape (None, 30).\n",
            "WARNING:tensorflow:Model was constructed with shape (None, 455, 30) for input KerasTensor(type_spec=TensorSpec(shape=(None, 455, 30), dtype=tf.float32, name='dense_input'), name='dense_input', description=\"created by layer 'dense_input'\"), but it was called on an input with incompatible shape (None, 30).\n",
            "15/15 [==============================] - 1s 4ms/step - loss: 0.6684 - accuracy: 0.6088\n",
            "Epoch 2/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6220 - accuracy: 0.6484\n",
            "Epoch 3/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.5386 - accuracy: 0.7495\n",
            "Epoch 4/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.4114 - accuracy: 0.8330\n",
            "Epoch 5/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 0.2382 - accuracy: 0.9209\n",
            "Epoch 6/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 0.2175 - accuracy: 0.9231\n",
            "Epoch 7/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.2224 - accuracy: 0.9187\n",
            "Epoch 8/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.2179 - accuracy: 0.9253\n",
            "Epoch 9/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.2022 - accuracy: 0.9231\n",
            "Epoch 10/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.1959 - accuracy: 0.9319\n",
            "Epoch 11/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.2636 - accuracy: 0.9143\n",
            "Epoch 12/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.1935 - accuracy: 0.9319\n",
            "Epoch 13/1000\n",
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            "Epoch 14/1000\n",
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            "Epoch 15/1000\n",
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            "Epoch 16/1000\n",
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            "Epoch 17/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.1912 - accuracy: 0.9363\n",
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            "Epoch 20/1000\n",
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            "Epoch 23/1000\n",
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            "15/15 [==============================] - 0s 4ms/step - loss: 0.2316 - accuracy: 0.9121\n",
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            "15/15 [==============================] - 0s 4ms/step - loss: 0.1699 - accuracy: 0.9341\n",
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            "15/15 [==============================] - 0s 4ms/step - loss: 0.1838 - accuracy: 0.9385\n",
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            "15/15 [==============================] - 0s 3ms/step - loss: 0.1541 - accuracy: 0.9319\n",
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            "15/15 [==============================] - 0s 5ms/step - loss: 0.1353 - accuracy: 0.9473\n",
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            "15/15 [==============================] - 0s 4ms/step - loss: 0.1479 - accuracy: 0.9407\n",
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            "15/15 [==============================] - 0s 4ms/step - loss: 0.1381 - accuracy: 0.9451\n",
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            "Epoch 100/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.1318 - accuracy: 0.9385\n",
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            "15/15 [==============================] - 0s 4ms/step - loss: 0.1120 - accuracy: 0.9604\n",
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            "15/15 [==============================] - 0s 5ms/step - loss: 0.1388 - accuracy: 0.9341\n",
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            "15/15 [==============================] - 0s 4ms/step - loss: 0.1273 - accuracy: 0.9407\n",
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            "15/15 [==============================] - 0s 5ms/step - loss: 0.2995 - accuracy: 0.8791\n",
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            "Epoch 737/1000\n",
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            "Epoch 750/1000\n",
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            "Epoch 768/1000\n",
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            "Epoch 774/1000\n",
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            "Epoch 786/1000\n",
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            "Epoch 787/1000\n",
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            "Epoch 788/1000\n",
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            "Epoch 790/1000\n",
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            "Epoch 791/1000\n",
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            "Epoch 792/1000\n",
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            "Epoch 794/1000\n",
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            "Epoch 796/1000\n",
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            "Epoch 798/1000\n",
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            "Epoch 799/1000\n",
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            "Epoch 800/1000\n",
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            "Epoch 801/1000\n",
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            "Epoch 803/1000\n",
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            "Epoch 807/1000\n",
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            "Epoch 808/1000\n",
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            "Epoch 809/1000\n",
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            "Epoch 811/1000\n",
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            "Epoch 813/1000\n",
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            "Epoch 814/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0716 - accuracy: 0.9758\n",
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            "Epoch 816/1000\n",
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            "Epoch 819/1000\n",
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            "Epoch 820/1000\n",
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            "Epoch 822/1000\n",
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            "Epoch 824/1000\n",
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            "Epoch 825/1000\n",
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            "Epoch 826/1000\n",
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            "Epoch 827/1000\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 0.0751 - accuracy: 0.9648\n",
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            "Epoch 829/1000\n",
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            "Epoch 830/1000\n",
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            "Epoch 831/1000\n",
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            "15/15 [==============================] - 0s 7ms/step - loss: 0.0658 - accuracy: 0.9802\n",
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            "Epoch 834/1000\n",
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            "Epoch 835/1000\n",
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            "Epoch 838/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0678 - accuracy: 0.9648\n",
            "Epoch 839/1000\n",
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            "Epoch 840/1000\n",
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            "Epoch 841/1000\n",
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            "Epoch 843/1000\n",
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            "Epoch 846/1000\n",
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            "Epoch 847/1000\n",
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            "Epoch 848/1000\n",
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            "Epoch 849/1000\n",
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            "Epoch 850/1000\n",
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            "Epoch 851/1000\n",
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            "Epoch 852/1000\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0751 - accuracy: 0.9802\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0702 - accuracy: 0.9714\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0845 - accuracy: 0.9714\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.1149 - accuracy: 0.9451\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0681 - accuracy: 0.9758\n",
            "Epoch 878/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0779 - accuracy: 0.9736\n",
            "Epoch 879/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 0.0628 - accuracy: 0.9758\n",
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            "15/15 [==============================] - 0s 5ms/step - loss: 0.0574 - accuracy: 0.9780\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0952 - accuracy: 0.9648\n",
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            "15/15 [==============================] - 0s 4ms/step - loss: 0.0957 - accuracy: 0.9758\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.1255 - accuracy: 0.9538\n",
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            "15/15 [==============================] - 0s 5ms/step - loss: 0.1194 - accuracy: 0.9648\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0890 - accuracy: 0.9648\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0720 - accuracy: 0.9824\n",
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            "15/15 [==============================] - 0s 5ms/step - loss: 0.1577 - accuracy: 0.9407\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0726 - accuracy: 0.9692\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0748 - accuracy: 0.9670\n",
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            "15/15 [==============================] - 0s 5ms/step - loss: 0.1298 - accuracy: 0.9648\n",
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            "15/15 [==============================] - 0s 5ms/step - loss: 0.1015 - accuracy: 0.9670\n",
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            "15/15 [==============================] - 0s 5ms/step - loss: 0.0925 - accuracy: 0.9714\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0740 - accuracy: 0.9670\n",
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            "15/15 [==============================] - 0s 5ms/step - loss: 0.0872 - accuracy: 0.9714\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0767 - accuracy: 0.9714\n",
            "Epoch 927/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0846 - accuracy: 0.9648\n",
            "Epoch 928/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 0.0899 - accuracy: 0.9670\n",
            "Epoch 929/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0946 - accuracy: 0.9626\n",
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            "15/15 [==============================] - 0s 5ms/step - loss: 0.0843 - accuracy: 0.9758\n",
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            "15/15 [==============================] - 0s 5ms/step - loss: 0.0847 - accuracy: 0.9758\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0890 - accuracy: 0.9692\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.1182 - accuracy: 0.9560\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0848 - accuracy: 0.9670\n",
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            "15/15 [==============================] - 0s 7ms/step - loss: 0.1308 - accuracy: 0.9516\n",
            "Epoch 936/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0914 - accuracy: 0.9626\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0845 - accuracy: 0.9670\n",
            "Epoch 938/1000\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 0.0773 - accuracy: 0.9648\n",
            "Epoch 939/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0829 - accuracy: 0.9648\n",
            "Epoch 940/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 0.0946 - accuracy: 0.9670\n",
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            "15/15 [==============================] - 0s 5ms/step - loss: 0.0791 - accuracy: 0.9714\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0823 - accuracy: 0.9758\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.1320 - accuracy: 0.9626\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0959 - accuracy: 0.9560\n",
            "Epoch 945/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0785 - accuracy: 0.9670\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0915 - accuracy: 0.9648\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.1200 - accuracy: 0.9604\n",
            "Epoch 948/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0918 - accuracy: 0.9714\n",
            "Epoch 949/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0725 - accuracy: 0.9670\n",
            "Epoch 950/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0848 - accuracy: 0.9670\n",
            "Epoch 951/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0849 - accuracy: 0.9648\n",
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            "15/15 [==============================] - 0s 7ms/step - loss: 0.0892 - accuracy: 0.9648\n",
            "Epoch 953/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.1047 - accuracy: 0.9692\n",
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            "15/15 [==============================] - 0s 5ms/step - loss: 0.1495 - accuracy: 0.9516\n",
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            "15/15 [==============================] - 0s 5ms/step - loss: 0.0844 - accuracy: 0.9604\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0848 - accuracy: 0.9626\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0698 - accuracy: 0.9736\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0824 - accuracy: 0.9714\n",
            "Epoch 959/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0800 - accuracy: 0.9714\n",
            "Epoch 960/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 0.0761 - accuracy: 0.9736\n",
            "Epoch 961/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0687 - accuracy: 0.9736\n",
            "Epoch 962/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0701 - accuracy: 0.9670\n",
            "Epoch 963/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0713 - accuracy: 0.9736\n",
            "Epoch 964/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0923 - accuracy: 0.9648\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0868 - accuracy: 0.9714\n",
            "Epoch 966/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0764 - accuracy: 0.9648\n",
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            "15/15 [==============================] - 0s 7ms/step - loss: 0.0781 - accuracy: 0.9648\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.1056 - accuracy: 0.9626\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0799 - accuracy: 0.9692\n",
            "Epoch 970/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 0.1020 - accuracy: 0.9626\n",
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            "15/15 [==============================] - 0s 6ms/step - loss: 0.0964 - accuracy: 0.9626\n",
            "Epoch 972/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0675 - accuracy: 0.9670\n",
            "Epoch 973/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.1152 - accuracy: 0.9604\n",
            "Epoch 974/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0920 - accuracy: 0.9692\n",
            "Epoch 975/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0680 - accuracy: 0.9692\n",
            "Epoch 976/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 0.0724 - accuracy: 0.9648\n",
            "Epoch 977/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0688 - accuracy: 0.9626\n",
            "Epoch 978/1000\n",
            "15/15 [==============================] - 0s 9ms/step - loss: 0.0786 - accuracy: 0.9692\n",
            "Epoch 979/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.1027 - accuracy: 0.9648\n",
            "Epoch 980/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.1067 - accuracy: 0.9626\n",
            "Epoch 981/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.1374 - accuracy: 0.9429\n",
            "Epoch 982/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 0.0993 - accuracy: 0.9626\n",
            "Epoch 983/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0717 - accuracy: 0.9736\n",
            "Epoch 984/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0677 - accuracy: 0.9692\n",
            "Epoch 985/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.1010 - accuracy: 0.9714\n",
            "Epoch 986/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0851 - accuracy: 0.9758\n",
            "Epoch 987/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0812 - accuracy: 0.9736\n",
            "Epoch 988/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0906 - accuracy: 0.9670\n",
            "Epoch 989/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.1227 - accuracy: 0.9582\n",
            "Epoch 990/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.1009 - accuracy: 0.9648\n",
            "Epoch 991/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0815 - accuracy: 0.9692\n",
            "Epoch 992/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0671 - accuracy: 0.9692\n",
            "Epoch 993/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0792 - accuracy: 0.9736\n",
            "Epoch 994/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 0.1995 - accuracy: 0.9099\n",
            "Epoch 995/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0833 - accuracy: 0.9692\n",
            "Epoch 996/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 0.1388 - accuracy: 0.9473\n",
            "Epoch 997/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0825 - accuracy: 0.9736\n",
            "Epoch 998/1000\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 0.1065 - accuracy: 0.9648\n",
            "Epoch 999/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 0.0794 - accuracy: 0.9670\n",
            "Epoch 1000/1000\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 0.0937 - accuracy: 0.9714\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<tensorflow.python.keras.callbacks.History at 0x7f720cffe3d0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "66mrzt3eHnHP",
        "outputId": "06942f66-5517-45fc-e575-36bfe63104dd"
      },
      "source": [
        "model.evaluate(x_test, y_test)"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Model was constructed with shape (None, 455, 30) for input KerasTensor(type_spec=TensorSpec(shape=(None, 455, 30), dtype=tf.float32, name='dense_input'), name='dense_input', description=\"created by layer 'dense_input'\"), but it was called on an input with incompatible shape (None, 30).\n",
            "4/4 [==============================] - 0s 4ms/step - loss: 0.1309 - accuracy: 0.9561\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.13094152510166168, 0.9561403393745422]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zERFjUoPIMg2"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}