01_Neural_network_regression_with_TensorFlow_Exercises.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyOUAp3Qk8puvGJiapYSHdrD",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/fedassembly/tensorflow-cert-prep/blob/main/01_Neural_network_regression_with_TensorFlow_Exercises.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import tensorflow as tf\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd"
      ],
      "metadata": {
        "id": "M-Ys0F78i8G8"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def plot_loss(history, label='', n=0):\n",
        "  # Use a log scale on y-axis to show the wide range of values.\n",
        "  colors = plt.rcParams['axes.prop_cycle'].by_key()['color']\n",
        "  plt.semilogy(history.epoch, history.history['loss'],\n",
        "               color=colors[n], label='Train ' + str(label))\n",
        "  plt.semilogy(history.epoch, history.history['val_loss'],\n",
        "               color=colors[n], label='Val ' + str(label),\n",
        "               linestyle=\"--\")\n",
        "  plt.xlabel('Epoch')\n",
        "  plt.ylabel('Loss')\n",
        "  plt.legend()"
      ],
      "metadata": {
        "id": "yGpexxZsvMb6"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "1. Create your own regression dataset (or make the one we created in \"Create data to view and fit\" bigger) and build fit a model to it."
      ],
      "metadata": {
        "id": "YHQCiNSghzQ8"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "x1 = np.random.default_rng(1).normal(size=1000)\n",
        "x2 = np.random.default_rng(2).normal(size=1000)\n",
        "e = np.random.default_rng(3).normal(size=1000)\n",
        "y = 10 + 2*x1 - 5*x2**2 + e\n",
        "X = np.c_[x1, x2]\n",
        "X_train = X[:800]\n",
        "X_val = X[800:900]\n",
        "X_test = X[900:]\n",
        "y_train = y[:800]\n",
        "y_val = y[800:900]\n",
        "y_test = y[900:]\n",
        "print(\"X train shape:\", X_train.shape)\n",
        "print(\"X val shape:\", X_val.shape)\n",
        "print(\"X test shape:\", X_test.shape)\n",
        "print(\"y train shape:\", y_train.shape)\n",
        "print(\"y val shape:\", y_val.shape)\n",
        "print(\"y test shape:\", y_test.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aOY29lDPi7UT",
        "outputId": "d6af3cfc-5c3b-4dc3-83b4-ef5b704f53b5"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "X train shape: (800, 2)\n",
            "X val shape: (100, 2)\n",
            "X test shape: (100, 2)\n",
            "y train shape: (800,)\n",
            "y val shape: (100,)\n",
            "y test shape: (100,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model_1 = tf.keras.Sequential([\n",
        "    tf.keras.layers.Dense(1, input_shape=(2,), # shape of one single example eg X[0].shape\n",
        "                          bias_initializer=tf.keras.initializers.Constant(np.mean(y_train)))\n",
        "], name=\"mod_1\")\n",
        "\n",
        "model_1.compile(loss=tf.keras.losses.mae,\n",
        "                optimizer=tf.keras.optimizers.SGD(),\n",
        "                metrics=[\"mae\"],\n",
        "                )\n",
        "\n",
        "model_1.summary()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JwvqFv-imD0W",
        "outputId": "26edcca2-b309-48bb-e26d-1194c8d6a663"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"mod_1\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " dense (Dense)               (None, 1)                 3         \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 3 (12.00 Byte)\n",
            "Trainable params: 3 (12.00 Byte)\n",
            "Non-trainable params: 0 (0.00 Byte)\n",
            "_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "history_1 = model_1.fit(X_train, y_train, epochs=100, validation_data=(X_val, y_val), verbose=0)"
      ],
      "metadata": {
        "id": "qewe2Hx3qgL4"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plot_loss(history_1, 'mod_1', 0)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "auK8GmvVv1CQ",
        "outputId": "5af73cf4-fbe1-4958-a3a8-ce23e94b2e62"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "2. Try building a neural network with 4 Dense layers and fitting it to your own regression dataset, how does it perform?"
      ],
      "metadata": {
        "id": "Rp5uyTu6i1VV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model_2 = tf.keras.Sequential([\n",
        "    tf.keras.layers.Dense(16, input_shape=(2,)),\n",
        "    tf.keras.layers.Dense(8),\n",
        "    tf.keras.layers.Dense(4),\n",
        "    tf.keras.layers.Dense(1, bias_initializer=tf.keras.initializers.Constant(np.mean(y_train))),\n",
        "], name=\"mod_2\")\n",
        "\n",
        "model_2.compile(loss=tf.keras.losses.mae,\n",
        "                optimizer=tf.keras.optimizers.SGD(),\n",
        "                metrics=[\"mae\"],\n",
        "                )\n",
        "\n",
        "model_2.summary()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "swGQPiHMi7vb",
        "outputId": "40289343-92cc-420c-e36e-f30753529cde"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"mod_2\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " dense_1 (Dense)             (None, 16)                48        \n",
            "                                                                 \n",
            " dense_2 (Dense)             (None, 8)                 136       \n",
            "                                                                 \n",
            " dense_3 (Dense)             (None, 4)                 36        \n",
            "                                                                 \n",
            " dense_4 (Dense)             (None, 1)                 5         \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 225 (900.00 Byte)\n",
            "Trainable params: 225 (900.00 Byte)\n",
            "Non-trainable params: 0 (0.00 Byte)\n",
            "_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "history_2 = model_2.fit(X_train, y_train, epochs=100, validation_data=(X_val, y_val), verbose=0)"
      ],
      "metadata": {
        "id": "VMdCgcVhrT3Q"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plot_loss(history_2, 'mod_2', 1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        },
        "id": "B1xx6ufqwNio",
        "outputId": "d90410d5-57af-4d25-eeb8-6f1a30c2c182"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "3. Try and improve the results we got on the insurance dataset, some things you might want to try include:\n",
        "  * Building a larger model (how does one with 4 dense layers go?).\n",
        "  * Increasing the number of units in each layer.\n",
        "  * Lookup the documentation of [Adam](https://www.tensorflow.org/api_docs/python/tf/keras/optimizers/Adam) and find out what the first parameter is, what happens if you increase it by 10x?\n",
        "  * What happens if you train for longer (say 300 epochs instead of 200)?"
      ],
      "metadata": {
        "id": "_hHVXDSAi3m5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model_3 = tf.keras.Sequential([\n",
        "    tf.keras.layers.Dense(32, input_shape=(2,)),\n",
        "    tf.keras.layers.Dense(16),\n",
        "    tf.keras.layers.Dense(8),\n",
        "    tf.keras.layers.Dense(1, bias_initializer=tf.keras.initializers.Constant(np.mean(y_train))),\n",
        "], name=\"mod_3\")\n",
        "model_3.compile(loss=tf.keras.losses.mae,\n",
        "              optimizer=tf.keras.optimizers.SGD(),\n",
        "              metrics=[\"mae\"])\n",
        "history_3 = model_3.fit(X_train, y_train, epochs=20, validation_data=(X_val, y_val), verbose=0)\n",
        "plot_loss(history_3, 'mod_3', 2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        },
        "id": "i2NEfj3nt1ne",
        "outputId": "8df649f2-54d5-46f3-8df6-334a549d1d84"
      },
      "execution_count": 10,
      "outputs": [
        {
          "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": [
        "model_4 = tf.keras.Sequential([\n",
        "    tf.keras.layers.Dense(32, input_shape=(2,)),\n",
        "    tf.keras.layers.Dense(16),\n",
        "    tf.keras.layers.Dense(8),\n",
        "    tf.keras.layers.Dense(4),\n",
        "    tf.keras.layers.Dense(1, bias_initializer=tf.keras.initializers.Constant(np.mean(y_train))),\n",
        "], name=\"mod_4\")\n",
        "model_4.compile(loss=tf.keras.losses.mae,\n",
        "              optimizer=tf.keras.optimizers.SGD(),\n",
        "              metrics=[\"mae\"])\n",
        "history_4 = model_4.fit(X_train, y_train, epochs=20, validation_data=(X_val, y_val), verbose=0)\n",
        "plot_loss(history_4, 'mod_4', 3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        },
        "id": "2NIIGno-zf1e",
        "outputId": "bc4665c6-b7dd-4ecb-e58c-1a1f6e0e3137"
      },
      "execution_count": 11,
      "outputs": [
        {
          "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": [
        "model_5 = tf.keras.Sequential([\n",
        "    tf.keras.layers.Dense(16, input_shape=(2,)),\n",
        "    tf.keras.layers.Dense(8),\n",
        "    tf.keras.layers.Dense(4),\n",
        "    tf.keras.layers.Dense(1, bias_initializer=tf.keras.initializers.Constant(np.mean(y_train))),\n",
        "], name=\"mod_5\")\n",
        "model_5.compile(loss=tf.keras.losses.mae,\n",
        "              optimizer=tf.keras.optimizers.Adam(),\n",
        "              metrics=[\"mae\"])\n",
        "history_5 = model_5.fit(X_train, y_train, epochs=20, validation_data=(X_val, y_val), verbose=0)\n",
        "plot_loss(history_5, 'mod_5', 4)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        },
        "id": "oj9AazAiztwY",
        "outputId": "f578d097-6c87-4ffe-980a-10655c5c0b92"
      },
      "execution_count": 12,
      "outputs": [
        {
          "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": [
        "model_6 = tf.keras.Sequential([\n",
        "    tf.keras.layers.Dense(16, input_shape=(2,)),\n",
        "    tf.keras.layers.Dense(8),\n",
        "    tf.keras.layers.Dense(4),\n",
        "    tf.keras.layers.Dense(1, bias_initializer=tf.keras.initializers.Constant(np.mean(y_train))),\n",
        "], name=\"mod_6\")\n",
        "model_6.compile(loss=tf.keras.losses.mae,\n",
        "              optimizer=tf.keras.optimizers.Adam(learning_rate=0.01),\n",
        "              metrics=[\"mae\"])\n",
        "history_6 = model_6.fit(X_train, y_train, epochs=20, validation_data=(X_val, y_val), verbose=0)\n",
        "plot_loss(history_6, 'mod_6', 5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        },
        "id": "DXHO229YzuWB",
        "outputId": "cf49cdf1-c11f-4d8a-dcd6-aacfd6ea095f"
      },
      "execution_count": 13,
      "outputs": [
        {
          "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": [
        "print(\"Mod_1:\", model_1.evaluate(X_test, y_test, verbose=0)[0])\n",
        "print(\"Mod_2:\", model_2.evaluate(X_test, y_test, verbose=0)[0])\n",
        "print(\"Mod_3:\", model_3.evaluate(X_test, y_test, verbose=0)[0])\n",
        "print(\"Mod_4:\", model_4.evaluate(X_test, y_test, verbose=0)[0])\n",
        "print(\"Mod_5:\", model_5.evaluate(X_test, y_test, verbose=0)[0])\n",
        "print(\"Mod_6:\", model_6.evaluate(X_test, y_test, verbose=0)[0])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eNEzXGhq00nM",
        "outputId": "395302f0-f89b-46b7-93a5-f8d434d2e86c"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mod_1: 5.023793697357178\n",
            "Mod_2: 5.061392307281494\n",
            "Mod_3: 5.043223857879639\n",
            "Mod_4: 5.01222038269043\n",
            "Mod_5: 5.052402496337891\n",
            "Mod_6: 5.0628886222839355\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plot_loss(history_1, 'mod_1', 0)\n",
        "plot_loss(history_2, 'mod_2', 1)\n",
        "plot_loss(history_3, 'mod_3', 2)\n",
        "plot_loss(history_4, 'mod_4', 3)\n",
        "plot_loss(history_5, 'mod_5', 4)\n",
        "plot_loss(history_6, 'mod_6', 5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "EJVBO_KW0ZcZ",
        "outputId": "0e52488e-b359-4067-9623-85165c60e1ed"
      },
      "execution_count": 15,
      "outputs": [
        {
          "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": [
        "model_7 = tf.keras.Sequential([\n",
        "    tf.keras.layers.Dense(64, activation=\"relu\", input_shape=(2,)),\n",
        "    tf.keras.layers.Dense(32, activation=\"relu\"),\n",
        "    tf.keras.layers.Dense(16, activation=\"relu\"),\n",
        "    tf.keras.layers.Dense(8, activation=\"relu\"),\n",
        "    tf.keras.layers.Dense(4, activation=\"relu\"),\n",
        "    tf.keras.layers.Dropout(0.5),\n",
        "    tf.keras.layers.Dense(1, bias_initializer=tf.keras.initializers.Constant(np.mean(y_train))),\n",
        "], name=\"mod_7\")\n",
        "model_7.compile(loss=tf.keras.losses.mae,\n",
        "                optimizer=tf.keras.optimizers.SGD(learning_rate=0.001),\n",
        "                metrics=[\"mae\"])\n",
        "early_stopping = tf.keras.callbacks.EarlyStopping(\n",
        "    patience=50,\n",
        "    restore_best_weights=True,\n",
        ")\n",
        "history_7 = model_7.fit(X_train, y_train, epochs=500, callbacks=[early_stopping], batch_size=32, validation_data=(X_val, y_val), verbose=0)\n",
        "plot_loss(history_7, 'mod_7', 5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        },
        "id": "lbnDeAqM1jnH",
        "outputId": "9329dd6d-642d-497f-b609-f315f3f8cd45"
      },
      "execution_count": 16,
      "outputs": [
        {
          "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": [
        "print(\"Mod_7:\", model_7.evaluate(X_test, y_test, verbose=0)[0])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AaozoNVVJDhS",
        "outputId": "6ef50f89-90e3-4568-c3d2-840ba567d3bf"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mod_7: 2.042032241821289\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(x2[900:], y_test, \"bo\")\n",
        "plt.plot(x2[900:], model_7.predict(X_test), \"ro\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 466
        },
        "id": "iMQesCRTNea4",
        "outputId": "c942d24b-92ba-4e7d-e949-f6f94936b17a"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "4/4 [==============================] - 0s 3ms/step\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7876b20e6530>]"
            ]
          },
          "metadata": {},
          "execution_count": 18
        },
        {
          "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": [
        "plt.plot(x1[900:], y_test, \"bo\")\n",
        "plt.plot(x1[900:], model_7.predict(X_test), \"ro\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 466
        },
        "id": "KmweI95RN-Zr",
        "outputId": "898388fa-935e-4664-a66b-031a880c3bd7"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "4/4 [==============================] - 0s 3ms/step\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7876b2154e20>]"
            ]
          },
          "metadata": {},
          "execution_count": 19
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "4. Import the [Boston pricing dataset](https://www.tensorflow.org/api_docs/python/tf/keras/datasets/boston_housing/load_data) from TensorFlow [`tf.keras.datasets`](https://www.tensorflow.org/api_docs/python/tf/keras/datasets) and model it."
      ],
      "metadata": {
        "id": "QrQYXuIgi6LJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from tensorflow.keras.datasets import boston_housing\n",
        "from sklearn.preprocessing import PowerTransformer, OneHotEncoder\n",
        "from sklearn.compose import ColumnTransformer"
      ],
      "metadata": {
        "id": "1RBZV-tjJ3iT"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "(x_train, y_train), (x_test, y_test) = boston_housing.load_data()"
      ],
      "metadata": {
        "id": "G2j2WAfxKC8d",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2fbaf320-e826-4e5c-e0a1-c123eb41981e"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/boston_housing.npz\n",
            "57026/57026 [==============================] - 0s 0us/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"X train shape:\", x_train.shape)\n",
        "print(\"X test shape:\", x_test.shape)\n",
        "print(\"y train shape:\", y_train.shape)\n",
        "print(\"y test shape:\", y_test.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XsowaT6dKQwu",
        "outputId": "fa1fb035-c8b3-4e63-c379-4102384b40a1"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "X train shape: (404, 13)\n",
            "X test shape: (102, 13)\n",
            "y train shape: (404,)\n",
            "y test shape: (102,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "train_df = pd.DataFrame(x_train)\n",
        "test_df = pd.DataFrame(x_test)\n",
        "train_df.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "uEw1kC6IOs4H",
        "outputId": "4e29f866-b325-4493-f11b-a7378ebfd70c"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               0           1           2           3           4           5   \\\n",
              "count  404.000000  404.000000  404.000000  404.000000  404.000000  404.000000   \n",
              "mean     3.745111   11.480198   11.104431    0.061881    0.557356    6.267082   \n",
              "std      9.240734   23.767711    6.811308    0.241238    0.117293    0.709788   \n",
              "min      0.006320    0.000000    0.460000    0.000000    0.385000    3.561000   \n",
              "25%      0.081437    0.000000    5.130000    0.000000    0.453000    5.874750   \n",
              "50%      0.268880    0.000000    9.690000    0.000000    0.538000    6.198500   \n",
              "75%      3.674808   12.500000   18.100000    0.000000    0.631000    6.609000   \n",
              "max     88.976200  100.000000   27.740000    1.000000    0.871000    8.725000   \n",
              "\n",
              "               6           7           8           9           10          11  \\\n",
              "count  404.000000  404.000000  404.000000  404.000000  404.000000  404.000000   \n",
              "mean    69.010644    3.740271    9.440594  405.898515   18.475990  354.783168   \n",
              "std     27.940665    2.030215    8.698360  166.374543    2.200382   94.111148   \n",
              "min      2.900000    1.129600    1.000000  188.000000   12.600000    0.320000   \n",
              "25%     45.475000    2.077100    4.000000  279.000000   17.225000  374.672500   \n",
              "50%     78.500000    3.142300    5.000000  330.000000   19.100000  391.250000   \n",
              "75%     94.100000    5.118000   24.000000  666.000000   20.200000  396.157500   \n",
              "max    100.000000   10.710300   24.000000  711.000000   22.000000  396.900000   \n",
              "\n",
              "               12  \n",
              "count  404.000000  \n",
              "mean    12.740817  \n",
              "std      7.254545  \n",
              "min      1.730000  \n",
              "25%      6.890000  \n",
              "50%     11.395000  \n",
              "75%     17.092500  \n",
              "max     37.970000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-74ffb416-26e1-45f2-bbe4-3b5991c6be9e\" 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>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "      <th>4</th>\n",
              "      <th>5</th>\n",
              "      <th>6</th>\n",
              "      <th>7</th>\n",
              "      <th>8</th>\n",
              "      <th>9</th>\n",
              "      <th>10</th>\n",
              "      <th>11</th>\n",
              "      <th>12</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>404.000000</td>\n",
              "      <td>404.000000</td>\n",
              "      <td>404.000000</td>\n",
              "      <td>404.000000</td>\n",
              "      <td>404.000000</td>\n",
              "      <td>404.000000</td>\n",
              "      <td>404.000000</td>\n",
              "      <td>404.000000</td>\n",
              "      <td>404.000000</td>\n",
              "      <td>404.000000</td>\n",
              "      <td>404.000000</td>\n",
              "      <td>404.000000</td>\n",
              "      <td>404.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>3.745111</td>\n",
              "      <td>11.480198</td>\n",
              "      <td>11.104431</td>\n",
              "      <td>0.061881</td>\n",
              "      <td>0.557356</td>\n",
              "      <td>6.267082</td>\n",
              "      <td>69.010644</td>\n",
              "      <td>3.740271</td>\n",
              "      <td>9.440594</td>\n",
              "      <td>405.898515</td>\n",
              "      <td>18.475990</td>\n",
              "      <td>354.783168</td>\n",
              "      <td>12.740817</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>9.240734</td>\n",
              "      <td>23.767711</td>\n",
              "      <td>6.811308</td>\n",
              "      <td>0.241238</td>\n",
              "      <td>0.117293</td>\n",
              "      <td>0.709788</td>\n",
              "      <td>27.940665</td>\n",
              "      <td>2.030215</td>\n",
              "      <td>8.698360</td>\n",
              "      <td>166.374543</td>\n",
              "      <td>2.200382</td>\n",
              "      <td>94.111148</td>\n",
              "      <td>7.254545</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.006320</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.460000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.385000</td>\n",
              "      <td>3.561000</td>\n",
              "      <td>2.900000</td>\n",
              "      <td>1.129600</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>188.000000</td>\n",
              "      <td>12.600000</td>\n",
              "      <td>0.320000</td>\n",
              "      <td>1.730000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>0.081437</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>5.130000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.453000</td>\n",
              "      <td>5.874750</td>\n",
              "      <td>45.475000</td>\n",
              "      <td>2.077100</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>279.000000</td>\n",
              "      <td>17.225000</td>\n",
              "      <td>374.672500</td>\n",
              "      <td>6.890000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>0.268880</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>9.690000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.538000</td>\n",
              "      <td>6.198500</td>\n",
              "      <td>78.500000</td>\n",
              "      <td>3.142300</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>330.000000</td>\n",
              "      <td>19.100000</td>\n",
              "      <td>391.250000</td>\n",
              "      <td>11.395000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>3.674808</td>\n",
              "      <td>12.500000</td>\n",
              "      <td>18.100000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.631000</td>\n",
              "      <td>6.609000</td>\n",
              "      <td>94.100000</td>\n",
              "      <td>5.118000</td>\n",
              "      <td>24.000000</td>\n",
              "      <td>666.000000</td>\n",
              "      <td>20.200000</td>\n",
              "      <td>396.157500</td>\n",
              "      <td>17.092500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>88.976200</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>27.740000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.871000</td>\n",
              "      <td>8.725000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>10.710300</td>\n",
              "      <td>24.000000</td>\n",
              "      <td>711.000000</td>\n",
              "      <td>22.000000</td>\n",
              "      <td>396.900000</td>\n",
              "      <td>37.970000</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-74ffb416-26e1-45f2-bbe4-3b5991c6be9e')\"\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-74ffb416-26e1-45f2-bbe4-3b5991c6be9e 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-74ffb416-26e1-45f2-bbe4-3b5991c6be9e');\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-6542dd6a-37f6-47f1-aeea-056fa1b1c785\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-6542dd6a-37f6-47f1-aeea-056fa1b1c785')\"\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-6542dd6a-37f6-47f1-aeea-056fa1b1c785 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "train_df[3] = train_df[3].astype(\"object\")\n",
        "test_df[3] = test_df[3].astype(\"object\")"
      ],
      "metadata": {
        "id": "1cbOEtvvTM22"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "fig, axs = plt.subplots(4, 4, figsize=(7,7))\n",
        "for col, ax in zip(train_df.columns, axs.flatten()):\n",
        "  ax.hist(train_df[col])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 599
        },
        "id": "73kMXRq7O0Z7",
        "outputId": "093bcc44-f4dd-4a60-90b2-9c2431838069"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x700 with 16 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "box_cols = train_df.apply(lambda x: all(x > 0) and x.dtype == float)\n",
        "yeo_cols = train_df.apply(lambda x: any(x <= 0) and x.dtype == float)\n",
        "obj_cols = train_df.apply(lambda x: x.dtype == object)"
      ],
      "metadata": {
        "id": "Sny-QxKwY0lb"
      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "preprocessor = ColumnTransformer([\n",
        "    (\"box\", PowerTransformer(\"box-cox\"), box_cols),\n",
        "    (\"yeo\", PowerTransformer(), yeo_cols),\n",
        "    (\"ohe\", OneHotEncoder(drop=\"if_binary\"), obj_cols),\n",
        "])\n",
        "preprocessor.fit(train_df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 116
        },
        "id": "cBLVhfQ1SGp2",
        "outputId": "fbcde57e-7d03-45c0-cb98-eddcf70e03b8"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ColumnTransformer(transformers=[('box', PowerTransformer(method='box-cox'),\n",
              "                                 0      True\n",
              "1     False\n",
              "2      True\n",
              "3     False\n",
              "4      True\n",
              "5      True\n",
              "6      True\n",
              "7      True\n",
              "8      True\n",
              "9      True\n",
              "10     True\n",
              "11     True\n",
              "12     True\n",
              "dtype: bool),\n",
              "                                ('yeo', PowerTransformer(),\n",
              "                                 0     False\n",
              "1      True\n",
              "2     False\n",
              "3     False\n",
              "4     False\n",
              "5     False\n",
              "6     False\n",
              "7     False\n",
              "8     False\n",
              "9     False\n",
              "10    False\n",
              "11    False\n",
              "12    False\n",
              "dtype: bool),\n",
              "                                ('ohe', OneHotEncoder(drop='if_binary'),\n",
              "                                 0     False\n",
              "1     False\n",
              "2     False\n",
              "3      True\n",
              "4     False\n",
              "5     False\n",
              "6     False\n",
              "7     False\n",
              "8     False\n",
              "9     False\n",
              "10    False\n",
              "11    False\n",
              "12    False\n",
              "dtype: bool)])"
            ],
            "text/html": [
              "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>ColumnTransformer(transformers=[(&#x27;box&#x27;, PowerTransformer(method=&#x27;box-cox&#x27;),\n",
              "                                 0      True\n",
              "1     False\n",
              "2      True\n",
              "3     False\n",
              "4      True\n",
              "5      True\n",
              "6      True\n",
              "7      True\n",
              "8      True\n",
              "9      True\n",
              "10     True\n",
              "11     True\n",
              "12     True\n",
              "dtype: bool),\n",
              "                                (&#x27;yeo&#x27;, PowerTransformer(),\n",
              "                                 0     False\n",
              "1      True\n",
              "2     False\n",
              "3     False\n",
              "4     False\n",
              "5     False\n",
              "6     False\n",
              "7     False\n",
              "8     False\n",
              "9     False\n",
              "10    False\n",
              "11    False\n",
              "12    False\n",
              "dtype: bool),\n",
              "                                (&#x27;ohe&#x27;, OneHotEncoder(drop=&#x27;if_binary&#x27;),\n",
              "                                 0     False\n",
              "1     False\n",
              "2     False\n",
              "3      True\n",
              "4     False\n",
              "5     False\n",
              "6     False\n",
              "7     False\n",
              "8     False\n",
              "9     False\n",
              "10    False\n",
              "11    False\n",
              "12    False\n",
              "dtype: bool)])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">ColumnTransformer</label><div class=\"sk-toggleable__content\"><pre>ColumnTransformer(transformers=[(&#x27;box&#x27;, PowerTransformer(method=&#x27;box-cox&#x27;),\n",
              "                                 0      True\n",
              "1     False\n",
              "2      True\n",
              "3     False\n",
              "4      True\n",
              "5      True\n",
              "6      True\n",
              "7      True\n",
              "8      True\n",
              "9      True\n",
              "10     True\n",
              "11     True\n",
              "12     True\n",
              "dtype: bool),\n",
              "                                (&#x27;yeo&#x27;, PowerTransformer(),\n",
              "                                 0     False\n",
              "1      True\n",
              "2     False\n",
              "3     False\n",
              "4     False\n",
              "5     False\n",
              "6     False\n",
              "7     False\n",
              "8     False\n",
              "9     False\n",
              "10    False\n",
              "11    False\n",
              "12    False\n",
              "dtype: bool),\n",
              "                                (&#x27;ohe&#x27;, OneHotEncoder(drop=&#x27;if_binary&#x27;),\n",
              "                                 0     False\n",
              "1     False\n",
              "2     False\n",
              "3      True\n",
              "4     False\n",
              "5     False\n",
              "6     False\n",
              "7     False\n",
              "8     False\n",
              "9     False\n",
              "10    False\n",
              "11    False\n",
              "12    False\n",
              "dtype: bool)])</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">box</label><div class=\"sk-toggleable__content\"><pre>0      True\n",
              "1     False\n",
              "2      True\n",
              "3     False\n",
              "4      True\n",
              "5      True\n",
              "6      True\n",
              "7      True\n",
              "8      True\n",
              "9      True\n",
              "10     True\n",
              "11     True\n",
              "12     True\n",
              "dtype: bool</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">PowerTransformer</label><div class=\"sk-toggleable__content\"><pre>PowerTransformer(method=&#x27;box-cox&#x27;)</pre></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">yeo</label><div class=\"sk-toggleable__content\"><pre>0     False\n",
              "1      True\n",
              "2     False\n",
              "3     False\n",
              "4     False\n",
              "5     False\n",
              "6     False\n",
              "7     False\n",
              "8     False\n",
              "9     False\n",
              "10    False\n",
              "11    False\n",
              "12    False\n",
              "dtype: bool</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">PowerTransformer</label><div class=\"sk-toggleable__content\"><pre>PowerTransformer()</pre></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">ohe</label><div class=\"sk-toggleable__content\"><pre>0     False\n",
              "1     False\n",
              "2     False\n",
              "3      True\n",
              "4     False\n",
              "5     False\n",
              "6     False\n",
              "7     False\n",
              "8     False\n",
              "9     False\n",
              "10    False\n",
              "11    False\n",
              "12    False\n",
              "dtype: bool</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">OneHotEncoder</label><div class=\"sk-toggleable__content\"><pre>OneHotEncoder(drop=&#x27;if_binary&#x27;)</pre></div></div></div></div></div></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pre_x_train = preprocessor.transform(train_df)\n",
        "pre_x_test = preprocessor.transform(test_df)"
      ],
      "metadata": {
        "id": "C1f5MAzBV6Fn"
      },
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "assert pre_x_train.shape == x_train.shape\n",
        "assert pre_x_test.shape == x_test.shape"
      ],
      "metadata": {
        "id": "2ovCnFMNWtTe"
      },
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pre_x_train_df = pd.DataFrame(pre_x_train)\n",
        "fig, axs = plt.subplots(4, 4, figsize=(7,7))\n",
        "for col, ax in zip(pre_x_train_df.columns, axs.flatten()):\n",
        "  ax.hist(pre_x_train_df[col])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 599
        },
        "id": "Ld3jOhqJWnyD",
        "outputId": "638c89ef-8d9f-4622-e64e-c0c9d2b1dba3"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x700 with 16 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "_ = plt.hist(y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "RdiH47UGOnwQ",
        "outputId": "42e8a1db-fd55-4eba-9959-f75daf2d30a2"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAigAAAGdCAYAAAA44ojeAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAeTUlEQVR4nO3dcWzU9f3H8deV0lKhd6Wd3LWjhW5jAiqooPXEbSqNiITBrFNMtzElsMzWWZpNaWJBNrTInLI6pOo21ARksgxUiDhWWImxVihjUYcVtird8IoL6x3UtVT6/f3hz29+J/zU6h3fd8vzkXwT7vv99tt3+aTpM9/e9XyO4zgCAAAwJMXrAQAAAD6KQAEAAOYQKAAAwBwCBQAAmEOgAAAAcwgUAABgDoECAADMIVAAAIA5qV4P8Fn09vbq0KFDyszMlM/n83ocAADwKTiOo6NHjyovL08pKR9/j6RfBsqhQ4eUn5/v9RgAAOAzaGtr08iRIz/2nH4ZKJmZmZI++AL9fr/H0wAAgE8jFospPz/f/Tn+cfploHz4ax2/30+gAADQz3yap2fwJFkAAGAOgQIAAMwhUAAAgDkECgAAMIdAAQAA5hAoAADAHAIFAACYQ6AAAABzCBQAAGAOgQIAAMzpc6Ds3LlTM2fOVF5ennw+nzZt2uQe6+np0Z133qnzzz9fQ4cOVV5enr73ve/p0KFDcdc4cuSISktL5ff7lZWVpXnz5unYsWOf+4sBAAADQ58DpbOzUxMnTtSqVatOOvbee+9pz549qq6u1p49e/SHP/xBLS0t+uY3vxl3XmlpqV5//XVt27ZNmzdv1s6dO7VgwYLP/lUAAIABxec4jvOZP9jn08aNGzV79uz/95xdu3bpkksu0dtvv62CggLt27dP48eP165duzR58mRJ0tatW3Xttdfqn//8p/Ly8j7x88ZiMQUCAUWjUd4sEACAfqIvP7+T/hyUaDQqn8+nrKwsSVJjY6OysrLcOJGk4uJipaSkqKmp6ZTX6O7uViwWi9sAAMDAlZrMi3d1denOO+/UTTfd5JZSJBLRiBEj4odITVV2drYikcgpr1NTU6OlS5cmc1TgUxm9aIvXI/TZW8tneD0CAPRZ0u6g9PT06IYbbpDjOFq9evXnulZVVZWi0ai7tbW1JWhKAABgUVLuoHwYJ2+//ba2b98e93umUCikw4cPx53//vvv68iRIwqFQqe8Xnp6utLT05MxKgAAMCjhd1A+jJP9+/frT3/6k3JycuKOh8NhdXR0qLm52d23fft29fb2qqioKNHjAACAfqjPd1COHTumAwcOuI9bW1u1d+9eZWdnKzc3V9dff7327NmjzZs368SJE+7zSrKzs5WWlqZx48bpmmuu0fz581VXV6eenh6Vl5drzpw5n+oVPAAAYODrc6Ds3r1bV155pfu4srJSkjR37lzdfffdevbZZyVJF1xwQdzH7dixQ1dccYUkae3atSovL9fUqVOVkpKikpIS1dbWfsYvAQAADDR9DpQrrrhCH/enUz7Nn1XJzs7WunXr+vqpAQDAGYL34gEAAOYQKAAAwBwCBQAAmEOgAAAAcwgUAABgDoECAADMIVAAAIA5BAoAADCHQAEAAOYQKAAAwBwCBQAAmEOgAAAAcwgUAABgDoECAADMIVAAAIA5BAoAADCHQAEAAOYQKAAAwBwCBQAAmEOgAAAAcwgUAABgDoECAADMIVAAAIA5BAoAADCHQAEAAOYQKAAAwBwCBQAAmEOgAAAAcwgUAABgDoECAADMIVAAAIA5BAoAADCHQAEAAOYQKAAAwBwCBQAAmEOgAAAAcwgUAABgDoECAADMIVAAAIA5BAoAADCHQAEAAOYQKAAAwBwCBQAAmEOgAAAAcwgUAABgDoECAADMIVAAAIA5BAoAADCnz4Gyc+dOzZw5U3l5efL5fNq0aVPcccdxtHjxYuXm5iojI0PFxcXav39/3DlHjhxRaWmp/H6/srKyNG/ePB07duxzfSEAAGDg6HOgdHZ2auLEiVq1atUpj69YsUK1tbWqq6tTU1OThg4dqmnTpqmrq8s9p7S0VK+//rq2bdumzZs3a+fOnVqwYMFn/yoAAMCAktrXD5g+fbqmT59+ymOO42jlypW66667NGvWLEnSk08+qWAwqE2bNmnOnDnat2+ftm7dql27dmny5MmSpIceekjXXnut7r//fuXl5X2OLwcAAAwECX0OSmtrqyKRiIqLi919gUBARUVFamxslCQ1NjYqKyvLjRNJKi4uVkpKipqamk553e7ubsVisbgNAAAMXAkNlEgkIkkKBoNx+4PBoHssEoloxIgRccdTU1OVnZ3tnvNRNTU1CgQC7pafn5/IsQEAgDH94lU8VVVVikaj7tbW1ub1SAAAIIkSGiihUEiS1N7eHre/vb3dPRYKhXT48OG44++//76OHDninvNR6enp8vv9cRsAABi4EhoohYWFCoVCqq+vd/fFYjE1NTUpHA5LksLhsDo6OtTc3Oyes337dvX29qqoqCiR4wAAgH6qz6/iOXbsmA4cOOA+bm1t1d69e5Wdna2CggJVVFRo2bJlGjNmjAoLC1VdXa28vDzNnj1bkjRu3Dhdc801mj9/vurq6tTT06Py8nLNmTOHV/AAAABJnyFQdu/erSuvvNJ9XFlZKUmaO3euHn/8cd1xxx3q7OzUggUL1NHRocsvv1xbt27VkCFD3I9Zu3atysvLNXXqVKWkpKikpES1tbUJ+HIAAMBA4HMcx/F6iL6KxWIKBAKKRqM8HwWn1ehFW7weoc/eWj7D6xEAQFLffn73i1fxAACAMwuBAgAAzCFQAACAOQQKAAAwh0ABAADmECgAAMAcAgUAAJhDoAAAAHMIFAAAYA6BAgAAzCFQAACAOQQKAAAwh0ABAADmECgAAMAcAgUAAJhDoAAAAHMIFAAAYA6BAgAAzCFQAACAOQQKAAAwh0ABAADmECgAAMAcAgUAAJhDoAAAAHMIFAAAYA6BAgAAzCFQAACAOQQKAAAwh0ABAADmECgAAMAcAgUAAJhDoAAAAHMIFAAAYA6BAgAAzCFQAACAOQQKAAAwh0ABAADmECgAAMAcAgUAAJhDoAAAAHMIFAAAYA6BAgAAzCFQAACAOQQKAAAwh0ABAADmECgAAMAcAgUAAJiT8EA5ceKEqqurVVhYqIyMDH35y1/Wz372MzmO457jOI4WL16s3NxcZWRkqLi4WPv370/0KAAAoJ9KeKDcd999Wr16tX71q19p3759uu+++7RixQo99NBD7jkrVqxQbW2t6urq1NTUpKFDh2ratGnq6upK9DgAAKAfSk30BV966SXNmjVLM2bMkCSNHj1aTz31lF555RVJH9w9Wblype666y7NmjVLkvTkk08qGAxq06ZNmjNnTqJHAgAA/UzC76Bcdtllqq+v15tvvilJ+utf/6oXX3xR06dPlyS1trYqEomouLjY/ZhAIKCioiI1NjYmehwAANAPJfwOyqJFixSLxTR27FgNGjRIJ06c0D333KPS0lJJUiQSkSQFg8G4jwsGg+6xj+ru7lZ3d7f7OBaLJXpsAABgSMLvoDz99NNau3at1q1bpz179uiJJ57Q/fffryeeeOIzX7OmpkaBQMDd8vPzEzgxAACwJuGB8pOf/ESLFi3SnDlzdP755+u73/2uFi5cqJqaGklSKBSSJLW3t8d9XHt7u3vso6qqqhSNRt2tra0t0WMDAABDEh4o7733nlJS4i87aNAg9fb2SpIKCwsVCoVUX1/vHo/FYmpqalI4HD7lNdPT0+X3++M2AAAwcCX8OSgzZ87UPffco4KCAp177rn6y1/+ogceeEC33HKLJMnn86miokLLli3TmDFjVFhYqOrqauXl5Wn27NmJHgcAAPRDCQ+Uhx56SNXV1br11lt1+PBh5eXl6Qc/+IEWL17snnPHHXeos7NTCxYsUEdHhy6//HJt3bpVQ4YMSfQ4AACgH/I5//dPvPYTsVhMgUBA0WiUX/fgtBq9aIvXI/TZW8tneD0CAEjq289v3osHAACYQ6AAAABzCBQAAGAOgQIAAMwhUAAAgDkECgAAMIdAAQAA5hAoAADAHAIFAACYQ6AAAABzCBQAAGAOgQIAAMwhUAAAgDkECgAAMIdAAQAA5hAoAADAHAIFAACYk+r1ADhzjV60xesRAABGcQcFAACYQ6AAAABzCBQAAGAOgQIAAMwhUAAAgDkECgAAMIdAAQAA5hAoAADAHAIFAACYQ6AAAABzCBQAAGAOgQIAAMwhUAAAgDkECgAAMIdAAQAA5hAoAADAHAIFAACYQ6AAAABzCBQAAGAOgQIAAMwhUAAAgDkECgAAMIdAAQAA5qR6PQCA5Bq9aIvXI/TZW8tneD0CAI9xBwUAAJhDoAAAAHMIFAAAYA6BAgAAzCFQAACAOQQKAAAwJymB8q9//Uvf+c53lJOTo4yMDJ1//vnavXu3e9xxHC1evFi5ubnKyMhQcXGx9u/fn4xRAABAP5TwQPnPf/6jKVOmaPDgwXr++ef1t7/9Tb/4xS80fPhw95wVK1aotrZWdXV1ampq0tChQzVt2jR1dXUlehwAANAPJfwPtd13333Kz8/XmjVr3H2FhYXuvx3H0cqVK3XXXXdp1qxZkqQnn3xSwWBQmzZt0pw5cxI9EgAA6GcSfgfl2Wef1eTJk/Xtb39bI0aM0IUXXqjHHnvMPd7a2qpIJKLi4mJ3XyAQUFFRkRobG095ze7ubsVisbgNAAAMXAkPlH/84x9avXq1xowZoxdeeEE//OEP9aMf/UhPPPGEJCkSiUiSgsFg3McFg0H32EfV1NQoEAi4W35+fqLHBgAAhiQ8UHp7e3XRRRfp3nvv1YUXXqgFCxZo/vz5qqur+8zXrKqqUjQadbe2trYETgwAAKxJeKDk5uZq/PjxcfvGjRungwcPSpJCoZAkqb29Pe6c9vZ299hHpaeny+/3x20AAGDgSnigTJkyRS0tLXH73nzzTY0aNUrSB0+YDYVCqq+vd4/HYjE1NTUpHA4nehwAANAPJfxVPAsXLtRll12me++9VzfccINeeeUVPfroo3r00UclST6fTxUVFVq2bJnGjBmjwsJCVVdXKy8vT7Nnz070OAAAoB9KeKBcfPHF2rhxo6qqqvTTn/5UhYWFWrlypUpLS91z7rjjDnV2dmrBggXq6OjQ5Zdfrq1bt2rIkCGJHgcAAPRDPsdxHK+H6KtYLKZAIKBoNMrzUfqx0Yu2eD0CjHpr+QyvRwCQBH35+c178QAAAHMIFAAAYA6BAgAAzCFQAACAOQQKAAAwh0ABAADmECgAAMAcAgUAAJhDoAAAAHMIFAAAYA6BAgAAzCFQAACAOQQKAAAwh0ABAADmECgAAMAcAgUAAJhDoAAAAHMIFAAAYA6BAgAAzCFQAACAOQQKAAAwh0ABAADmECgAAMAcAgUAAJhDoAAAAHMIFAAAYA6BAgAAzCFQAACAOaleD4DEGL1oi9cjAACQMNxBAQAA5hAoAADAHAIFAACYQ6AAAABzCBQAAGAOgQIAAMwhUAAAgDkECgAAMIdAAQAA5hAoAADAHAIFAACYQ6AAAABzCBQAAGAOgQIAAMwhUAAAgDkECgAAMIdAAQAA5hAoAADAHAIFAACYk/RAWb58uXw+nyoqKtx9XV1dKisrU05OjoYNG6aSkhK1t7cnexQAANBPJDVQdu3apUceeUQTJkyI279w4UI999xz2rBhgxoaGnTo0CFdd911yRwFAAD0I0kLlGPHjqm0tFSPPfaYhg8f7u6PRqP6zW9+owceeEBXXXWVJk2apDVr1uill17Syy+/nKxxAABAP5K0QCkrK9OMGTNUXFwct7+5uVk9PT1x+8eOHauCggI1Njae8lrd3d2KxWJxGwAAGLhSk3HR9evXa8+ePdq1a9dJxyKRiNLS0pSVlRW3PxgMKhKJnPJ6NTU1Wrp0aTJGBQAABiX8DkpbW5tuv/12rV27VkOGDEnINauqqhSNRt2tra0tIdcFAAA2JTxQmpubdfjwYV100UVKTU1VamqqGhoaVFtbq9TUVAWDQR0/flwdHR1xH9fe3q5QKHTKa6anp8vv98dtAABg4Er4r3imTp2qV199NW7fzTffrLFjx+rOO+9Ufn6+Bg8erPr6epWUlEiSWlpadPDgQYXD4USPAwAA+qGEB0pmZqbOO++8uH1Dhw5VTk6Ou3/evHmqrKxUdna2/H6/brvtNoXDYV166aWJHgcAAPRDSXmS7Cd58MEHlZKSopKSEnV3d2vatGl6+OGHvRgFAAAY5HMcx/F6iL6KxWIKBAKKRqM8H+V/jV60xesRgIR5a/kMr0cAkAR9+fnNe/EAAABzCBQAAGAOgQIAAMwhUAAAgDkECgAAMIdAAQAA5hAoAADAHAIFAACYQ6AAAABzCBQAAGAOgQIAAMwhUAAAgDkECgAAMIdAAQAA5hAoAADAHAIFAACYQ6AAAABzCBQAAGAOgQIAAMxJ9XoAAPio0Yu2eD1Cn721fIbXIwADCndQAACAOQQKAAAwh0ABAADmECgAAMAcAgUAAJhDoAAAAHMIFAAAYA6BAgAAzCFQAACAOQQKAAAwh0ABAADmECgAAMAcAgUAAJhDoAAAAHMIFAAAYA6BAgAAzCFQAACAOQQKAAAwh0ABAADmECgAAMAcAgUAAJhDoAAAAHMIFAAAYA6BAgAAzCFQAACAOQQKAAAwh0ABAADmJDxQampqdPHFFyszM1MjRozQ7Nmz1dLSEndOV1eXysrKlJOTo2HDhqmkpETt7e2JHgUAAPRTCQ+UhoYGlZWV6eWXX9a2bdvU09Ojq6++Wp2dne45Cxcu1HPPPacNGzaooaFBhw4d0nXXXZfoUQAAQD/lcxzHSeYnePfddzVixAg1NDTo61//uqLRqM4++2ytW7dO119/vSTpjTfe0Lhx49TY2KhLL730E68Zi8UUCAQUjUbl9/uTOX6/MXrRFq9HANDPvLV8htcj4AzTl5/fSX8OSjQalSRlZ2dLkpqbm9XT06Pi4mL3nLFjx6qgoECNjY3JHgcAAPQDqcm8eG9vryoqKjRlyhSdd955kqRIJKK0tDRlZWXFnRsMBhWJRE55ne7ubnV3d7uPY7FY0mYGAADeS+odlLKyMr322mtav37957pOTU2NAoGAu+Xn5ydoQgAAYFHSAqW8vFybN2/Wjh07NHLkSHd/KBTS8ePH1dHREXd+e3u7QqHQKa9VVVWlaDTqbm1tbckaGwAAGJDwQHEcR+Xl5dq4caO2b9+uwsLCuOOTJk3S4MGDVV9f7+5raWnRwYMHFQ6HT3nN9PR0+f3+uA0AAAxcCX8OSllZmdatW6dnnnlGmZmZ7vNKAoGAMjIyFAgENG/ePFVWVio7O1t+v1+33XabwuHwp3oFDwAAGPgSHiirV6+WJF1xxRVx+9esWaPvf//7kqQHH3xQKSkpKikpUXd3t6ZNm6aHH3440aMAAIB+KuGB8mn+rMqQIUO0atUqrVq1KtGfHgAADAC8Fw8AADCHQAEAAOYk9Q+1AQBwpuuvb0Xi9VshcAcFAACYQ6AAAABzCBQAAGAOgQIAAMwhUAAAgDm8iucU+uszrgEAGCi4gwIAAMwhUAAAgDkECgAAMIdAAQAA5hAoAADAHAIFAACYQ6AAAABzCBQAAGAOgQIAAMwhUAAAgDkECgAAMIdAAQAA5hAoAADAHAIFAACYQ6AAAABzCBQAAGAOgQIAAMwhUAAAgDkECgAAMIdAAQAA5qR6PQAAwBujF23xegTg/8UdFAAAYA6BAgAAzCFQAACAOQQKAAAwh0ABAADmECgAAMAcAgUAAJhDoAAAAHMIFAAAYA6BAgAAzCFQAACAOQQKAAAwh0ABAADmECgAAMAcAgUAAJhDoAAAAHMIFAAAYA6BAgAAzPE0UFatWqXRo0dryJAhKioq0iuvvOLlOAAAwAjPAuV3v/udKisrtWTJEu3Zs0cTJ07UtGnTdPjwYa9GAgAARngWKA888IDmz5+vm2++WePHj1ddXZ3OOuss/fa3v/VqJAAAYESqF5/0+PHjam5uVlVVlbsvJSVFxcXFamxsPOn87u5udXd3u4+j0agkKRaLJWW+3u73knJdAAD6i2T8jP3wmo7jfOK5ngTKv//9b504cULBYDBufzAY1BtvvHHS+TU1NVq6dOlJ+/Pz85M2IwAAZ7LAyuRd++jRowoEAh97jieB0ldVVVWqrKx0H/f29urIkSPKycmRz+fzcDK7YrGY8vPz1dbWJr/f7/U4ZzzWwxbWwxbWw55krYnjODp69Kjy8vI+8VxPAuULX/iCBg0apPb29rj97e3tCoVCJ52fnp6u9PT0uH1ZWVnJHHHA8Pv9fMMbwnrYwnrYwnrYk4w1+aQ7Jx/y5EmyaWlpmjRpkurr6919vb29qq+vVzgc9mIkAABgiGe/4qmsrNTcuXM1efJkXXLJJVq5cqU6Ozt18803ezUSAAAwwrNAufHGG/Xuu+9q8eLFikQiuuCCC7R169aTnjiLzyY9PV1Lliw56Vdj8AbrYQvrYQvrYY+FNfE5n+a1PgAAAKcR78UDAADMIVAAAIA5BAoAADCHQAEAAOYQKP3Yzp07NXPmTOXl5cnn82nTpk1xxx3H0eLFi5Wbm6uMjAwVFxdr//793gx7BqipqdHFF1+szMxMjRgxQrNnz1ZLS0vcOV1dXSorK1NOTo6GDRumkpKSk/5gIRJj9erVmjBhgvuHpsLhsJ5//nn3OGvhreXLl8vn86miosLdx5qcXnfffbd8Pl/cNnbsWPe41+tBoPRjnZ2dmjhxolatWnXK4ytWrFBtba3q6urU1NSkoUOHatq0aerq6jrNk54ZGhoaVFZWppdfflnbtm1TT0+Prr76anV2drrnLFy4UM8995w2bNighoYGHTp0SNddd52HUw9cI0eO1PLly9Xc3Kzdu3frqquu0qxZs/T6669LYi28tGvXLj3yyCOaMGFC3H7W5PQ799xz9c4777jbiy++6B7zfD0cDAiSnI0bN7qPe3t7nVAo5Pz85z9393V0dDjp6enOU0895cGEZ57Dhw87kpyGhgbHcT74/x88eLCzYcMG95x9+/Y5kpzGxkavxjyjDB8+3Pn1r3/NWnjo6NGjzpgxY5xt27Y53/jGN5zbb7/dcRy+P7ywZMkSZ+LEiac8ZmE9uIMyQLW2tioSiai4uNjdFwgEVFRUpMbGRg8nO3NEo1FJUnZ2tiSpublZPT09cWsyduxYFRQUsCZJduLECa1fv16dnZ0Kh8OshYfKyso0Y8aMuP97ie8Pr+zfv195eXn60pe+pNLSUh08eFCSjfXoF+9mjL6LRCKSdNJf5g0Gg+4xJE9vb68qKio0ZcoUnXfeeZI+WJO0tLST3uiSNUmeV199VeFwWF1dXRo2bJg2btyo8ePHa+/evayFB9avX689e/Zo165dJx3j++P0Kyoq0uOPP65zzjlH77zzjpYuXaqvfe1reu2110ysB4ECJEFZWZlee+21uN/n4vQ755xztHfvXkWjUf3+97/X3Llz1dDQ4PVYZ6S2tjbdfvvt2rZtm4YMGeL1OJA0ffp0998TJkxQUVGRRo0apaeffloZGRkeTvYBfsUzQIVCIUk66RnX7e3t7jEkR3l5uTZv3qwdO3Zo5MiR7v5QKKTjx4+ro6Mj7nzWJHnS0tL0la98RZMmTVJNTY0mTpyoX/7yl6yFB5qbm3X48GFddNFFSk1NVWpqqhoaGlRbW6vU1FQFg0HWxGNZWVn66le/qgMHDpj4HiFQBqjCwkKFQiHV19e7+2KxmJqamhQOhz2cbOByHEfl5eXauHGjtm/frsLCwrjjkyZN0uDBg+PWpKWlRQcPHmRNTpPe3l51d3ezFh6YOnWqXn31Ve3du9fdJk+erNLSUvffrIm3jh07pr///e/Kzc018T3Cr3j6sWPHjunAgQPu49bWVu3du1fZ2dkqKChQRUWFli1bpjFjxqiwsFDV1dXKy8vT7NmzvRt6ACsrK9O6dev0zDPPKDMz0/09bSAQUEZGhgKBgObNm6fKykplZ2fL7/frtttuUzgc1qWXXurx9ANPVVWVpk+froKCAh09elTr1q3Tn//8Z73wwgushQcyMzPd52N9aOjQocrJyXH3syan149//GPNnDlTo0aN0qFDh7RkyRINGjRIN910k43vkdPyWiEkxY4dOxxJJ21z5851HOeDlxpXV1c7wWDQSU9Pd6ZOneq0tLR4O/QAdqq1kOSsWbPGPee///2vc+uttzrDhw93zjrrLOdb3/qW884773g39AB2yy23OKNGjXLS0tKcs88+25k6darzxz/+0T3OWnjv/77M2HFYk9PtxhtvdHJzc520tDTni1/8onPjjTc6Bw4ccI97vR4+x3Gc05NCAAAAnw7PQQEAAOYQKAAAwBwCBQAAmEOgAAAAcwgUAABgDoECAADMIVAAAIA5BAoAADCHQAEAAOYQKAAAwBwCBQAAmEOgAAAAc/4HmlCC8V0bqx8AAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pre_y_train = np.log(y_train)\n",
        "pre_y_test = np.log(y_test)"
      ],
      "metadata": {
        "id": "Okp19-f5Q7PU"
      },
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "assert y_train.shape == pre_y_train.shape\n",
        "assert y_test.shape == pre_y_test.shape"
      ],
      "metadata": {
        "id": "_G4Wfd8Tb_n1"
      },
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "_ = plt.hist(pre_y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "3VUIcZOtQmJW",
        "outputId": "86dab122-9307-4c83-ef20-eeaf931ddc82"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAi0AAAGdCAYAAADey0OaAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAe4ElEQVR4nO3df2zUhf3H8deV0pYhvVq23rWhSOMYP5QfCloL5itKJyphNLK5ms4xJWBc6ygk0zYRHPNHgTBgKFL8hbrAmC6DKcy6WrSNWmppYUPGEB1iN7yyBbmDEs5KP98/Fi87KEjhrtf39flIPon3uc99eJ8fPumTTz/tuRzHcQQAANDDJcR6AAAAgPNBtAAAABOIFgAAYALRAgAATCBaAACACUQLAAAwgWgBAAAmEC0AAMCExFgPcCE6Ojp06NAhDRgwQC6XK9bjAACA8+A4jo4dO6asrCwlJHT9uonJaDl06JCys7NjPQYAALgALS0tGjRoUJdfZzJaBgwYIOm/bzo1NTXG0wAAgPMRCASUnZ0d+jreVSaj5atvCaWmphItAAAYc6G3dnAjLgAAMIFoAQAAJhAtAADABKIFAACYQLQAAAATiBYAAGAC0QIAAEwgWgAAgAlECwAAMIFoAQAAJhAtAADABKIFAACYQLQAAAATiBYAAGBCYqwHAIB4MKRsa6xH6LJPFk+N9QhAl3ClBQAAmEC0AAAAE4gWAABgAtECAABMIFoAAIAJRAsAADCBaAEAACYQLQAAwASiBQAAmEC0AAAAE4gWAABgAtECAABMIFoAAIAJRAsAADCBaAEAACYQLQAAwASiBQAAmEC0AAAAE4gWAABgAtECAABMIFoAAIAJRAsAADCBaAEAACYQLQAAwASiBQAAmEC0AAAAE4gWAABgAtECAABMIFoAAIAJRAsAADChy9FSV1enadOmKSsrSy6XS5s3bw49197ergcffFCjRo1S//79lZWVpR//+Mc6dOhQ2D6OHDmioqIipaamKi0tTbNmzdLx48cv+s0AAID41eVoaWtr05gxY7R69eoznjtx4oSam5u1YMECNTc36w9/+IP27dun733ve2HbFRUVac+ePaqurtaWLVtUV1enOXPmXPi7AAAAcc/lOI5zwS92ubRp0yYVFBScdZvGxkZde+21OnjwoAYPHqy9e/dq5MiRamxs1Pjx4yVJVVVVuu222/TPf/5TWVlZX/vnBgIBud1u+f1+paamXuj4ABAxQ8q2xnqELvtk8dRYj4Be5mK/fkf9nha/3y+Xy6W0tDRJUn19vdLS0kLBIkn5+flKSEhQQ0NDp/sIBoMKBAJhCwAA6F2iGi0nT57Ugw8+qDvvvDNUVD6fTxkZGWHbJSYmKj09XT6fr9P9VFRUyO12h5bs7Oxojg0AAHqgqEVLe3u77rjjDjmOozVr1lzUvsrLy+X3+0NLS0tLhKYEAABWJEZjp18Fy8GDB7Vt27aw71t5vV4dPnw4bPsvv/xSR44ckdfr7XR/ycnJSk5OjsaoAADAiIhfafkqWPbv368333xTAwcODHs+Ly9PR48eVVNTU2jdtm3b1NHRodzc3EiPAwAA4kSXr7QcP35cH330UejxgQMHtGvXLqWnpyszM1Pf//731dzcrC1btujUqVOh+1TS09OVlJSkESNG6JZbbtHs2bNVWVmp9vZ2lZSUqLCw8Lx+cggAAPROXY6WHTt26MYbbww9nj9/viRp5syZ+sUvfqFXX31VkjR27Niw17311luaNGmSJGn9+vUqKSnR5MmTlZCQoBkzZmjVqlUX+BYAAEBv0OVomTRpks71q13O59e+pKena8OGDV39owEAQC/GZw8BAAATiBYAAGAC0QIAAEwgWgAAgAlECwAAMIFoAQAAJhAtAADABKIFAACYQLQAAAATiBYAAGAC0QIAAEwgWgAAgAlECwAAMIFoAQAAJhAtAADABKIFAACYQLQAAAATiBYAAGAC0QIAAEwgWgAAgAlECwAAMIFoAQAAJhAtAADABKIFAACYQLQAAAATiBYAAGAC0QIAAEwgWgAAgAlECwAAMIFoAQAAJhAtAADABKIFAACYQLQAAAATiBYAAGAC0QIAAEwgWgAAgAlECwAAMIFoAQAAJhAtAADABKIFAACYQLQAAAATuhwtdXV1mjZtmrKysuRyubR58+aw5x3H0cKFC5WZmal+/fopPz9f+/fvD9vmyJEjKioqUmpqqtLS0jRr1iwdP378ot4IAACIb12Olra2No0ZM0arV6/u9PmlS5dq1apVqqysVENDg/r3768pU6bo5MmToW2Kioq0Z88eVVdXa8uWLaqrq9OcOXMu/F0AAIC4l9jVF9x666269dZbO33OcRytXLlSDz30kKZPny5Jeumll+TxeLR582YVFhZq7969qqqqUmNjo8aPHy9JeuKJJ3Tbbbdp2bJlysrKuoi3AwAA4lVE72k5cOCAfD6f8vPzQ+vcbrdyc3NVX18vSaqvr1daWlooWCQpPz9fCQkJamhoiOQ4AAAgjnT5Ssu5+Hw+SZLH4wlb7/F4Qs/5fD5lZGSED5GYqPT09NA2pwsGgwoGg6HHgUAgkmMDAAADTPz0UEVFhdxud2jJzs6O9UgAAKCbRTRavF6vJKm1tTVsfWtra+g5r9erw4cPhz3/5Zdf6siRI6FtTldeXi6/3x9aWlpaIjk2AAAwIKLRkpOTI6/Xq5qamtC6QCCghoYG5eXlSZLy8vJ09OhRNTU1hbbZtm2bOjo6lJub2+l+k5OTlZqaGrYAAIDepcv3tBw/flwfffRR6PGBAwe0a9cupaena/DgwSotLdWjjz6qoUOHKicnRwsWLFBWVpYKCgokSSNGjNAtt9yi2bNnq7KyUu3t7SopKVFhYSE/OQQAAM6qy9GyY8cO3XjjjaHH8+fPlyTNnDlTL7zwgh544AG1tbVpzpw5Onr0qK6//npVVVUpJSUl9Jr169erpKREkydPVkJCgmbMmKFVq1ZF4O0AAIB45XIcx4n1EF0VCATkdrvl9/v5VhGAHmFI2dZYj9BlnyyeGusR0Mtc7NdvEz89BAAAQLQAAAATiBYAAGAC0QIAAEwgWgAAgAlECwAAMIFoAQAAJhAtAADABKIFAACYQLQAAAATiBYAAGAC0QIAAEwgWgAAgAlECwAAMIFoAQAAJhAtAADABKIFAACYQLQAAAATiBYAAGAC0QIAAEwgWgAAgAlECwAAMIFoAQAAJhAtAADABKIFAACYQLQAAAATiBYAAGAC0QIAAEwgWgAAgAlECwAAMIFoAQAAJiTGegAAON2Qsq2xHgFAD8SVFgAAYALRAgAATCBaAACACUQLAAAwgWgBAAAmEC0AAMAEogUAAJhAtAAAABOIFgAAYALRAgAATIh4tJw6dUoLFixQTk6O+vXrp8svv1yPPPKIHMcJbeM4jhYuXKjMzEz169dP+fn52r9/f6RHAQAAcSTi0bJkyRKtWbNGTz75pPbu3aslS5Zo6dKleuKJJ0LbLF26VKtWrVJlZaUaGhrUv39/TZkyRSdPnoz0OAAAIE5E/AMT33vvPU2fPl1Tp06VJA0ZMkS//e1v9f7770v671WWlStX6qGHHtL06dMlSS+99JI8Ho82b96swsLCSI8EAADiQMSvtEyYMEE1NTX68MMPJUl/+ctf9M477+jWW2+VJB04cEA+n0/5+fmh17jdbuXm5qq+vj7S4wAAgDgR8SstZWVlCgQCGj58uPr06aNTp07pscceU1FRkSTJ5/NJkjweT9jrPB5P6LnTBYNBBYPB0ONAIBDpsQEAQA8X8SstL7/8stavX68NGzaoublZL774opYtW6YXX3zxgvdZUVEht9sdWrKzsyM4MQAAsCDi0fLzn/9cZWVlKiws1KhRo3TXXXdp3rx5qqiokCR5vV5JUmtra9jrWltbQ8+drry8XH6/P7S0tLREemwAANDDRTxaTpw4oYSE8N326dNHHR0dkqScnBx5vV7V1NSEng8EAmpoaFBeXl6n+0xOTlZqamrYAgAAepeI39Mybdo0PfbYYxo8eLCuuOIK7dy5U8uXL9c999wjSXK5XCotLdWjjz6qoUOHKicnRwsWLFBWVpYKCgoiPQ4AAIgTEY+WJ554QgsWLNBPf/pTHT58WFlZWbr33nu1cOHC0DYPPPCA2traNGfOHB09elTXX3+9qqqqlJKSEulxAABAnHA5//urao0IBAJyu93y+/18qwiIQ0PKtsZ6hF7hk8VTYz0CepmL/frNZw8BAAATiBYAAGAC0QIAAEwgWgAAgAlECwAAMIFoAQAAJhAtAADABKIFAACYQLQAAAATiBYAAGAC0QIAAEwgWgAAgAlECwAAMIFoAQAAJhAtAADABKIFAACYQLQAAAATiBYAAGAC0QIAAEwgWgAAgAlECwAAMIFoAQAAJhAtAADABKIFAACYQLQAAAATiBYAAGAC0QIAAEwgWgAAgAlECwAAMIFoAQAAJhAtAADABKIFAACYQLQAAAATiBYAAGAC0QIAAEwgWgAAgAlECwAAMIFoAQAAJhAtAADABKIFAACYQLQAAAATiBYAAGBCVKLlX//6l370ox9p4MCB6tevn0aNGqUdO3aEnnccRwsXLlRmZqb69eun/Px87d+/PxqjAACAOBHxaPn88881ceJE9e3bV6+//rr+9re/6Ve/+pUuvfTS0DZLly7VqlWrVFlZqYaGBvXv319TpkzRyZMnIz0OAACIE4mR3uGSJUuUnZ2tdevWhdbl5OSE/ttxHK1cuVIPPfSQpk+fLkl66aWX5PF4tHnzZhUWFkZ6JAAAEAcifqXl1Vdf1fjx4/WDH/xAGRkZuuqqq/TMM8+Enj9w4IB8Pp/y8/ND69xut3Jzc1VfX9/pPoPBoAKBQNgCAAB6l4hHyz/+8Q+tWbNGQ4cO1RtvvKH77rtPP/vZz/Tiiy9Kknw+nyTJ4/GEvc7j8YSeO11FRYXcbndoyc7OjvTYAACgh4t4tHR0dOjqq6/W448/rquuukpz5szR7NmzVVlZecH7LC8vl9/vDy0tLS0RnBgAAFgQ8WjJzMzUyJEjw9aNGDFCn376qSTJ6/VKklpbW8O2aW1tDT13uuTkZKWmpoYtAACgd4l4tEycOFH79u0LW/fhhx/qsssuk/Tfm3K9Xq9qampCzwcCATU0NCgvLy/S4wAAgDgR8Z8emjdvniZMmKDHH39cd9xxh95//309/fTTevrppyVJLpdLpaWlevTRRzV06FDl5ORowYIFysrKUkFBQaTHAQAAcSLi0XLNNddo06ZNKi8v1y9/+Uvl5ORo5cqVKioqCm3zwAMPqK2tTXPmzNHRo0d1/fXXq6qqSikpKZEeBwAAxAmX4zhOrIfoqkAgILfbLb/fz/0tQBwaUrY11iP0Cp8snhrrEdDLXOzXbz57CAAAmEC0AAAAE4gWAABgAtECAABMIFoAAIAJRAsAADCBaAEAACZE/JfLAehZ+J0nAOIFV1oAAIAJRAsAADCBaAEAACYQLQAAwASiBQAAmEC0AAAAE4gWAABgAtECAABMIFoAAIAJRAsAADCBaAEAACYQLQAAwASiBQAAmEC0AAAAE4gWAABgAtECAABMIFoAAIAJRAsAADCBaAEAACYQLQAAwASiBQAAmEC0AAAAE4gWAABgAtECAABMIFoAAIAJRAsAADCBaAEAACYQLQAAwASiBQAAmEC0AAAAE4gWAABgAtECAABMIFoAAIAJRAsAADAh6tGyePFiuVwulZaWhtadPHlSxcXFGjhwoC655BLNmDFDra2t0R4FAAAYFtVoaWxs1Nq1azV69Oiw9fPmzdNrr72mV155RbW1tTp06JBuv/32aI4CAACMi1q0HD9+XEVFRXrmmWd06aWXhtb7/X4999xzWr58uW666SaNGzdO69at03vvvaft27dHaxwAAGBc1KKluLhYU6dOVX5+ftj6pqYmtbe3h60fPny4Bg8erPr6+k73FQwGFQgEwhYAANC7JEZjpxs3blRzc7MaGxvPeM7n8ykpKUlpaWlh6z0ej3w+X6f7q6io0KJFi6IxKgAAMCLiV1paWlo0d+5crV+/XikpKRHZZ3l5ufx+f2hpaWmJyH4BAIAdEY+WpqYmHT58WFdffbUSExOVmJio2tparVq1SomJifJ4PPriiy909OjRsNe1trbK6/V2us/k5GSlpqaGLQAAoHeJ+LeHJk+erN27d4etu/vuuzV8+HA9+OCDys7OVt++fVVTU6MZM2ZIkvbt26dPP/1UeXl5kR4HAADEiYhHy4ABA3TllVeGrevfv78GDhwYWj9r1izNnz9f6enpSk1N1f3336+8vDxdd911kR4HAADEiajciPt1VqxYoYSEBM2YMUPBYFBTpkzRU089FYtRAACAES7HcZxYD9FVgUBAbrdbfr+f+1uArzGkbGusR0AP9cniqbEeAb3MxX795rOHAACACTH59hAAIPYsXoXj6lDvxpUWAABgAtECAABMIFoAAIAJRAsAADCBaAEAACYQLQAAwASiBQAAmEC0AAAAE4gWAABgAtECAABMIFoAAIAJRAsAADCBaAEAACYQLQAAwASiBQAAmJAY6wEAADhfQ8q2xnqELvtk8dRYjxA3uNICAABMIFoAAIAJRAsAADCBaAEAACYQLQAAwASiBQAAmEC0AAAAE4gWAABgAtECAABMIFoAAIAJRAsAADCBaAEAACbwgYkAAESRxQ95lHrmBz1ypQUAAJhAtAAAABOIFgAAYALRAgAATCBaAACACUQLAAAwgWgBAAAmEC0AAMAEogUAAJhAtAAAABOIFgAAYELEo6WiokLXXHONBgwYoIyMDBUUFGjfvn1h25w8eVLFxcUaOHCgLrnkEs2YMUOtra2RHgUAAMSRiEdLbW2tiouLtX37dlVXV6u9vV0333yz2traQtvMmzdPr732ml555RXV1tbq0KFDuv322yM9CgAAiCMR/5TnqqqqsMcvvPCCMjIy1NTUpP/7v/+T3+/Xc889pw0bNuimm26SJK1bt04jRozQ9u3bdd1110V6JAAAEAeifk+L3++XJKWnp0uSmpqa1N7ervz8/NA2w4cP1+DBg1VfX9/pPoLBoAKBQNgCAAB6l4hfaflfHR0dKi0t1cSJE3XllVdKknw+n5KSkpSWlha2rcfjkc/n63Q/FRUVWrRoUTRHBc7LkLKtsR4BAHqtqF5pKS4u1gcffKCNGzde1H7Ky8vl9/tDS0tLS4QmBAAAVkTtSktJSYm2bNmiuro6DRo0KLTe6/Xqiy++0NGjR8OutrS2tsrr9Xa6r+TkZCUnJ0drVAAAYEDEr7Q4jqOSkhJt2rRJ27ZtU05OTtjz48aNU9++fVVTUxNat2/fPn366afKy8uL9DgAACBORPxKS3FxsTZs2KA//vGPGjBgQOg+FbfbrX79+sntdmvWrFmaP3++0tPTlZqaqvvvv195eXn85BAAADiriEfLmjVrJEmTJk0KW79u3Tr95Cc/kSStWLFCCQkJmjFjhoLBoKZMmaKnnnoq0qMAAIA4EvFocRzna7dJSUnR6tWrtXr16kj/8QAAIE7x2UMAAMAEogUAAJhAtAAAABOIFgAAYALRAgAATCBaAACACUQLAAAwgWgBAAAmEC0AAMAEogUAAJhAtAAAABOIFgAAYALRAgAATCBaAACACUQLAAAwgWgBAAAmEC0AAMAEogUAAJhAtAAAABOIFgAAYEJirAdA7zWkbGusRwAAGMKVFgAAYALRAgAATCBaAACACUQLAAAwgWgBAAAmEC0AAMAEogUAAJhAtAAAABOIFgAAYALRAgAATCBaAACACUQLAAAwgWgBAAAmEC0AAMAEogUAAJiQGOsBEBlDyrbGegQAAKKKKy0AAMAEogUAAJhAtAAAABOIFgAAYAI34naCm1oBAOh5YnqlZfXq1RoyZIhSUlKUm5ur999/P5bjAACAHixm0fK73/1O8+fP18MPP6zm5maNGTNGU6ZM0eHDh2M1EgAA6MFiFi3Lly/X7Nmzdffdd2vkyJGqrKzUN77xDT3//POxGgkAAPRgMbmn5YsvvlBTU5PKy8tD6xISEpSfn6/6+voztg8GgwoGg6HHfr9fkhQIBKIyX0fwRFT2CwCAFdH4GvvVPh3HuaDXxyRa/vOf/+jUqVPyeDxh6z0ej/7+97+fsX1FRYUWLVp0xvrs7OyozQgAQG/mXhm9fR87dkxut7vLrzPx00Pl5eWaP39+6HFHR4cOHjyosWPHqqWlRampqTGcrncLBALKzs7mOMQYx6Fn4Dj0DByHnqGz4+A4jo4dO6asrKwL2mdMouWb3/ym+vTpo9bW1rD1ra2t8nq9Z2yfnJys5OTksHUJCf+9HSc1NZW/lD0Ax6Fn4Dj0DByHnoHj0DOcfhwu5ArLV2JyI25SUpLGjRunmpqa0LqOjg7V1NQoLy8vFiMBAIAeLmbfHpo/f75mzpyp8ePH69prr9XKlSvV1tamu+++O1YjAQCAHixm0fLDH/5Q//73v7Vw4UL5fD6NHTtWVVVVZ9ycezbJycl6+OGHz/i2EboXx6Fn4Dj0DByHnoHj0DNE4zi4nAv9uSMAAIBuxAcmAgAAE4gWAABgAtECAABMIFoAAIAJPTZa6urqNG3aNGVlZcnlcmnz5s3n3P7tt9+Wy+U6Y/H5fN0zcByqqKjQNddcowEDBigjI0MFBQXat2/f177ulVde0fDhw5WSkqJRo0bpT3/6UzdMG78u5Di88MILZ5wLKSkp3TRxfFqzZo1Gjx4d+kVZeXl5ev3118/5Gs6FyOvqceBc6B6LFy+Wy+VSaWnpObe72HOix0ZLW1ubxowZo9WrV3fpdfv27dNnn30WWjIyMqI0Yfyrra1VcXGxtm/frurqarW3t+vmm29WW1vbWV/z3nvv6c4779SsWbO0c+dOFRQUqKCgQB988EE3Th5fLuQ4SP/9LZT/ey4cPHiwmyaOT4MGDdLixYvV1NSkHTt26KabbtL06dO1Z8+eTrfnXIiOrh4HiXMh2hobG7V27VqNHj36nNtF5JxwDJDkbNq06ZzbvPXWW44k5/PPP++WmXqjw4cPO5Kc2tras25zxx13OFOnTg1bl5ub69x7773RHq/XOJ/jsG7dOsftdnffUL3UpZde6jz77LOdPse50H3OdRw4F6Lr2LFjztChQ53q6mrnhhtucObOnXvWbSNxTvTYKy0XauzYscrMzNR3v/tdvfvuu7EeJ674/X5JUnp6+lm3qa+vV35+fti6KVOmqL6+Pqqz9Sbncxwk6fjx47rsssuUnZ39tf8SRdecOnVKGzduVFtb21k/eoRzIfrO5zhInAvRVFxcrKlTp57xd70zkTgnTHzK8/nIzMxUZWWlxo8fr2AwqGeffVaTJk1SQ0ODrr766liPZ15HR4dKS0s1ceJEXXnllWfdzufznfFbjT0eD/cWRcj5Hodhw4bp+eef1+jRo+X3+7Vs2TJNmDBBe/bs0aBBg7px4viye/du5eXl6eTJk7rkkku0adMmjRw5stNtOReipyvHgXMhejZu3Kjm5mY1Njae1/aROCfiJlqGDRumYcOGhR5PmDBBH3/8sVasWKHf/OY3MZwsPhQXF+uDDz7QO++8E+tRerXzPQ55eXlh//KcMGGCRowYobVr1+qRRx6J9phxa9iwYdq1a5f8fr9+//vfa+bMmaqtrT3rF0xER1eOA+dCdLS0tGju3Lmqrq7u1hub4yZaOnPttdfyRTYCSkpKtGXLFtXV1X3tv0y8Xq9aW1vD1rW2tsrr9UZzxF6hK8fhdH379tVVV12ljz76KErT9Q5JSUn69re/LUkaN26cGhsb9etf/1pr1649Y1vOhejpynE4HedCZDQ1Nenw4cNh38k4deqU6urq9OSTTyoYDKpPnz5hr4nEORF397T8r127dikzMzPWY5jlOI5KSkq0adMmbdu2TTk5OV/7mry8PNXU1IStq66uPuf3m3FuF3IcTnfq1Cnt3r2b8yHCOjo6FAwGO32Oc6H7nOs4nI5zITImT56s3bt3a9euXaFl/PjxKioq0q5du84IFilC58SF3S8cfceOHXN27tzp7Ny505HkLF++3Nm5c6dz8OBBx3Ecp6yszLnrrrtC269YscLZvHmzs3//fmf37t3O3LlznYSEBOfNN9+M1Vsw77777nPcbrfz9ttvO5999lloOXHiRGibu+66yykrKws9fvfdd53ExERn2bJlzt69e52HH37Y6du3r7N79+5YvIW4cCHHYdGiRc4bb7zhfPzxx05TU5NTWFjopKSkOHv27InFW4gLZWVlTm1trXPgwAHnr3/9q1NWVua4XC7nz3/+s+M4nAvdpavHgXOh+5z+00PROCd6bLR89SPMpy8zZ850HMdxZs6c6dxwww2h7ZcsWeJcfvnlTkpKipOenu5MmjTJ2bZtW2yGjxOd/f+X5Kxbty60zQ033BA6Jl95+eWXne985ztOUlKSc8UVVzhbt27t3sHjzIUch9LSUmfw4MFOUlKS4/F4nNtuu81pbm7u/uHjyD333ONcdtllTlJSkvOtb33LmTx5cugLpeNwLnSXrh4HzoXuc3q0ROOccDmO43TtohAAAED3i+t7WgAAQPwgWgAAgAlECwAAMIFoAQAAJhAtAADABKIFAACYQLQAAAATiBYAAGAC0QIAAEwgWgAAgAlECwAAMIFoAQAAJvw/UXCcteGbq74AAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model_8 = tf.keras.Sequential([\n",
        "    tf.keras.layers.Dense(64, activation=\"relu\", input_shape=(13,)),\n",
        "    tf.keras.layers.Dense(32, activation=\"relu\"),\n",
        "    tf.keras.layers.Dense(16, activation=\"relu\"),\n",
        "    tf.keras.layers.Dense(8, activation=\"relu\"),\n",
        "    tf.keras.layers.Dense(4, activation=\"relu\"),\n",
        "    tf.keras.layers.Dropout(0.5),\n",
        "    tf.keras.layers.Dense(1, bias_initializer=tf.keras.initializers.Constant(np.mean(pre_y_train))),\n",
        "], name=\"mod_8\")\n",
        "model_8.compile(loss=tf.keras.losses.mae,\n",
        "                optimizer=tf.keras.optimizers.SGD(learning_rate=0.001),\n",
        "                metrics=[\"mae\"])\n",
        "early_stopping = tf.keras.callbacks.EarlyStopping(\n",
        "    min_delta=0,\n",
        "    patience=20,\n",
        "    restore_best_weights=True,\n",
        ")\n",
        "history_8 = model_8.fit(pre_x_train, pre_y_train, epochs=500, callbacks=[early_stopping], batch_size=64, validation_data=(pre_x_test, pre_y_test), verbose=0)\n",
        "plot_loss(history_8, 'mod_7', 5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 451
        },
        "id": "xNppo4o2KeP0",
        "outputId": "5a298053-bd45-4854-c053-f900d3672a3e"
      },
      "execution_count": 35,
      "outputs": [
        {
          "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": [
        "plt.plot(pre_x_test[:,0], pre_y_test, \"bo\")\n",
        "plt.plot(pre_x_test[:,0], model_8.predict(pre_x_test), \"ro\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 468
        },
        "id": "tAUlGrVEcPg8",
        "outputId": "462a3e88-9057-4879-add7-f81dcc20cd0c"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "4/4 [==============================] - 0s 3ms/step\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x78769ef54190>]"
            ]
          },
          "metadata": {},
          "execution_count": 36
        },
        {
          "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": [
        "plt.plot(pre_x_test[:,1], pre_y_test, \"bo\")\n",
        "plt.plot(pre_x_test[:,1], model_8.predict(pre_x_test), \"ro\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 468
        },
        "id": "BQAqVJKqcwmJ",
        "outputId": "815488b5-2a07-41c4-e861-922f4fe3e099"
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "4/4 [==============================] - 0s 3ms/step\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x78769efc2d40>]"
            ]
          },
          "metadata": {},
          "execution_count": 37
        },
        {
          "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": [
        "plt.plot(pre_x_test[:,2], pre_y_test, \"bo\")\n",
        "plt.plot(pre_x_test[:,2], model_8.predict(pre_x_test), \"ro\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 468
        },
        "id": "p6ZD2Zw5czgD",
        "outputId": "d3c797ce-215f-46f5-f8f2-57887405b158"
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "4/4 [==============================] - 0s 3ms/step\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x78769ee65cf0>]"
            ]
          },
          "metadata": {},
          "execution_count": 38
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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Z7jeQT80B1dXSe+9Ja9dKdXXWz8bG9AKuiROtxGnxDByYXBNQNgzF9otETXDxMGMzYCEYQVyZDhQy2fnSr/yS/j+ebBiK7ReJ0v3bQVCHfEcwgpjcCBTcyL+R69av751ivqePPkpuH2bDUGw/idXxedAge+8nqEO+IxhBTG4ECjQHpC8T+zAbhmL7TbQmuKYmgjrADoIRxORGoEBzQPoytQ+zYSi23/RsgissJKgD7CAYQUxuBAo0B6Qvk/swEx1u8w1BHZBYwJhoPQL8xe4UxHBWKGSNmmlujt5vJBCwLqiNjek92YU7yUrR829wwU6Mfeh/fsmjA7jJ7v2bmhHE5Fa/AZ4c08c+9L9sGEUFeIWaESQULSFZRUV6ibqiyZcnx0xup1f7MF+OXTrYR8hHdu/fBCOwhQupM/yWadYJubhNTmMfIV8RjAA+E+7X0fMbl839OnJxm5zGPkI+IxhBxlBLkrxwZ+BYeVuc6gzsplzcpmjSOd/zZR8BsdCBFWkJhaSGBmnZMutnOMtqpuepyVWZSiAX6zi5IR+y56Z7vufDPgKcwKy9PuZVDUSs9u2aGunuu3tXNzc1SZdeKi1YIP3Hf/CEF00mEsh53Q8h17PnxmpeCc/LZKd5Jdf3EeAUakZ8yqsaiFgT4zU1SYsXR883EjZ/PrUksTidQM4PMx3ncvZcp+ZlyuV9BDiJPiM+5FWHt0Tt23YFAnTK68nJBHJ+6YfgVlI8LzQ0WA8Aiaxda+UMiSWX9xFgB31GspQbM+XGkqh9OxmZKmO2cjKBnF/6IeTyZHpONa+E91GsRz5jsncfAU4iGPEZL280TrVb0ykvOqeypPqpH0KuZn6leQVwFx1YfcbLG43TF1Y65fVWXS1VVaXXMdlvN0ontslvwpMPJmpeSTT5YLimM5ZAwKpFrKrK7v0FpItgJMOSHRHj5Y0m0QU4WTw1RheeoyRVTt0onZTuNvlF9+/r9ddbnbIDgeiTD9ppXkmmpjMX9h+QKpppMiiVETETJ0oDB8b/3IEDM3OjSdQHIBCQ5s3rXSXfUzpT1uerZPKF5HJfDS/1/L7On2991wYMiFwvmSYoPzWpAX5GMJIhfhh6GU+sm1+iPgCLFkk7d1o5RaLhZpi8VIJWv/XV8DL5mhNifV8//th6LVgg1dVZo2caG+3vX781qQG+ZbJAW1ubkWTa2tq8Lootn39uTHm5MVYlbO9XIGBMRYW1Xk9r18Z+X/fX2rWpl2/lyt7lKy+3lnffhrVrjamrs35GK2u0z6moiPwcxLdypXU+RDtHAoHE+9LOcco0O+eTn6XzfbX72dGOcbqfDWQDu/dv8oxkQDo5CpYts56OE6mrszKiJsvpHCbMU5M6v+QLSUcuTALnVE6RWML7SIre9yQb9hF649pnD3lGPJROO3Emq3UzkcMk3HGxpsb6yZfRPr/kC0mVlzlxnJTpfh1+a1JD+pijy3mMpsmAdAKKTI6UoGe/v2R758ZsPZ96PtEOHmzvfen068jF4c/5yok5i9AbwUgGpBNQhEdKzJyZ3pDCaPx+88u3as9s79zo9/MpmliTCw4caHVUzeRQ6VwZ/pzPEtUGkjcmdTTTZIDdoZdSaiNaUo267d7U7D4pOikfqz3DQWvPcyTM70Oksy2YijfC7aOPjtxMumN0GLrL9qZVP8vbYCTTQxETBRRS/JtvdbX03ntWp7lUhhRGk+jmF3bNNe4GAX4fBp0p2Z4vJJuCKTtPtAMHSieeGPk7+nX4m9tDyrOxNjBruDK2J01OD+11cyhitKGX6Q7nTEf4b8caauhWOcIyOawyW2TzEOlY55Ob55AddofMP/ec90OlYY8XQ8rdSL2Qa+zev/MuGPEyEDDGHzfflSuNKSuL/2VyKwjww5fbD7k6/FCGVGVDMFVXZ+88q6vzuqSww6vrOHljkmf3/p1XHVj90PnIDyMQqqulkhJp2jRvyyF5X+0Zq0Pj/fe7WzWfzZ0bnR4pkomOzNnWvwWxeXkdDzetXnpp9N8b4++m1Wj8MnAgr4IRPwQCXt98w/bu9Uc5vLxJMETPOU4FU5kKDn03uWCUO0BIQV/cFPzOD9fxXOGXhzEpzzqw+iEQ8MsTml/K4VUnyFxJ2JUrQiHpzjutJ85MdGROp7OwY50kwx/0ve9ZX6xuvdc/GzJcNw2pz6vRZKny8joevm7EEq6VyYbrhu8GDrjUbJQWp/qM+KV/gh/aHP1SDmO86QTph3MBFjf7MCXbv8WxTpIJNjKkgAlJ5odaYL6jOjNJa01Qn/uqE7BfePndzZXrhpt9F+nAGoVfbsCxOl+Fy+DWxcdPIyHc7gRJh0Z/iPddyNRF3m5n4ZUrjQnqczNJa7sChIIvAoSkvh8rV9rauM4e/9+lclOtlXSI7MHL63iuXDfcDKrowBqFK52PbPQGqq6Wbr1VuueeyOq8YFCaO9e9trpwLpRobYb3/TKk6gHrpWXuNGC7nS7bL81UWSFDPdziNZXF4kTVe9z+LV9sa2dzi3bc8q4a9Ygq1Nz1690q1xxzv54KVNvrJBkKSTfcYKtcPVsqy9WkFbpUl+5eqfXrq3Ov/8OhQ9KSJdKOHdLIkdItt0iFhQnfFlRIv7t+vR6a36I9GiwjaYj2qkWlelET1algxjqRdr8eHKVDmqUlGqkd2qGRekC36HMV9lrPj/zQZaGnvApGuot3IqUsWm+gsjLrYjR6dNeFvH5VUHffLQXNIc3REo3Su5IC2hg6R4cWf6K/dgzSud8sk847T3r44cgvazDozI3hi4tudUeLqv7fYG3ZIn323l4dM7JUY0s/ULC2Vnr//SPrn3iidOON1naEU7Tu3WtlitqyxcrQFu+C0v3CM3y4NHaslfYy/P6//13BUEiT29ulgwet7ZowWwomeUxs3ji7d2gMmJAmar1K1aIWlWq9JiogqXrQel3Y3CI1OBgZHTxo9RlYu9baT1deaTUyJzqusbar5wX9uuukRx9NfIGP9Xk9l3/4oVXeRD3cDh6U5s2T3n3XOkcWL5aOPjruDWf9mkO6tMn6DjZqmCRphHbq7xqhNzVWg/Vh1/HolLUvHLnIh7exuVn64ANp0CDre/rBB9bTQFOTCiTNk9QzTir7IkCYaVbqyd3VvTtJ9tx/hw5Z53kKAl/8/Yd1g9Y0V0khORcUphgIOPbZt93W+2ns1lul735XOny493kUVl8v/Z//owubm3VhlD/9frBcu+ber/PjPdGlEVyHrxvfbbpNc3WPjtKR8t+tW3WP5uq/Khb5ItFfPL4MqtKvhMk8p5tp7tI8c1jBiPqowwqaX2he6tV7NuubO8vLzXUDV0YtQ8JXQYExxx2XfgN2tDYRp17BoDHz5kX+vXnzrOXJflZBQe/PSna74uyflSuNqdZKs0uR7/lAA80HGpjefo7WFlBVFXtb4x3XWNtVVZV4v0Y7HrE+b9685M6LcPlibdfIkb3LFy7PvHkmFLB3TjjaXOHAud8pmX06zhTo88jq+Gif3a+fI9+rv18937kMX9G+j9HOk1TY+ex585Lb/qqqI/s30bFJ1IbmQCegv1XNM53q3awWXva3Kgf2Y4aF74W/yMS9sAf6jESxdq0ViMQ7ke7SvOTbyRL1Bor4O4Guv9WzDCm9km3ATraRPtVX+OKT7IUn3melsl3x9s/Klabzi46D0c6FlPdztAte376pHdd585w5XuF96OTxHzjQmG98I+X32z3/rc6dAbNhXpodiBw+9+t02ZFrRYa/V1H3VSqduxJ9H9MJSOx8dkdHag8m3/hG74A91itWpxEnMqV9Uf5Y526nZG1fR0fq+9ElbgVVBCNRLP9Nhzms+CfSYQXN8t8keSLZ7Q3U42A7drGy22MriaAp7VcwaMz+/aldeHq+Cgrif7lT6Rqeyr6ws5+dvCkFAs7sv/Dx+Owz946/w69OpdkrMQPn/ucKmM8/63DlexXzepFMb007gUCqN1K7n714sXvnTfenSqeGj9x7r72/fe+9ye9DN7kYVNm9f+dVnpHxG5foKIV6dRQLC0g6SiGN37gkuQ9OspdPQL07q6XFGHtTRSbKFuSkUMjqD+HEgPvOTqsNOpZUptJMZV8k2s+p9MhM9PecSlgQCll9Otw6/g4LyOY5HksGzv2gjIIPL3HlexXzemH3uy9Z36FE51MoFP+7lu5nr1qV/Genqvt12anpdnfssPe37a7nlS+OV7x7YcrnQoqSCkYefPBBnXHGGSouLlZxcbEqKyv1zDPPxH3PE088oVNOOUV9+/bV2LFj9ac//SmtAqfjZGPvBLG7Xhe/dJ1OFBS5PZXk9u3OfVa8L3cqXcPT2Rex3utmsJeKd9/1ugTpS/W4Zerc37HDH1O02ilDJm+kdt/jVKBuR/frslPDR0aOtPc5dtfzig+DqqSCkfLyct11113atGmTXnvtNf3TP/2TqqqqtHXr1qjrv/zyy6qpqdG1116rzZs3a8aMGZoxY4beeustRwqfrILR9k4Qu+t1SZRG1C2JgiKXg6ZQvxLnPizelzuVcbrp7ItY7/XDTSme0aO9LkH6Uj1umTr3R470x8OInTJk8kZq9z3f+Ebyn52saGmbnRrLHx7RGE8waK3nZ34MqtJtDzr++OPNo48+GvV33/72t80ll1wSsey8884zN954Y1J/w7FZezPZThYrg1iybcCpvJLtM+JGB1bJbL31MXf7jCSTBSmVfZFoPyfZd8jO3wsVBHt1sE3pHOreZ8Sp4z9ggCvnka19n0gmzv3wtSKD36tOyYQCBc7sFz/0GfnLX1LeD5/bOOdjjqZxMlNaJjsBuyWT50IPGe8zEgqFtHz5ch04cECVlZVR19mwYYOm9Zgadvr06dqwYUPcz+7o6FB7e3vEyxGFhdLcuV3j97sz+qKdbO7c1MbbhzOIlZXFX++L2pNoZUhJook1uos3QUcGtPQdYe3PdH3/+/GPyRfbZYzU2aMVtFMBGaPe+yfZfWFnPztZQxYIyEh66Ji5kgJRtsti+xyaO9fK1+Dk8f/v/7ayfkUpR6JyGRvrdEnmHI+l+/F2okzSkWuFnYlvEnx2tL8d/n/Brd+3PifZSXV6+uL6F1eq1z+7n/3hh8l/tqQPL6jS3ZonKf5+7DihPPoMl+lMTtTTokVW/6ue6waD1vJFixJ/htcyeS6kKtko58033zTHHnusCQaDpqSkxPzxj3+MuW6fPn1MXY+8uA888IAZPHhw3L8xf/788Hcz4pV2zUhYJsfZd88vsWBB7BznqeTeiJZnJJWc6YlyLRQWpvU0F5LMTlWYtc99Hnt/291em8ckVs6Qnaow1VoZexdF2xcDB1qvVPZzvBz78bY1ynHdsmClkYz5ZoztqldV4lw1dvOMVFREzzMycGDvGpAeeRmazqmKOjywfUj0PCN/q5oXNb9BzJeT8wLEOff3aqBpk43ho7HOy3hzGqxcaT49PvbcNJ+rwLTp2Mh9WJYg10yq+8XLPCOp1B5WVXWlYbfyMxX02ner9M9mktaaZb9NULPh5H7s6LBGzcyebf3MguG8vWTyXPiC3ZqRgDHGJBO8HDp0SLt27VJbW5tWrFihRx99VOvWrdOpp57aa93CwkL9+te/Vk1NTdeyJUuWaMGCBdqzZ0/Mv9HR0aGOjo6u/7e3t6uiokJtbW0qLi5OprjxNiRzGQi7i5ftL1yGd9+1ovNzzpE++eRIRkgXMrCqpSUyo2r4Mw8etEbDhP/20qXS5s1SS4tCJwzWvdXr9f1PF8gosuOR9cQe0E0DV+jBPdVHimYjA6tCIal7BtbZs20dk1DI+simJqlAvbOpmkBQ5eVSY2OMXRXtGEmp7+domXgrKqwnr699zXYG1mV/COryy623R9uuTgV1lA7plf+9ROP7ZygDa4J9EZ75s485qF9qnkbpXW3XaN2qxToUOForlh1SdcuR71noxls0/EuFamqKzPzYPQPrx8Uj9MM/jFXw4w8zMy9Ajwysb38wSLf83zKtl7Wtk9SgyWpQQJ36RP11gj7SeL2usy84RoO+OdHKEhrrvIzzfW9YE9JPplnH8AMN1Fht0cl6ryvrZaeCmqj1WvLDFp06NYksvKnwKgNr+Mva3Gzd+qI59lhpwgTpS1/qysDa0GDNZCzFzxi6dm2cVP9hGZreIGtl+F7Y3t6ukpKSxPfvdKOeqVOnmhtuuCHq7yoqKsy9PcZb//jHPzZnnHFGUn/DsT4jcEzKNREZ4MuZNO3OxhaHL7erm1RSN/hxm9yaeM0vE3V6LoUZOtl32cu1PCOdnZ0RtRjdVVZWas2aNRHLVq9eHbOPCbJHdbV0xcpq/a+y9zRZa1WjOk3WWl1Y3qgrVla7Ntmf5M9Jn7pmY6upsX6m8OSVqAtKtEEDbkoldYMfj1Wi7kPGWBVOmfw7TnSLyRqx+teVx+jvIfZdXkgmwrn99tvNunXrTGNjo3nzzTfN7bffbgKBgPnLX/5ijDHmyiuvNLfffnvX+i+99JI56qijzN13323eeecdM3/+fNOnTx+zZcuWjERWcJ8DFQBp8+PTtlNSeIi0xYnjlsp06n4+Vom6UqU6FYydv+Nkt5iskcJJyL7LPhlJB/9v//ZvZtiwYaawsNAMGjTITJ06tSsQMcaYSZMmmauvvjriPX/4wx/Ml770JVNYWGhOO+20uB1eYyEYQTy5XoXr9AU42bnCYt0zUgks/H6sPv/c6nceq2zpBIA9/47XQXy2Yt9ll4x1YPWC7Q4wyFvhjpSSdesIC1fhxqj9zRpO9bkL76ee3/pY+ylaX9zycqvKvKoqfl/EQEBROw7HOlZhCxZI//Ef3lS5d+8MHU2sbQIQnd37N8GIj9DJOz3xBrFkcyDiFDs32rIya+DU3r3WIK+f/CR+4CKlFgRGO1bdhQMet49b91Eb8dgatQGAYCTbxHsC9eJGmq2BUbaW2w12b7R2dK8hWLUqtSAwFJJ+/nNp/vzony+5X6O1bJm6hlPHU1dn9U0GEJ/d+/dRLpYJMcSqOm9utpa7fUH2W2CUjPAgFvTm5AiV7iNlqqutJptUgsD//u/Ynx8IWClYqqrcCyidmsIEQHLSHtqL9MSbdT68rLbWuZnkEwkHRj2rz8OBUX29O+WA8zJxAw0HOKmMZHZqVncn+X04NZCrCEY85qcLst8CIzgrE5NLpxPgZFvOEfJZAJlDMOIxP12Q/RQYwXlOzpPoRA2BX5tEUsjJBSBNBCMe89MF2U+BETLD7uTS8ThVQ+DnJpHqaum996xRM3V11s/GRgIRIFPowOqx8AU5Ua4GNy7IfgqMkDk9O5wOHixdc038ucu6Ky93Zrh0uKZm5kzrPI82NNjLJhG/dYZmpBhyGUN7fcAvCbsSTahJwqfcFe8cNMZKRDZ6dGZuguSHSSybR7ghv5FnJMv45YIca5ixZN2YaDPPXV6egzz1x5Zs1lzATwhGspBfLsi33Sbdc0/kqJlgUJo7V1q0yP3ywD1+OQdhIT09sh3BCFLCUxjgH6SnR7aze/9mNA26kGcE8BdGuCFfEIygC3lGAH9hhBvyBcEIuvAUBviLn3OxAE4iGEEXnsIAfyE9PfIFwQi68BQG+A/p6ZEPyMCKLn7PiAnkq55Zcxl2jVxDMIII4aewaNkeM5n8ivwWQHx+S08POIlgBL24/RRGqmsAyG8kPYOnSLIGALmLpGfwPZKs5bdQyMowumyZ9ZPjDOQvghF4hiRr+au+3ppzZcoU6fLLrZ/Dh1vLAeQfghF4hiRr+SncNNczEG1utpYTkAD5h2AEniHJWv6haQ5ANAQj8AxJ1vIPTXMAoiEYgWdIdZ1/aJoDEA3BCDxFquv8QtMcgGjIMwJfIANrfgiFrFEzzc3R+40EAlYg2tjI8Qdygd37NxlY4Qukus4PzH8Er/HgE8kv+4NmGgCuomkOXiG/TSQ/7Q+aaQB4wi9PZMgPTD0Rya39Yff+TTACAMhp4b5KsYaV51tfJTf3B3PTAAAg8tv05Mf9QTACAMhp5LeJ5Mf9QTACAMhp5LeJ5Mf9QTACAMhpTD0RyY/7g2AEAJDTmHoikh/3B8EIgIw5dMi6qH33u9bPQ4e8LhHyFfltIvltfzC0F0BG3HabdM891jDCsGBQmjtXWrTIu3Ihv5HfJlKm9wfp4AF45rbbpMWLey8PhY4sJyCBF5h6IpJf9gc1IwAcdeiQdMwxkTUiPQWD0mefSYWF7pULgPtIegbAE0uWxA9EJOv3S5a4Ux4A/kczDQBH7djh7Hpeon+B/3BMchPBCABHjRzp7Hpeqa+X5syJTJtdXm4Nicy3kRd+wTHJXfQZAeCoXOgzwgyv/sMxyU70GQHgicJCa/huPHPn+jcQCYWsp+9oj2nhZbW1ifvFwDkck9xHMALAcYsWSfPm9W7LDwat5X4e1uvHGU3zHcck99FnBEBGLFok/exn1qiZHTusPiK33OLfGpEwP85omu84JrmPYARAxhQWWtXn2cSPM5rmO45J7qOZBgC68eOMpvmOY5L7CEYAoBs/zmia7zgmuY9gBAB68NuMpuCY5DryjABADGT79B+OSXZh1l4ASJNfZjTNRakGFRyT3EQwAgBwVTpp3akZyU30GQEAuCac1r1nErPmZmt5fX389w4fLk2ZIl1+ufVz+PD470F2IBgBALginbTu6QQx8D+CEQCAK1JN687cNLmPYAQA4IpU07ozN03uIxgBALgi1bTuzE2T+whGAACuSDWtO3PT5D6CEQCAK1JN687cNLmPYAQA4JpU0rozN03uIx08AMB1qSQvi5YsraLCCkSYm8af7N6/CUYAAFmDDKzZxe79O6lmmoULF+qcc85Rv379NHjwYM2YMUPbtm2L+56lS5cqEAhEvPr27ZvMnwUAQNKRuWlqaqyfBCK5IalgZN26dZo1a5ZeeeUVrV69WocPH9ZFF12kAwcOxH1fcXGxWlpaul47d+5Mq9AAACB3JDVR3p///OeI/y9dulSDBw/Wpk2bdOGFF8Z8XyAQ0NChQ1MrIQDkAZofkM/SGk3T1tYmSRowYEDc9T799FMNGzZMFRUVqqqq0tatW+Ou39HRofb29ogXAOQqJoBDvks5GOns7FRtba0uuOACnX766THXGzNmjB577DGtWrVKv/3tb9XZ2akJEyaoKU5u34ULF6qkpKTrVVFRkWoxAcDXmAAOSGM0zc0336xnnnlGL774osrLy22/7/Dhw/ryl7+smpoa/fSnP426TkdHhzo6Orr+397eroqKCkbTAMgpoZBVAxLr2SwQsPJvNDbSZIPsZHc0TVJ9RsJmz56tp59+Wi+88EJSgYgk9enTR2eddZa2b98ec52ioiIVFRWlUjQAyBrJTAA3ebJrxQJcl1QzjTFGs2fP1pNPPqnnn39eI0aMSPoPhkIhbdmyRaVMIgAgzzEBHGBJqmZk1qxZqqur06pVq9SvXz+1trZKkkpKSnT00UdLkq666iqVlZVp4cKFkqQ777xT559/vkaNGqV9+/Zp8eLF2rlzp6677jqHNwUAsgsTwAGWpIKRBx98UJI0uUd94eOPP65rrrlGkrRr1y4VFBypcPnkk090/fXXq7W1Vccff7zGjx+vl19+Waeeemp6JQeALBeeAK652WqS6SncZ4QJ4JDrSAcPAB4Kj6aRIgOS8ARwsSaPA7JBRtLBAwCclcostkCuSWk0DQDAOdXVUlUVGViRvwhGAMAHwhPAAfmIZhoAAOApghEAAOApghEAAOApghEAAOApghEAAOApghEAAOApghEAAOApghEAAOApghEAAOApghEAAOApghEAAOApghEAAOApJsoDgBhCIWbSdRP7O38RjABAFPX10pw5UlPTkWXl5dL990vV1d6VK1exv/MbzTQA0EN9vTRzZuSNUZKam63l9fXelCtXsb8RMMYYrwuRSHt7u0pKStTW1qbi4mKviwMgh4VC0vDhvW+MYYGA9cTe2EgTghPY37nN7v2bmhEA6Gb9+tg3RkkyRtq921oP6WN/QyIYAYAILS3Orof42N+QCEYAIEJpqbPrIT72NySCEQCIMHGi1UchEIj++0BAqqiw1kP62N+QCEYAIEIwaA0nlXrfIMP/v+8+OlM6hf0NiWAEAHqprpZWrJDKyiKXl5dby8l74azqaunWW6WCHnekggJrOfs79zG0FwBiICOoO8J5RqLdjQIBAsBsZvf+TTACAHBMsgEceUZyG3lGAACuqq+3AospU6TLL7d+Dh8eP4MqeUYgEYwAAByQakp38oxAIhgBAKQpFLImuYvW6B9eVltrrdcTeUYgEYwAANKUTlMLeUYgEYwAANKUTlMLeUYgEYwAANKUblMLeV3A0F4AQFrCw3Obm2PnCrEzPJe8LrnH7v37KBfLBADIQeGmlpkzrcCje0CSTFNLMChNnpypUsLPaKYBAKSNphakg5oRAIAjqqulqiqaWpA8ghEAgGNoakEqaKYBAACeIhgBAACeIhgBAACeIhgBAACeIhgBAACeIhgBAACeIhgBAACeIhgBAACeIhgBAACeIhgBAACeIhgBAACeIhgBAACeIhgBAACeYtZeAHBZKCStXy+1tEilpdLEidZst0C+IhgBABfV10tz5khNTUeWlZdL998vVVd7Vy7ASzTTAIBL6uulmTMjAxFJam62ltfXe1MuwGsEIwDgglDIqhExpvfvwstqa631gHxDMAIALli/vneNSHfGSLt3W+sB+YZgBABc0NLi7HpALiEYAQAXlJY6ux6QSwhGAMAFEydao2YCgei/DwSkigprPSDfEIwAgAuCQWv4rtQ7IAn//777yDeC/EQwAgAuqa6WVqyQysoil5eXW8vJM4J8RdIzAHBRdbVUVUUGVqA7ghEAcFkwKE2e7HUpAP+gmQYAAHiKYAQAAHiKZhoAgC8wm3H+SqpmZOHChTrnnHPUr18/DR48WDNmzNC2bdsSvu+JJ57QKaecor59+2rs2LH605/+lHKBAQC5p75eGj5cmjJFuvxy6+fw4UwemC+SCkbWrVunWbNm6ZVXXtHq1at1+PBhXXTRRTpw4EDM97z88suqqanRtddeq82bN2vGjBmaMWOG3nrrrbQLDwDIfsxmjIAx0eaQtOeDDz7Q4MGDtW7dOl144YVR17nssst04MABPf30013Lzj//fI0bN04PPfSQrb/T3t6ukpIStbW1qbi4ONXiAgB8JhSyakBiTSIYCFh5WBobabLJRnbv32l1YG1ra5MkDRgwIOY6GzZs0LRp0yKWTZ8+XRs2bIj5no6ODrW3t0e8AAD+FwpJDQ3SsmXWz1Ao/no/+QmzGSONDqydnZ2qra3VBRdcoNNPPz3meq2trRoyZEjEsiFDhqi1tTXmexYuXKgFCxakWjQAgAfq66U5cyKDi/JyKw1+9+yy0dZLhNmMc1vKNSOzZs3SW2+9peXLlztZHknSHXfcoba2tq7X7t27Hf8bAADn2O33EWu9RJjNOLelVDMye/ZsPf3003rhhRdUXl4ed92hQ4dqz549Ecv27NmjoUOHxnxPUVGRioqKUikaAMBloZBV0xGtB6IxVr+P2lrpn/859nqxhPuMMJtxbkuqZsQYo9mzZ+vJJ5/U888/rxEjRiR8T2VlpdasWROxbPXq1aqsrEyupACQI+z2q8gW69fb6/exZElyNSLMZpw/kqoZmTVrlurq6rRq1Sr169evq99HSUmJjj76aEnSVVddpbKyMi1cuFCSNGfOHE2aNEm//OUvdckll2j58uV67bXX9Mgjjzi8KQDgf3b7VWQTu/05duxI7nPLy61AJFv3C+xLqmbkwQcfVFtbmyZPnqzS0tKu1+9///uudXbt2qWWbmfmhAkTVFdXp0ceeURnnnmmVqxYoaeeeipup1cAyEW5mk/Dbn+OkSPtrffDH0pr11rDeQlE8kNaeUbcQp4RANkul/NphLetuTl6f5Dwtm3fbgUkidbLxn2A6FzJMwIAsMduv4pszKcRDFrNTNKRfh5h3ft9FBbaW49AJP8QjACAC+z2q8jWfBrV1dKKFVJZWeTy8nJrebi5xe56yC/M2gsALrDbryKb82lUV0tVVYln3rW7HvIHfUYAwAV2+1XQXwK5hD4jAOAjdvtVEIggHxGMAIBL6C8BREefEQBwEf0lgN4IRgDAZcGgNHmy16UA/INmGgAA4CmCEQAA4CmCEQAA4CmCEQAA4CmCEQAA4CmCEQAA4CmCEQAA4CmCEQAA4CmCEQAA4CmCEQAA4CmCEQAA4CmCEQAA4CmCEQAA4CmCEQAA4CmCEQAA4CmCEQAA4CmCEQAA4CmCEQAA4CmCEQAA4CmCEQAA4CmCEQAA4CmCEQAA4KmjvC4AACD/hELS+vVSS4tUWipNnCgFg16XCl4hGAEAuKq+XpozR2pqOrKsvFy6/36putq7csE7NNMAAFxTXy/NnBkZiEhSc7O1vL7em3LBWwQjAABXhEJWjYgxvX8XXlZba62H/EIwAgBwxfr1vWtEujNG2r3bWg/5hWAEAOCKlhZn10PuIBgBALiitNTZ9ZA7CEYAAK6YONEaNRMIRP99ICBVVFjrIb8QjAAAXBEMWsN3pd4BSfj/991HvpF8RDACAHBNdbW0YoVUVha5vLzcWk6ekfxE0jMAgKuqq6WqKjKw4giCEQCA64JBafJkr0sBv6CZBgAAeIpgBAAAeIpgBAAAeIpgBAAAeIpgBAAAeIpgBAAAeIpgBAAAeIpgBAAAeIpgBAAAeCorMrAaYyRJ7e3tHpcEAADYFb5vh+/jsWRFMLJ//35JUkVFhcclAQAAydq/f79KSkpi/j5gEoUrPtDZ2an3339f/fr1UyAQUHt7uyoqKrR7924VFxd7XbyMyZftlNjWXJQv2ymxrbkoX7ZTyuy2GmO0f/9+nXjiiSooiN0zJCtqRgoKClReXt5reXFxcc6fJFL+bKfEtuaifNlOiW3NRfmynVLmtjVejUgYHVgBAICnCEYAAICnsjIYKSoq0vz581VUVOR1UTIqX7ZTYltzUb5sp8S25qJ82U7JH9uaFR1YAQBA7srKmhEAAJA7CEYAAICnCEYAAICnCEYAAICnCEYAAICnfB+MvPfee7r22ms1YsQIHX300Ro5cqTmz5+vQ4cOxX3fP/7xD82aNUsDBw7Ucccdp0svvVR79uxxqdSp+/nPf64JEybomGOOUf/+/W2955prrlEgEIh4XXzxxZktqANS2VZjjH784x+rtLRURx99tKZNm6Z33303swVN08cff6wrrrhCxcXF6t+/v6699lp9+umncd8zefLkXsf0pptucqnE9j3wwAMaPny4+vbtq/POO09//etf467/xBNP6JRTTlHfvn01duxY/elPf3KppOlLZluXLl3a6/j17dvXxdKm5oUXXtC//Mu/6MQTT1QgENBTTz2V8D0NDQ06++yzVVRUpFGjRmnp0qUZL6cTkt3WhoaGXsc0EAiotbXVnQKnaOHChTrnnHPUr18/DR48WDNmzNC2bdsSvs/t76rvg5G//e1v6uzs1MMPP6ytW7fq3nvv1UMPPaQf/OAHcd/3ve99T//zP/+jJ554QuvWrdP777+v6upql0qdukOHDulb3/qWbr755qTed/HFF6ulpaXrtWzZsgyV0DmpbOuiRYv0n//5n3rooYe0ceNGHXvssZo+fbr+8Y9/ZLCk6bniiiu0detWrV69Wk8//bReeOEF3XDDDQnfd/3110cc00WLFrlQWvt+//vfa+7cuZo/f75ef/11nXnmmZo+fbr27t0bdf2XX35ZNTU1uvbaa7V582bNmDFDM2bM0FtvveVyyZOX7LZKVmrt7sdv586dLpY4NQcOHNCZZ56pBx54wNb6jY2NuuSSSzRlyhS98cYbqq2t1XXXXadnn302wyVNX7LbGrZt27aI4zp48OAMldAZ69at06xZs/TKK69o9erVOnz4sC666CIdOHAg5ns8+a6aLLRo0SIzYsSImL/ft2+f6dOnj3niiSe6lr3zzjtGktmwYYMbRUzb448/bkpKSmyte/XVV5uqqqqMlieT7G5rZ2enGTp0qFm8eHHXsn379pmioiKzbNmyDJYwdW+//baRZF599dWuZc8884wJBAKmubk55vsmTZpk5syZ40IJU3fuueeaWbNmdf0/FAqZE0880SxcuDDq+t/+9rfNJZdcErHsvPPOMzfeeGNGy+mEZLc1me+vX0kyTz75ZNx1brvtNnPaaadFLLvsssvM9OnTM1gy59nZ1rVr1xpJ5pNPPnGlTJmyd+9eI8msW7cu5jpefFd9XzMSTVtbmwYMGBDz95s2bdLhw4c1bdq0rmWnnHKKTjrpJG3YsMGNIrquoaFBgwcP1pgxY3TzzTfro48+8rpIjmtsbFRra2vEcS0pKdF5553n2+O6YcMG9e/fX1/5yle6lk2bNk0FBQXauHFj3Pf+7ne/0wknnKDTTz9dd9xxhz777LNMF9e2Q4cOadOmTRHHoqCgQNOmTYt5LDZs2BCxviRNnz7dt8cuLJVtlaRPP/1Uw4YNU0VFhaqqqrR161Y3iuuqbD2m6Rg3bpxKS0v11a9+VS+99JLXxUlaW1ubJMW9h3pxXLNi1t7utm/frl/96le6++67Y67T2tqqwsLCXv0QhgwZ4vv2vVRcfPHFqq6u1ogRI7Rjxw794Ac/0Ne+9jVt2LBBwWDQ6+I5JnzshgwZErHcz8e1tbW1VzXuUUcdpQEDBsQt8+WXX65hw4bpxBNP1Jtvvql///d/17Zt21RfX5/pItvy4YcfKhQKRT0Wf/vb36K+p7W1NauOXVgq2zpmzBg99thjOuOMM9TW1qa7775bEyZM0NatW6POQJ6tYh3T9vZ2HTx4UEcffbRHJXNeaWmpHnroIX3lK19RR0eHHn30UU2ePFkbN27U2Wef7XXxbOns7FRtba0uuOACnX766THX8+K76lnNyO233x61M1D3V88venNzsy6++GJ961vf0vXXX+9RyZOXyrYm4zvf+Y6+8Y1vaOzYsZoxY4aefvppvfrqq2poaHBuI2zK9Lb6Raa384YbbtD06dM1duxYXXHFFfrNb36jJ598Ujt27HBwK5AplZWVuuqqqzRu3DhNmjRJ9fX1GjRokB5++GGvi4YUjRkzRjfeeKPGjx+vCRMm6LHHHtOECRN07733el0022bNmqW33npLy5cv97oovXhWM/L9739f11xzTdx1Tj755K5/v//++5oyZYomTJigRx55JO77hg4dqkOHDmnfvn0RtSN79uzR0KFD0yl2SpLd1nSdfPLJOuGEE7R9+3ZNnTrVsc+1I5PbGj52e/bsUWlpadfyPXv2aNy4cSl9ZqrsbufQoUN7dXL8/PPP9fHHHyd1Lp533nmSrJrBkSNHJl1ep51wwgkKBoO9RqjF+44NHTo0qfX9IpVt7alPnz4666yztH379kwU0TOxjmlxcXFO1YrEcu655+rFF1/0uhi2zJ49u6sDfaLaOS++q54FI4MGDdKgQYNsrdvc3KwpU6Zo/Pjxevzxx1VQEL9CZ/z48erTp4/WrFmjSy+9VJLVA3rXrl2qrKxMu+zJSmZbndDU1KSPPvoo4obtlkxu64gRIzR06FCtWbOmK/hob2/Xxo0bkx59lC6721lZWal9+/Zp06ZNGj9+vCTp+eefV2dnZ1eAYccbb7whSZ4c02gKCws1fvx4rVmzRjNmzJBkVQGvWbNGs2fPjvqeyspKrVmzRrW1tV3LVq9e7cl3MhmpbGtPoVBIW7Zs0de//vUMltR9lZWVvYZ8ZsMxdcobb7zhm+9kLMYYffe739WTTz6phoYGjRgxIuF7PPmuZqxrrEOamprMqFGjzNSpU01TU5NpaWnpenVfZ8yYMWbjxo1dy2666SZz0kknmeeff9689tprprKy0lRWVnqxCUnZuXOn2bx5s1mwYIE57rjjzObNm83mzZvN/v37u9YZM2aMqa+vN8YYs3//fnPrrbeaDRs2mMbGRvPcc8+Zs88+24wePdr84x//8GozbEl2W40x5q677jL9+/c3q1atMm+++aapqqoyI0aMMAcPHvRiE2y5+OKLzVlnnWU2btxoXnzxRTN69GhTU1PT9fue5+/27dvNnXfeaV577TXT2NhoVq1aZU4++WRz4YUXerUJUS1fvtwUFRWZpUuXmrffftvccMMNpn///qa1tdUYY8yVV15pbr/99q71X3rpJXPUUUeZu+++27zzzjtm/vz5pk+fPmbLli1ebYJtyW7rggULzLPPPmt27NhhNm3aZL7zne+Yvn37mq1bt3q1Cbbs37+/63soydxzzz1m8+bNZufOncYYY26//XZz5ZVXdq3/97//3RxzzDFm3rx55p133jEPPPCACQaD5s9//rNXm2Bbstt67733mqeeesq8++67ZsuWLWbOnDmmoKDAPPfcc15tgi0333yzKSkpMQ0NDRH3z88++6xrHT98V30fjDz++ONGUtRXWGNjo5Fk1q5d27Xs4MGD5pZbbjHHH3+8OeaYY8w3v/nNiADGr66++uqo29p92ySZxx9/3BhjzGeffWYuuugiM2jQINOnTx8zbNgwc/3113ddJP0s2W01xhre+6Mf/cgMGTLEFBUVmalTp5pt27a5X/gkfPTRR6ampsYcd9xxpri42Pzrv/5rRMDV8/zdtWuXufDCC82AAQNMUVGRGTVqlJk3b55pa2vzaAti+9WvfmVOOukkU1hYaM4991zzyiuvdP1u0qRJ5uqrr45Y/w9/+IP50pe+ZAoLC81pp51m/vjHP7pc4tQls621tbVd6w4ZMsR8/etfN6+//roHpU5OePhqz1d4266++mozadKkXu8ZN26cKSwsNCeffHLE99XPkt3WX/ziF2bkyJGmb9++ZsCAAWby5Mnm+eef96bwSYh1/+x+nPzwXQ18UVgAAABPZGWeEQAAkDsIRgAAgKcIRgAAgKcIRgAAgKcIRgAAgKcIRgAAgKcIRgAAgKcIRgAAgKcIRgAAgKcIRgAAgKcIRgAAgKf+P/sIYw9zPdZnAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(pre_x_test[:,3], pre_y_test, \"bo\")\n",
        "plt.plot(pre_x_test[:,3], model_8.predict(pre_x_test), \"ro\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 468
        },
        "id": "51sWhhksc1Tu",
        "outputId": "4da081c2-ca0c-4539-eda1-48e51285d0b3"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "4/4 [==============================] - 0s 3ms/step\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x78769eeca7a0>]"
            ]
          },
          "metadata": {},
          "execution_count": 39
        },
        {
          "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": [
        "plt.plot(pre_x_test[:,4], pre_y_test, \"bo\")\n",
        "plt.plot(pre_x_test[:,4], model_8.predict(pre_x_test), \"ro\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 468
        },
        "id": "5-t5sC4oc40a",
        "outputId": "991c46e5-cf75-4fb5-ee98-a24ae8de3a9d"
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "4/4 [==============================] - 0s 3ms/step\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x78769ed35510>]"
            ]
          },
          "metadata": {},
          "execution_count": 40
        },
        {
          "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": [
        "plt.plot(pre_x_test[:,5], pre_y_test, \"bo\")\n",
        "plt.plot(pre_x_test[:,5], model_8.predict(pre_x_test), \"ro\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 468
        },
        "id": "baDtt1WEc7_N",
        "outputId": "c2ee483b-b8e8-40b9-d820-fc24057c94be"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "4/4 [==============================] - 0s 3ms/step\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x78769eddc280>]"
            ]
          },
          "metadata": {},
          "execution_count": 41
        },
        {
          "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": [
        "plt.plot(pre_x_test[:,5], pre_y_test, \"bo\")\n",
        "plt.plot(pre_x_test[:,5], model_8.predict(pre_x_test), \"ro\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 468
        },
        "id": "a4nvsmANc9pM",
        "outputId": "623b81c7-5ed3-48cb-aaa9-98165d4a6446"
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "4/4 [==============================] - 0s 3ms/step\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x78769ec192a0>]"
            ]
          },
          "metadata": {},
          "execution_count": 42
        },
        {
          "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": "lELujOfkc_sw"
      },
      "execution_count": 42,
      "outputs": []
    }
  ]
}