goit_python_ds_hw_09-8911.ipynb

{
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  "metadata": {
    "colab": {
      "provenance": [],
      "collapsed_sections": [
        "jmJyh7Upwyfu",
        "thFtPJEF5lYY"
      ],
      "authorship_tag": "ABX9TyOho8LNgqsa6Uo6X/CWqTes",
      "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/lexxai/CourseraSaveAssist/blob/main/goit_python_ds_hw_09-8911.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Модуль 9. Підбір гіперпараметрів НМ\n",
        "\n",
        "*З циклу [домашніх завдань Python Data Science](https://github.com/lexxai/goit_python_data_sciense_homework).*\n",
        "\n",
        "# Домашнє завдання"
      ],
      "metadata": {
        "id": "70GUWXMHwUKi"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Про датасет Fashion-MNIST\n",
        "\n",
        "Дану нейромережу ми будемо вивчати на датасеті Fashion-MNIST.\n",
        "Fashion-MNIST - це набір даних зображень статей Zalando, що складається з навчального набору з 60 000 прикладів і тестового набору з 10 000 прикладів. Кожен приклад - це зображення 28x28 у відтінках сірого, пов'язане з міткою з 10 класів. Кожен піксель приймає значення від 0 до 255.\n",
        "\n",
        "**Label\tDescription**\n",
        "\n",
        "| Label | Clothing Item | --- | Label | Clothing Item | --- | Label | Clothing Item | --- | Label | Clothing Item | --- | Label | Clothing Item |\n",
        "|-------|---------------|-----|-------|---------------|-----|-------|---------------|-----|-------|---------------|-----|-------|---------------|\n",
        "| 0     | T-shirt/top   |     | 2     | Pullover      |     | 4     | Coat          |     | 6     | Shirt         |     | 8     | Bag           |\n",
        "| 1     | Trouser       |     | 3     | Dress         |     | 5     | Sandal        |     | 7     | Sneaker       |     | 9     | Ankle boot    |\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "jmJyh7Upwyfu"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 34,
      "metadata": {
        "id": "Ujit5CoCwOz_"
      },
      "outputs": [],
      "source": [
        "import tensorflow as tf\n",
        "\n",
        "from keras.models import Sequential\n",
        "from keras.layers import Input, Dense, Flatten, Conv2D, MaxPooling2D\n",
        "from keras import optimizers, regularizers\n",
        "from keras import losses, metrics\n",
        "from keras.utils import plot_model\n",
        "\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from matplotlib.ticker import MultipleLocator\n",
        "from sklearn.metrics import confusion_matrix, classification_report, ConfusionMatrixDisplay"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "iDN285c27drt"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Завантажуємо датасет"
      ],
      "metadata": {
        "id": "LDowYTxB5NZ3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# from tensorflow.keras.datasets import mnist\n",
        "from keras.datasets import fashion_mnist\n",
        "\n",
        "# Завантажуємо датасет\n",
        "(x_train, y_train), (x_test, y_test) = fashion_mnist.load_data()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "H2pS_-FIx8zl",
        "outputId": "88d4b989-895f-44e6-9560-3f3b2d5da7dd"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-labels-idx1-ubyte.gz\n",
            "29515/29515 [==============================] - 0s 0us/step\n",
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-images-idx3-ubyte.gz\n",
            "26421880/26421880 [==============================] - 0s 0us/step\n",
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/t10k-labels-idx1-ubyte.gz\n",
            "5148/5148 [==============================] - 0s 0us/step\n",
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/t10k-images-idx3-ubyte.gz\n",
            "4422102/4422102 [==============================] - 2s 0us/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "num_classes = 10 # загальна кількість класів\n",
        "learning_rate = 0.001 # швидкість навчання нейронної мережі\n",
        "num_features = x_train.shape[1] * x_train.shape[2] # кількість атрибутів вхідного вектора 28 * 28 = 784\n",
        "num_features"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OGzM2QfHxlJ1",
        "outputId": "5a2dc2b0-999e-4474-bbb9-25151c9748c2"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "784"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "labels = ['T-shirt/top', 'Trouser', \"Pullover\", \"Dress\", \"Coat\", \"Sandal\", \"Shirt\", \"Sneaker\", \"Bag\", \"Ankle boot\"]\n",
        "labels_uk = [\"Футболка/топ\", \"Штани\", \"Пуловер\", \"Сукня\", \"Пальто\", \"Босоніжки\", \"Сорочка\", \"Кросівки\", \"Сумка\", \"Черевики\"]"
      ],
      "metadata": {
        "id": "qi4Zijez_sJI"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Перетворюємо цілочисельні пікселі на тип float32\n",
        "x_train, x_test = np.array(x_train, np.float32), np.array(x_test, np.float32)\n",
        "# Нормалізуємо значення пікселів\n",
        "x_train, x_test = x_train / 255., x_test / 255."
      ],
      "metadata": {
        "id": "gPugeFesykGd"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x_train.shape[1:]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "N-tPKIXD0JLT",
        "outputId": "3dc13439-a32c-49ed-df68-40efa15a19d3"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(28, 28)"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Створення моделі"
      ],
      "metadata": {
        "id": "4nLzlIVn5Q2t"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "n_hidden_1 = 256 # кількість нейронів 1-го шару\n",
        "n_hidden_2 = 512 # кількість нейронів 2-го шару\n",
        "n_hidden_3 = 16 # кількість нейронів 3-го шару\n",
        "\n",
        "kernel_regularizer=regularizers.l2(0.01)\n",
        "\n",
        "model = Sequential([\n",
        "    # Conv2D(32, (3, 3), activation='relu', kernel_initializer='he_uniform', input_shape=(28, 28, 1)),\n",
        "    # MaxPooling2D(2, 2),\n",
        "    # Flatten(),\n",
        "    Flatten(input_shape=x_train.shape[1:], name=\"INPUT\"),\n",
        "    Dense(n_hidden_1, activation='relu', name=\"Hidden_Layer_1\"),\n",
        "    Dense(n_hidden_2, activation='relu', kernel_regularizer=kernel_regularizer, name=\"Hidden_Layer_2\"),\n",
        "    Dense(256, activation='relu', name=\"Hidden_Layer_3\"),\n",
        "    Dense(32, activation='relu', name=\"Hidden_Layer_4\"),\n",
        "\n",
        "\n",
        "    # Dense(n_hidden_3, activation='relu', name=\"Hidden_Layer_3\"),\n",
        "    Dense(num_classes, activation='softmax', name=\"OUTPUT\"),\n",
        "])\n",
        "\n",
        "model.compile(\n",
        "    optimizer=optimizers.Adam(learning_rate=learning_rate),\n",
        "    loss='sparse_categorical_crossentropy',\n",
        "    metrics=[\"accuracy\"]\n",
        ")\n",
        "\n",
        "model.summary()\n",
        "plot_model(model, to_file='model_plot.png', show_shapes=True, show_layer_names=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "BFt3mSiWzYJ2",
        "outputId": "c9746045-d6b0-4e11-d2d2-7c1a72e6c4d1"
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential_3\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " INPUT (Flatten)             (None, 784)               0         \n",
            "                                                                 \n",
            " Hidden_Layer_1 (Dense)      (None, 256)               200960    \n",
            "                                                                 \n",
            " Hidden_Layer_2 (Dense)      (None, 512)               131584    \n",
            "                                                                 \n",
            " Hidden_Layer_3 (Dense)      (None, 256)               131328    \n",
            "                                                                 \n",
            " Hidden_Layer_4 (Dense)      (None, 32)                8224      \n",
            "                                                                 \n",
            " OUTPUT (Dense)              (None, 10)                330       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 472426 (1.80 MB)\n",
            "Trainable params: 472426 (1.80 MB)\n",
            "Non-trainable params: 0 (0.00 Byte)\n",
            "_________________________________________________________________\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Навчання моделі"
      ],
      "metadata": {
        "id": "Y9Yegjgc5W3d"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "batch_size = 450 # перераховувати ваги мережі ми будемо не на всій вибірці, а на її випадковій підмножині з batch_size елементів\n",
        "epochs = 3\n",
        "\n",
        "history = model.fit(\n",
        "    x_train,\n",
        "    y_train,\n",
        "    initial_epoch=0,\n",
        "    epochs=epochs,\n",
        "    batch_size=batch_size,\n",
        "    validation_data=(x_test, y_test),\n",
        "    use_multiprocessing=True\n",
        ")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2-56EBBv6wce",
        "outputId": "248f4aaf-ab1e-4b69-984a-61c73da5eab3"
      },
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/3\n",
            "134/134 [==============================] - 8s 59ms/step - loss: 0.0671 - accuracy: 0.9806 - val_loss: 0.6774 - val_accuracy: 0.8801\n",
            "Epoch 2/3\n",
            "134/134 [==============================] - 4s 31ms/step - loss: 0.0680 - accuracy: 0.9806 - val_loss: 0.5776 - val_accuracy: 0.8871\n",
            "Epoch 3/3\n",
            "134/134 [==============================] - 5s 38ms/step - loss: 0.0598 - accuracy: 0.9830 - val_loss: 0.5987 - val_accuracy: 0.8911\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Аналіз результатів"
      ],
      "metadata": {
        "id": "ACdVLIbc5efD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "results = model.evaluate(x_test, y_test, verbose=True)\n",
        "print(results)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KdMErH-EdKDU",
        "outputId": "73c5f148-5385-4758-949c-ff0cb8ec874a"
      },
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "313/313 [==============================] - 1s 3ms/step - loss: 0.5987 - accuracy: 0.8911\n",
            "[0.5986995697021484, 0.8910999894142151]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "history.history.keys()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KJMTwynL7omv",
        "outputId": "9b03ffe2-8dbb-427f-c4d0-873c4a5a885a"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "dict_keys(['loss', 'accuracy', 'val_loss', 'val_accuracy'])"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def pair_plot(loss_history, accuracy_history, title):\n",
        "  fig, ax1 = plt.subplots()\n",
        "  fig.set_size_inches((12,6))\n",
        "\n",
        "  color = 'tab:red'\n",
        "  ax1.set_xlabel('Epoch')\n",
        "  ax1.set_ylabel('Loss', color=color)\n",
        "  ax1.plot(loss_history, color=color, label=\"Loss\")\n",
        "  ax1.tick_params(axis='y', labelcolor=color)\n",
        "  ax1.xaxis.set_major_formatter(plt.FuncFormatter(lambda x, _: int((x + 1))))\n",
        "  ax1.yaxis.set_major_formatter(plt.FuncFormatter(lambda y, _: f'{(y):.2f}'))\n",
        "  ax1.set_xticks(np.arange(0, len(loss_history)+1, step=2))  # Set label locations.\n",
        "  #ax1.legend()\n",
        "\n",
        "\n",
        "  ax2 = ax1.twinx()  # instantiate a second axes that shares the same x-axis\n",
        "\n",
        "  color = 'tab:blue'\n",
        "  ax2.set_ylabel('Accuracy', color=color)  # we already handled the x-label with ax1\n",
        "  p2=ax2.plot(accuracy_history, color=color, label=\"Accuracy\")\n",
        "  ax2.tick_params(axis='y', labelcolor=color)\n",
        "  ax2.yaxis.set_major_formatter(plt.FuncFormatter(lambda y, _: f'{y:.0%}'))\n",
        "  ax2.grid()\n",
        "  ax1.xaxis.grid(True)\n",
        "\n",
        "  # Combine the legends from ax1 and ax2\n",
        "  lines, labels_ = ax1.get_legend_handles_labels()\n",
        "  lines2, labels2 = ax2.get_legend_handles_labels()\n",
        "  ax2.legend(lines + lines2, labels_ + labels2, loc='best')\n",
        "\n",
        "  fig.tight_layout()  # otherwise the right y-label is slightly clipped\n",
        "  plt.title(title)\n",
        "  plt.show()\n",
        "\n",
        "loss_history = history.history['loss']\n",
        "accuracy_history = history.history['accuracy']\n",
        "val_loss_history = history.history['loss']\n",
        "val_accuracy_history = history.history['val_accuracy']\n",
        "\n",
        "pair_plot(loss_history, accuracy_history, \"Loss / Accuracy (train)\")\n",
        "pair_plot(val_loss_history, val_accuracy_history, \"Loss / Accuracy (test validation)\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "0HJhHc2Z7nB6",
        "outputId": "1f3ac3f5-dec2-4b94-8b91-ddc61fa4aa24"
      },
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 2 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 2 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "test_pred = model.predict(x_test, batch_size=batch_size, use_multiprocessing=True)\n",
        "test_pred.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "G7sxO7L4-eH4",
        "outputId": "8672e8f2-0632-4969-c730-b5940307571b"
      },
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "23/23 [==============================] - 0s 11ms/step\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(10000, 10)"
            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def summarize(histories):\n",
        "\n",
        "  for i in range(len(histories)):\n",
        "    # plot loss\n",
        "    plt.figure(figsize=(12,8))\n",
        "    plt.subplot(2, 1, 1)\n",
        "    plt.title('Cross Entropy Loss')\n",
        "    plt.plot(histories[i].history['loss'], color='blue', label='train')\n",
        "    plt.plot(histories[i].history['val_loss'], color='orange', label='test')\n",
        "    axis = plt.gca()\n",
        "    axis.xaxis.set_major_formatter(plt.FuncFormatter(lambda x, _: int((x + 1))))\n",
        "    axis.xaxis.set_major_locator(MultipleLocator(1))\n",
        "    plt.xlabel('Epoch')\n",
        "    plt.ylabel('Loss')\n",
        "    plt.legend()\n",
        "    plt.grid()\n",
        "    #plt.show()\n",
        "    plt.tight_layout(pad=3.0)\n",
        "    # plot accuracy\n",
        "    #plt.figure(figsize=(12,8))\n",
        "    plt.subplot(2, 1, 2)\n",
        "    plt.title('Classification Accuracy')\n",
        "    plt.plot(histories[i].history['accuracy'], color='blue', label='train')\n",
        "    plt.plot(histories[i].history['val_accuracy'], color='orange', label='test')\n",
        "    axis = plt.gca()\n",
        "    axis.xaxis.set_major_formatter(plt.FuncFormatter(lambda x, _: int((x + 1))))\n",
        "    axis.xaxis.set_major_locator(MultipleLocator(1))\n",
        "    axis.yaxis.set_major_formatter(plt.FuncFormatter(lambda y, _: f'{y:.0%}'))\n",
        "    plt.legend()\n",
        "    plt.xlabel('Epoch')\n",
        "    plt.ylabel('Accuracy')\n",
        "    plt.grid()\n",
        "    plt.show()\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "summarize([history])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 796
        },
        "id": "y-TIQRCNsEcE",
        "outputId": "094591fe-0e6a-4f1c-bd3f-fb3b9c2bdaf0"
      },
      "execution_count": 67,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x800 with 2 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "test_pred_values = tf.math.argmax(test_pred, axis=1)"
      ],
      "metadata": {
        "id": "FCDJQiZA_OU3"
      },
      "execution_count": 55,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "target_names = [ f\"{i} - {labels[i]:11}\" for i in range(0, num_classes)]\n",
        "print(classification_report(y_test, test_pred_values, target_names=target_names))\n",
        "cr = classification_report(y_test, test_pred_values, target_names=target_names, output_dict=True)\n",
        "print(cr[\"accuracy\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "e7NK7-KW-IwX",
        "outputId": "4d34ef82-3986-4648-bbe3-07b5181dae33"
      },
      "execution_count": 68,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                 precision    recall  f1-score   support\n",
            "\n",
            "0 - T-shirt/top       0.84      0.84      0.84      1000\n",
            "1 - Trouser           0.98      0.97      0.98      1000\n",
            "2 - Pullover          0.81      0.81      0.81      1000\n",
            "3 - Dress             0.87      0.90      0.88      1000\n",
            "4 - Coat              0.79      0.82      0.81      1000\n",
            "5 - Sandal            0.95      0.97      0.96      1000\n",
            "6 - Shirt             0.71      0.69      0.70      1000\n",
            "7 - Sneaker           0.95      0.94      0.94      1000\n",
            "8 - Bag               0.99      0.95      0.97      1000\n",
            "9 - Ankle boot        0.96      0.95      0.96      1000\n",
            "\n",
            "       accuracy                           0.88     10000\n",
            "      macro avg       0.88      0.88      0.88     10000\n",
            "   weighted avg       0.88      0.88      0.88     10000\n",
            "\n",
            "0.8849\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "confusion_matrix(y_test, test_pred_values)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cVv2jYTs_mEq",
        "outputId": "0b3ff28b-1610-42a5-dfd8-1d5b4433a31b"
      },
      "execution_count": 69,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[844,   4,  15,  30,   6,   1,  96,   0,   4,   0],\n",
              "       [  2, 974,   0,  16,   4,   0,   4,   0,   0,   0],\n",
              "       [ 10,   0, 807,  16,  94,   0,  73,   0,   0,   0],\n",
              "       [ 18,  12,  11, 895,  35,   0,  26,   0,   3,   0],\n",
              "       [  0,   1,  83,  33, 821,   0,  62,   0,   0,   0],\n",
              "       [  0,   0,   0,   1,   0, 972,   0,  14,   1,  12],\n",
              "       [129,   1,  76,  35,  67,   0, 687,   0,   5,   0],\n",
              "       [  0,   0,   0,   0,   0,  35,   0, 942,   0,  23],\n",
              "       [  7,   2,   3,   5,   7,   4,  13,   5, 954,   0],\n",
              "       [  0,   0,   0,   0,   0,  11,   1,  35,   0, 953]])"
            ]
          },
          "metadata": {},
          "execution_count": 69
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ConfusionMatrixDisplay.from_predictions(y_test, test_pred_values)\n",
        "plt.show()\n",
        "print(list(map(lambda x: x.strip(),target_names)))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 467
        },
        "id": "59lDgVPNB9sn",
        "outputId": "d94c7c1f-5d27-494f-9ed9-d343e1f34ff4"
      },
      "execution_count": 70,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['0 - T-shirt/top', '1 - Trouser', '2 - Pullover', '3 - Dress', '4 - Coat', '5 - Sandal', '6 - Shirt', '7 - Sneaker', '8 - Bag', '9 - Ankle boot']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Візуалізація прогнозу"
      ],
      "metadata": {
        "id": "thFtPJEF5lYY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "img_selected = 10\n",
        "random_img_idx = np.random.randint(0, x_test.shape[0], size=img_selected)\n",
        "\n",
        "\n",
        "# Plot the images\n",
        "colors = [(1, 1, 1), (1, 0, 0), (1, 0, 0)]  # white, red, red\n",
        "custom_cmap = plt.cm.colors.LinearSegmentedColormap.from_list(\"CustomRed\", colors, N=256)\n",
        "\n",
        "plt.figure(figsize=(16, 5))\n",
        "pred = 0\n",
        "for i, idx in enumerate(random_img_idx, start=1):\n",
        "    plt.subplot(1, img_selected, i)\n",
        "    correct = y_test[idx] == test_pred_values[idx]\n",
        "    pred += int(correct)\n",
        "    cmap = 'gray_r' if correct else custom_cmap\n",
        "    color = \"black\" if correct else \"red\"\n",
        "    plt.imshow(x_test[idx], cmap=cmap)\n",
        "    title = labels_uk[y_test[idx]] if correct else f'{labels_uk[y_test[idx]]}\\n[{labels_uk[test_pred_values[idx]]}]'\n",
        "    plt.title(title, color=color)\n",
        "    plt.axis('off')\n",
        "\n",
        "acc = pred/img_selected\n",
        "plt.suptitle(f\"Accuracy of selection: {acc:.2%}, Accuracy of test dataset: {results[1]:.2%}\")\n",
        "plt.subplots_adjust(top=2.2)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "Ef0LuUuCDtuv",
        "outputId": "23dc90ae-e26b-4b88-c690-652622891e9c"
      },
      "execution_count": 73,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x500 with 10 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}