ECG_HeartBeat_Categorization.ipynb

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      "cell_type": "markdown",
      "source": [
        "## Import Dependencies"
      ],
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      }
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      "execution_count": 37,
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        "id": "h7-uBb8trEXe"
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      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "import tensorflow as tf\n",
        "from tensorflow.keras.models import Sequential\n",
        "from tensorflow.keras.layers import GRU, LSTM, Dense, Dropout\n",
        "from tensorflow.keras.callbacks import EarlyStopping, ReduceLROnPlateau, ModelCheckpoint\n",
        "\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import classification_report, confusion_matrix\n",
        "from mlxtend.plotting import plot_confusion_matrix\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Fetch the datasets\n"
      ],
      "metadata": {
        "id": "P5ZSR8Ooscm7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "train_data = pd.read_csv('/content/mitbih_train.csv')\n",
        "test_data = pd.read_csv('/content/mitbih_test.csv')\n",
        "\n",
        "train_data.head()"
      ],
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        "outputId": "5461b22a-9250-4921-87bc-618fcbd8d47f"
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              "        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-614abb6e-1ad2-41b3-80bb-78ddaeb4bf86 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "train_data"
            }
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Data info"
      ],
      "metadata": {
        "id": "72B1zx4useIr"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# total samples\n",
        "(train_data.shape[0], test_data.shape[0])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yPd-jDePrsJY",
        "outputId": "60a26e81-1d99-4fa3-db6b-c847d247e4a9"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(87553, 21891)"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Null values\n",
        "(train_data.isna().sum().sum(), test_data.isna().sum().sum())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jKjNpLd0rxv-",
        "outputId": "d37c2ce2-fb5b-46f8-d912-7ae633df973a"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(0, 0)"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Duplicates\n",
        "(train_data.duplicated().sum(), test_data.duplicated().sum())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GKC5v5Yhr10K",
        "outputId": "a6d19ff9-d6f3-430e-8c91-21f6ea200536"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(0, 0)"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# No of classes and contents\n",
        "train_data.iloc[:, -1].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 272
        },
        "id": "xhrinySysP4Q",
        "outputId": "800237fb-cbf7-484a-fc67-a748d158c655"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.000000000000000000e+00.88\n",
              "0.0    72470\n",
              "4.0     6431\n",
              "2.0     5788\n",
              "1.0     2223\n",
              "3.0      641\n",
              "Name: count, dtype: int64"
            ],
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0.000000000000000000e+00.88</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0.0</th>\n",
              "      <td>72470</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4.0</th>\n",
              "      <td>6431</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2.0</th>\n",
              "      <td>5788</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1.0</th>\n",
              "      <td>2223</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3.0</th>\n",
              "      <td>641</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> int64</label>"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "test_classes = test_data.iloc[:, -1].unique()\n",
        "train_classes = train_data.iloc[:, -1].unique()"
      ],
      "metadata": {
        "id": "jvuFnIhBsWGV"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "labels = {\n",
        "    0: \"Normal\",\n",
        "    1: \"Artial Premature\",\n",
        "    2: \"Premature ventricular contraction\",\n",
        "    3: \"Fusion of ventricular and normal\",\n",
        "    4: \"Fusion of paced and normal\"\n",
        "}"
      ],
      "metadata": {
        "id": "9ExT59assYZ3"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Data Preprocessing"
      ],
      "metadata": {
        "id": "XJMgIJsgso0T"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Separate features and labels\n",
        "X_train = train_data.iloc[:, :-1].values\n",
        "y_train = train_data.iloc[:, -1].values\n",
        "\n",
        "X_test = test_data.iloc[:, :-1].values\n",
        "y_test = test_data.iloc[:, -1].values\n",
        "\n",
        "# Scaling the data\n",
        "scaler = MinMaxScaler()\n",
        "X_train_scaled = scaler.fit_transform(X_train)\n",
        "X_test_scaled = scaler.transform(X_test)\n",
        "\n",
        "# Define the number of samples\n",
        "n_test_samples = X_test_scaled.shape[0]\n",
        "\n",
        "# Split the training data\n",
        "X_val, X_test_new, y_val, y_test_new = train_test_split(X_test_scaled, y_test, test_size=0.5, random_state=42, stratify=y_test)\n",
        "\n",
        "# Reshape the data\n",
        "X_train_scaled = np.reshape(X_train_scaled, (X_train_scaled.shape[0], X_train_scaled.shape[1], 1))\n",
        "X_val = np.reshape(X_val, (X_val.shape[0], X_val.shape[1], 1))\n",
        "X_test_new = np.reshape(X_test_new, (X_test_new.shape[0], X_test_new.shape[1], 1))"
      ],
      "metadata": {
        "id": "-7Jn2XDxsiXi"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Model 1 | GRU"
      ],
      "metadata": {
        "id": "66nDGxrvtB-C"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model1 = Sequential()\n",
        "model1.add(GRU(128, input_shape=(X_train.shape[1], 1), return_sequences=True))\n",
        "model1.add(Dropout(0.2))\n",
        "model1.add(GRU(64))\n",
        "model1.add(Dropout(0.2))\n",
        "model1.add(Dense(5, activation='softmax'))"
      ],
      "metadata": {
        "id": "4DJKPxtHs0zI"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model1.compile(optimizer='adam',\n",
        "                  loss='sparse_categorical_crossentropy',\n",
        "                  metrics=['accuracy'])\n",
        "\n",
        "es = EarlyStopping(monitor=\"val_loss\",\n",
        "                    patience=3,\n",
        "                    restore_best_weights=True)\n",
        "\n",
        "reduce_lr = ReduceLROnPlateau(monitor='val_loss',\n",
        "                              factor=0.2,\n",
        "                              verbose=1,\n",
        "                              patience=2,\n",
        "                              min_lr=1e-6)\n",
        "\n",
        "model_checkpoint = ModelCheckpoint('model.keras',\n",
        "                                   monitor='val_loss',\n",
        "                                   save_best_only=True)"
      ],
      "metadata": {
        "id": "p8cfg9Gos80N"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "history1 = model1.fit(X_train_scaled, y_train,\n",
        "                            epochs=20,\n",
        "                            batch_size=64,\n",
        "                            validation_data=(X_val, y_val),\n",
        "                            callbacks= [es, reduce_lr, model_checkpoint])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CsQjeYO9tE3v",
        "outputId": "178f4387-a364-4314-b11f-a5695720b305"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/20\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m28s\u001b[0m 19ms/step - accuracy: 0.9299 - loss: 0.2883 - val_accuracy: 0.9506 - val_loss: 0.1995 - learning_rate: 0.0010\n",
            "Epoch 2/20\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m39s\u001b[0m 18ms/step - accuracy: 0.9503 - loss: 0.1886 - val_accuracy: 0.9609 - val_loss: 0.1536 - learning_rate: 0.0010\n",
            "Epoch 3/20\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m40s\u001b[0m 17ms/step - accuracy: 0.9585 - loss: 0.1570 - val_accuracy: 0.9654 - val_loss: 0.1395 - learning_rate: 0.0010\n",
            "Epoch 4/20\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 17ms/step - accuracy: 0.9647 - loss: 0.1320 - val_accuracy: 0.9672 - val_loss: 0.1328 - learning_rate: 0.0010\n",
            "Epoch 5/20\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 17ms/step - accuracy: 0.9705 - loss: 0.1103 - val_accuracy: 0.9688 - val_loss: 0.1191 - learning_rate: 0.0010\n",
            "Epoch 6/20\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 17ms/step - accuracy: 0.9730 - loss: 0.1022 - val_accuracy: 0.9727 - val_loss: 0.1035 - learning_rate: 0.0010\n",
            "Epoch 7/20\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m46s\u001b[0m 21ms/step - accuracy: 0.9753 - loss: 0.0922 - val_accuracy: 0.9710 - val_loss: 0.1025 - learning_rate: 0.0010\n",
            "Epoch 8/20\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m40s\u001b[0m 20ms/step - accuracy: 0.9772 - loss: 0.0829 - val_accuracy: 0.9741 - val_loss: 0.0922 - learning_rate: 0.0010\n",
            "Epoch 9/20\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m44s\u001b[0m 23ms/step - accuracy: 0.9788 - loss: 0.0783 - val_accuracy: 0.9762 - val_loss: 0.0835 - learning_rate: 0.0010\n",
            "Epoch 10/20\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m43s\u001b[0m 24ms/step - accuracy: 0.9795 - loss: 0.0746 - val_accuracy: 0.9771 - val_loss: 0.0862 - learning_rate: 0.0010\n",
            "Epoch 11/20\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m28s\u001b[0m 21ms/step - accuracy: 0.9802 - loss: 0.0710 - val_accuracy: 0.9790 - val_loss: 0.0741 - learning_rate: 0.0010\n",
            "Epoch 12/20\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m42s\u001b[0m 21ms/step - accuracy: 0.9812 - loss: 0.0677 - val_accuracy: 0.9772 - val_loss: 0.0800 - learning_rate: 0.0010\n",
            "Epoch 13/20\n",
            "\u001b[1m1367/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 16ms/step - accuracy: 0.9826 - loss: 0.0622\n",
            "Epoch 13: ReduceLROnPlateau reducing learning rate to 0.00020000000949949026.\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m24s\u001b[0m 17ms/step - accuracy: 0.9826 - loss: 0.0622 - val_accuracy: 0.9778 - val_loss: 0.0793 - learning_rate: 0.0010\n",
            "Epoch 14/20\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 17ms/step - accuracy: 0.9854 - loss: 0.0480 - val_accuracy: 0.9825 - val_loss: 0.0632 - learning_rate: 2.0000e-04\n",
            "Epoch 15/20\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 17ms/step - accuracy: 0.9882 - loss: 0.0401 - val_accuracy: 0.9836 - val_loss: 0.0612 - learning_rate: 2.0000e-04\n",
            "Epoch 16/20\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m25s\u001b[0m 18ms/step - accuracy: 0.9882 - loss: 0.0404 - val_accuracy: 0.9829 - val_loss: 0.0604 - learning_rate: 2.0000e-04\n",
            "Epoch 17/20\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m42s\u001b[0m 18ms/step - accuracy: 0.9892 - loss: 0.0374 - val_accuracy: 0.9826 - val_loss: 0.0618 - learning_rate: 2.0000e-04\n",
            "Epoch 18/20\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 16ms/step - accuracy: 0.9888 - loss: 0.0365\n",
            "Epoch 18: ReduceLROnPlateau reducing learning rate to 4.0000001899898055e-05.\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m23s\u001b[0m 17ms/step - accuracy: 0.9888 - loss: 0.0365 - val_accuracy: 0.9836 - val_loss: 0.0617 - learning_rate: 2.0000e-04\n",
            "Epoch 19/20\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 17ms/step - accuracy: 0.9900 - loss: 0.0334 - val_accuracy: 0.9841 - val_loss: 0.0612 - learning_rate: 4.0000e-05\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_test_pred_gru = model1.predict(X_test_new).argmax(axis=1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UOOjm4pDwp-K",
        "outputId": "f7e5989e-3bef-41f8-d4ea-14f56343bb37"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m343/343\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 6ms/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "gru_test_loss, gru_test_acc = model1.evaluate(X_test_new, y_test_new, verbose=0)\n",
        "print(f\"GRU Test Loss: {gru_test_loss:.4f}\")\n",
        "print(f\"GRU Test Accuracy: {gru_test_acc:.4f}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "P0NGfR9pwuRG",
        "outputId": "3f3ed972-33c8-4221-e7a0-363f3b4d8a01"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "GRU Test Loss: 0.0555\n",
            "GRU Test Accuracy: 0.9845\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "class_names = [labels[i] for i in range(len(labels))]"
      ],
      "metadata": {
        "id": "szkUdMl-xC7w"
      },
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "conf_matrix_gru = confusion_matrix(y_test_new, y_test_pred_gru)\n",
        "\n",
        "plot_confusion_matrix(conf_matrix_gru,\n",
        "                      class_names=class_names,\n",
        "                      show_normed=True,\n",
        "                      figsize=(8,6),\n",
        "                      colorbar=True)\n",
        "\n",
        "plt.title('GRU Confusion Matrix')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 727
        },
        "id": "RhwQuzfkw1Yg",
        "outputId": "cb96d8b9-3099-46c3-f675-e7c1649614dc"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(classification_report(y_test_new, y_test_pred_gru))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gRmnLl0g8oH1",
        "outputId": "eff6826f-78a2-4f04-bcee-b9fea54458fa"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "         0.0       0.99      0.99      0.99      9059\n",
            "         1.0       0.88      0.78      0.82       278\n",
            "         2.0       0.96      0.95      0.95       724\n",
            "         3.0       0.80      0.84      0.82        81\n",
            "         4.0       0.99      0.99      0.99       804\n",
            "\n",
            "    accuracy                           0.98     10946\n",
            "   macro avg       0.92      0.91      0.92     10946\n",
            "weighted avg       0.98      0.98      0.98     10946\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Model 2 | LSTM"
      ],
      "metadata": {
        "id": "mH7jsJEfxG2e"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model2 = Sequential()\n",
        "model2.add(LSTM(128, input_shape=(X_train.shape[1], 1), return_sequences=True))\n",
        "model2.add(Dropout(0.2))\n",
        "model2.add(LSTM(64))\n",
        "model2.add(Dropout(0.2))\n",
        "model2.add(Dense(5, activation='softmax'))"
      ],
      "metadata": {
        "id": "EfOmNVCdxIoN"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model2.compile(optimizer='adam',\n",
        "                   loss='sparse_categorical_crossentropy',\n",
        "                   metrics=['accuracy'])\n",
        "\n",
        "hisotry2 = model2.fit(X_train_scaled, y_train,\n",
        "                            epochs=10,\n",
        "                            batch_size=64,\n",
        "                            validation_data=(X_val, y_val),\n",
        "                            callbacks= [reduce_lr, model_checkpoint])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4vwCkCz4xOGg",
        "outputId": "da8bd81a-fe74-4f2b-abed-d67459c30121"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/10\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m26s\u001b[0m 18ms/step - accuracy: 0.8790 - loss: 0.4243 - val_accuracy: 0.9238 - val_loss: 0.3080 - learning_rate: 0.0010\n",
            "Epoch 2/10\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 18ms/step - accuracy: 0.8992 - loss: 0.3773 - val_accuracy: 0.9261 - val_loss: 0.3231 - learning_rate: 0.0010\n",
            "Epoch 3/10\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 18ms/step - accuracy: 0.9251 - loss: 0.2950 - val_accuracy: 0.9315 - val_loss: 0.2578 - learning_rate: 0.0010\n",
            "Epoch 4/10\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 18ms/step - accuracy: 0.9338 - loss: 0.2532 - val_accuracy: 0.9401 - val_loss: 0.2250 - learning_rate: 0.0010\n",
            "Epoch 5/10\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 18ms/step - accuracy: 0.9391 - loss: 0.2269 - val_accuracy: 0.9424 - val_loss: 0.2215 - learning_rate: 0.0010\n",
            "Epoch 6/10\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 18ms/step - accuracy: 0.9426 - loss: 0.2089 - val_accuracy: 0.9524 - val_loss: 0.1782 - learning_rate: 0.0010\n",
            "Epoch 7/10\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m26s\u001b[0m 19ms/step - accuracy: 0.9473 - loss: 0.1918 - val_accuracy: 0.9497 - val_loss: 0.1793 - learning_rate: 0.0010\n",
            "Epoch 8/10\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 19ms/step - accuracy: 0.9549 - loss: 0.1656 - val_accuracy: 0.9546 - val_loss: 0.1664 - learning_rate: 0.0010\n",
            "Epoch 9/10\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 19ms/step - accuracy: 0.9590 - loss: 0.1515 - val_accuracy: 0.9590 - val_loss: 0.1616 - learning_rate: 0.0010\n",
            "Epoch 10/10\n",
            "\u001b[1m1369/1369\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m40s\u001b[0m 18ms/step - accuracy: 0.9586 - loss: 0.1537 - val_accuracy: 0.9640 - val_loss: 0.1399 - learning_rate: 0.0010\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_test_pred_lstm = model2.predict(X_test_new).argmax(axis=1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L2TEacsxylzP",
        "outputId": "942666bd-0f59-4b3f-b85c-d0ce1119e7fa"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m343/343\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 6ms/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "lstm_test_loss, lstm_test_acc = model2.evaluate(X_test_new, y_test_new, verbose=0)\n",
        "print(f\"LSTM Test Loss: {lstm_test_loss:.4f}\")\n",
        "print(f\"LSTM Test Accuracy: {lstm_test_acc:.4f}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4EOXbk6Byrqq",
        "outputId": "06a4f53d-d8a0-4742-fde3-650ad6560a72"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "LSTM Test Loss: 0.1297\n",
            "LSTM Test Accuracy: 0.9667\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "conf_matrix_lstm = confusion_matrix(y_test_new, y_test_pred_lstm)\n",
        "\n",
        "plot_confusion_matrix(conf_matrix_lstm,\n",
        "                      class_names=class_names,\n",
        "                      show_normed=True,\n",
        "                      figsize=(8,6),\n",
        "                      colorbar=True)\n",
        "\n",
        "plt.title('LSTM Confusion Matrix')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 727
        },
        "id": "VBKQuvTfyrFm",
        "outputId": "145c6be2-9e88-49a3-b042-641e03ab6777"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(classification_report(y_test_new, y_test_pred_lstm))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DCYpztu18sp0",
        "outputId": "cacd4d6e-537a-4484-dbeb-f79410e735e8"
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "         0.0       0.97      0.99      0.98      9059\n",
            "         1.0       0.85      0.54      0.66       278\n",
            "         2.0       0.89      0.91      0.90       724\n",
            "         3.0       0.69      0.51      0.59        81\n",
            "         4.0       0.99      0.93      0.96       804\n",
            "\n",
            "    accuracy                           0.97     10946\n",
            "   macro avg       0.88      0.78      0.82     10946\n",
            "weighted avg       0.97      0.97      0.96     10946\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Model Comparison"
      ],
      "metadata": {
        "id": "HdLKNDgG71H5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "accuracy1 = history1.history['accuracy']\n",
        "loss1 = history1.history['loss']\n",
        "accuracy2 = hisotry2.history['accuracy']\n",
        "loss2 = hisotry2.history['loss']\n",
        "\n",
        "epochs1 = range(1, len(accuracy1) + 1)\n",
        "epochs2 = range(1, len(accuracy2) + 1)\n",
        "\n",
        "plt.figure(figsize=(12, 5))\n",
        "\n",
        "plt.subplot(1, 2, 1)\n",
        "plt.plot(epochs1, accuracy1, 'b', label='Model 1 (GRU) Accuracy')\n",
        "plt.plot(epochs2, accuracy2, 'r', label='Model 2 (Bi-LSTM) Accuracy')\n",
        "plt.title('Training Accuracy Comparison')\n",
        "plt.xlabel('Epochs')\n",
        "plt.ylabel('Accuracy')\n",
        "plt.legend()\n",
        "\n",
        "plt.subplot(1, 2, 2)\n",
        "plt.plot(epochs1, loss1, 'b', label='Model 1 (GRU) Loss')\n",
        "plt.plot(epochs2, loss2, 'r', label='Model 2 (Bi-LSTM) Loss')\n",
        "plt.title('Training Loss Comparison')\n",
        "plt.xlabel('Epochs')\n",
        "plt.ylabel('Loss')\n",
        "plt.legend()\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 527
        },
        "id": "-JJC9V5ky1hp",
        "outputId": "5c1e2221-06b7-42fa-873d-264add40fd46"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x500 with 2 Axes>"
            ],
            "image/png": 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          "metadata": {}
        }
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    }
  ]
}