diff --git a/lstm_model_2.ipynb b/lstm_model_2.ipynb
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@@ -0,0 +1,837 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
+    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5",
+    "execution": {
+     "iopub.execute_input": "2025-10-21T17:37:44.526303Z",
+     "iopub.status.busy": "2025-10-21T17:37:44.526132Z",
+     "iopub.status.idle": "2025-10-21T17:38:00.962782Z",
+     "shell.execute_reply": "2025-10-21T17:38:00.962190Z",
+     "shell.execute_reply.started": "2025-10-21T17:37:44.526286Z"
+    },
+    "trusted": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2025-10-21 17:37:49.128593: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:477] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
+      "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
+      "E0000 00:00:1761068269.369935      37 cuda_dnn.cc:8310] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
+      "E0000 00:00:1761068269.441141      37 cuda_blas.cc:1418] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n"
+     ]
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.metrics import (classification_report, confusion_matrix,\n",
+    "                            accuracy_score, precision_recall_fscore_support)\n",
+    "import tensorflow as tf\n",
+    "from tensorflow import keras\n",
+    "from tensorflow.keras import layers, models, callbacks\n",
+    "from tensorflow.keras.utils import plot_model\n",
+    "\n",
+    "# Set random seeds for reproducibility\n",
+    "np.random.seed(42)\n",
+    "tf.random.set_seed(42)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-10-21T17:38:13.505953Z",
+     "iopub.status.busy": "2025-10-21T17:38:13.505424Z",
+     "iopub.status.idle": "2025-10-21T17:38:15.747418Z",
+     "shell.execute_reply": "2025-10-21T17:38:15.746796Z",
+     "shell.execute_reply.started": "2025-10-21T17:38:13.505929Z"
+    },
+    "trusted": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Loading preprocessed data from Kaggle Input...\n",
+      "Data shape: X=(112559, 250, 1), y=(112559, 5)\n",
+      "Classes: ['F' 'N' 'Q' 'S' 'V']\n"
+     ]
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "# Change the path to point to the Kaggle input directory if on Kaggle.\n",
+    "KAGGLE_DATA_PATH = '/kaggle/input/ecg-data1/ecg_mitdb_processed.npz'\n",
+    "\n",
+    "print(\"Loading preprocessed data from Kaggle Input...\")\n",
+    "data = np.load(KAGGLE_DATA_PATH)\n",
+    "X = data['X']\n",
+    "y = data['y']\n",
+    "label_names = data['label_names']\n",
+    "\n",
+    "print(f\"Data shape: X={X.shape}, y={y.shape}\")\n",
+    "print(f\"Classes: {label_names}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-10-21T17:38:21.820661Z",
+     "iopub.status.busy": "2025-10-21T17:38:21.820074Z",
+     "iopub.status.idle": "2025-10-21T17:38:22.063144Z",
+     "shell.execute_reply": "2025-10-21T17:38:22.062490Z",
+     "shell.execute_reply.started": "2025-10-21T17:38:21.820624Z"
+    },
+    "trusted": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Splitting data...\n",
+      "Train set: 72037 samples\n",
+      "Validation set: 18010 samples\n",
+      "Test set: 22512 samples\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"\\nSplitting data...\")\n",
+    "# First split: 80% train+val, 20% test\n",
+    "X_temp, X_test, y_temp, y_test = train_test_split(\n",
+    "    X, y, test_size=0.2, random_state=42, stratify=y.argmax(axis=1)\n",
+    ")\n",
+    "\n",
+    "# Second split: 80% train, 20% validation (of the 80%)\n",
+    "X_train, X_val, y_train, y_val = train_test_split(\n",
+    "    X_temp, y_temp, test_size=0.2, random_state=42, stratify=y_temp.argmax(axis=1)\n",
+    ")\n",
+    "\n",
+    "print(f\"Train set: {X_train.shape[0]} samples\")\n",
+    "print(f\"Validation set: {X_val.shape[0]} samples\")\n",
+    "print(f\"Test set: {X_test.shape[0]} samples\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-10-21T17:38:24.638819Z",
+     "iopub.status.busy": "2025-10-21T17:38:24.638292Z",
+     "iopub.status.idle": "2025-10-21T17:38:27.158927Z",
+     "shell.execute_reply": "2025-10-21T17:38:27.158299Z",
+     "shell.execute_reply.started": "2025-10-21T17:38:24.638799Z"
+    },
+    "trusted": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Building model...\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "I0000 00:00:1761068305.632002      37 gpu_device.cc:2022] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 13942 MB memory:  -> device: 0, name: Tesla T4, pci bus id: 0000:00:04.0, compute capability: 7.5\n",
+      "I0000 00:00:1761068305.632757      37 gpu_device.cc:2022] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13942 MB memory:  -> device: 1, name: Tesla T4, pci bus id: 0000:00:05.0, compute capability: 7.5\n",
+      "/usr/local/lib/python3.11/dist-packages/keras/src/layers/rnn/bidirectional.py:107: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n",
+      "  super().__init__(**kwargs)\n"
+     ]
+    }
+   ],
+   "source": [
+    "def create_lstm_model(input_shape, num_classes):\n",
+    "    \"\"\"\n",
+    "    Create a Bidirectional LSTM model for ECG classification.\n",
+    "    \"\"\"\n",
+    "    model = models.Sequential([\n",
+    "        # First Bi-LSTM layer with return sequences\n",
+    "        layers.Bidirectional(\n",
+    "            layers.LSTM(128, return_sequences=True),\n",
+    "            input_shape=input_shape\n",
+    "        ),\n",
+    "        layers.Dropout(0.4),\n",
+    "        layers.BatchNormalization(),\n",
+    "\n",
+    "        # Second Bi-LSTM layer\n",
+    "        layers.Bidirectional(layers.LSTM(64)),\n",
+    "        layers.Dropout(0.4),\n",
+    "        layers.BatchNormalization(),\n",
+    "\n",
+    "        # Dense layers for classification\n",
+    "        layers.Dense(64, activation='relu'),\n",
+    "        layers.Dropout(0.4),\n",
+    "        layers.Dense(32, activation='relu'),\n",
+    "        layers.Dropout(0.2),\n",
+    "\n",
+    "        # Output layer\n",
+    "        layers.Dense(num_classes, activation='softmax')\n",
+    "    ])\n",
+    "    return model\n",
+    "\n",
+    "# --- Model Configuration ---\n",
+    "\n",
+    "input_shape = (X_train.shape[1], X_train.shape[2])  # (250, 1)\n",
+    "num_classes = y_train.shape[1]\n",
+    "\n",
+    "# Callbacks for smart training\n",
+    "early_stop = keras.callbacks.EarlyStopping(\n",
+    "    monitor='val_loss',\n",
+    "    patience=15,\n",
+    "    restore_best_weights=True\n",
+    ")\n",
+    "\n",
+    "reduce_lr = keras.callbacks.ReduceLROnPlateau(\n",
+    "    monitor='val_loss',\n",
+    "    factor=0.2,\n",
+    "    patience=5,\n",
+    "    min_lr=1e-6\n",
+    ")\n",
+    "\n",
+    "# --- Create, Compile, and Train Model ---\n",
+    "\n",
+    "print(\"\\nBuilding model...\")\n",
+    "model = create_lstm_model(input_shape, num_classes)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-10-21T17:38:32.911332Z",
+     "iopub.status.busy": "2025-10-21T17:38:32.911063Z",
+     "iopub.status.idle": "2025-10-21T17:38:32.934255Z",
+     "shell.execute_reply": "2025-10-21T17:38:32.933655Z",
+     "shell.execute_reply.started": "2025-10-21T17:38:32.911312Z"
+    },
+    "trusted": true
+   },
+   "outputs": [],
+   "source": [
+    "model.compile(\n",
+    "    optimizer=keras.optimizers.Adam(learning_rate=0.001),\n",
+    "    loss='categorical_crossentropy',\n",
+    "    metrics=['accuracy', keras.metrics.Precision(), keras.metrics.Recall()]\n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-10-21T17:38:34.946739Z",
+     "iopub.status.busy": "2025-10-21T17:38:34.946146Z",
+     "iopub.status.idle": "2025-10-21T18:11:43.295377Z",
+     "shell.execute_reply": "2025-10-21T18:11:43.294790Z",
+     "shell.execute_reply.started": "2025-10-21T17:38:34.946716Z"
+    },
+    "trusted": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Training model...\n",
+      "Epoch 1/100\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "I0000 00:00:1761068322.600633      99 cuda_dnn.cc:529] Loaded cuDNN version 90300\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m40s\u001b[0m 108ms/step - accuracy: 0.7420 - loss: 0.7885 - precision: 0.8033 - recall: 0.6606 - val_accuracy: 0.8185 - val_loss: 0.5188 - val_precision: 0.8351 - val_recall: 0.7974 - learning_rate: 0.0010\n",
+      "Epoch 2/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m30s\u001b[0m 106ms/step - accuracy: 0.8748 - loss: 0.4120 - precision: 0.8981 - recall: 0.8444 - val_accuracy: 0.9257 - val_loss: 0.2525 - val_precision: 0.9509 - val_recall: 0.9002 - learning_rate: 0.0010\n",
+      "Epoch 3/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 109ms/step - accuracy: 0.9149 - loss: 0.2979 - precision: 0.9357 - recall: 0.8928 - val_accuracy: 0.9458 - val_loss: 0.1848 - val_precision: 0.9629 - val_recall: 0.9287 - learning_rate: 0.0010\n",
+      "Epoch 4/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m32s\u001b[0m 112ms/step - accuracy: 0.9319 - loss: 0.2445 - precision: 0.9481 - recall: 0.9162 - val_accuracy: 0.9394 - val_loss: 0.1828 - val_precision: 0.9536 - val_recall: 0.9244 - learning_rate: 0.0010\n",
+      "Epoch 5/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m32s\u001b[0m 112ms/step - accuracy: 0.9389 - loss: 0.2193 - precision: 0.9535 - recall: 0.9254 - val_accuracy: 0.9562 - val_loss: 0.1443 - val_precision: 0.9679 - val_recall: 0.9457 - learning_rate: 0.0010\n",
+      "Epoch 6/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9403 - loss: 0.2131 - precision: 0.9545 - recall: 0.9275 - val_accuracy: 0.9582 - val_loss: 0.1355 - val_precision: 0.9676 - val_recall: 0.9511 - learning_rate: 0.0010\n",
+      "Epoch 7/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 112ms/step - accuracy: 0.9496 - loss: 0.1785 - precision: 0.9613 - recall: 0.9397 - val_accuracy: 0.9605 - val_loss: 0.1286 - val_precision: 0.9711 - val_recall: 0.9518 - learning_rate: 0.0010\n",
+      "Epoch 8/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 112ms/step - accuracy: 0.9507 - loss: 0.1786 - precision: 0.9612 - recall: 0.9407 - val_accuracy: 0.9478 - val_loss: 0.1989 - val_precision: 0.9594 - val_recall: 0.9366 - learning_rate: 0.0010\n",
+      "Epoch 9/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9510 - loss: 0.1795 - precision: 0.9613 - recall: 0.9421 - val_accuracy: 0.9651 - val_loss: 0.1149 - val_precision: 0.9715 - val_recall: 0.9600 - learning_rate: 0.0010\n",
+      "Epoch 10/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9596 - loss: 0.1416 - precision: 0.9676 - recall: 0.9527 - val_accuracy: 0.9642 - val_loss: 0.1199 - val_precision: 0.9715 - val_recall: 0.9589 - learning_rate: 0.0010\n",
+      "Epoch 11/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 112ms/step - accuracy: 0.9624 - loss: 0.1321 - precision: 0.9698 - recall: 0.9567 - val_accuracy: 0.9652 - val_loss: 0.1216 - val_precision: 0.9717 - val_recall: 0.9601 - learning_rate: 0.0010\n",
+      "Epoch 12/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9633 - loss: 0.1312 - precision: 0.9703 - recall: 0.9562 - val_accuracy: 0.9721 - val_loss: 0.0953 - val_precision: 0.9775 - val_recall: 0.9675 - learning_rate: 0.0010\n",
+      "Epoch 13/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9652 - loss: 0.1252 - precision: 0.9719 - recall: 0.9594 - val_accuracy: 0.9681 - val_loss: 0.1084 - val_precision: 0.9751 - val_recall: 0.9639 - learning_rate: 0.0010\n",
+      "Epoch 14/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9661 - loss: 0.1239 - precision: 0.9715 - recall: 0.9597 - val_accuracy: 0.9752 - val_loss: 0.0859 - val_precision: 0.9793 - val_recall: 0.9713 - learning_rate: 0.0010\n",
+      "Epoch 15/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9688 - loss: 0.1146 - precision: 0.9742 - recall: 0.9637 - val_accuracy: 0.9703 - val_loss: 0.1049 - val_precision: 0.9753 - val_recall: 0.9663 - learning_rate: 0.0010\n",
+      "Epoch 16/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9708 - loss: 0.1065 - precision: 0.9752 - recall: 0.9657 - val_accuracy: 0.9776 - val_loss: 0.0825 - val_precision: 0.9812 - val_recall: 0.9726 - learning_rate: 0.0010\n",
+      "Epoch 17/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9712 - loss: 0.1016 - precision: 0.9757 - recall: 0.9663 - val_accuracy: 0.9779 - val_loss: 0.0780 - val_precision: 0.9808 - val_recall: 0.9748 - learning_rate: 0.0010\n",
+      "Epoch 18/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9714 - loss: 0.1012 - precision: 0.9752 - recall: 0.9671 - val_accuracy: 0.9778 - val_loss: 0.0808 - val_precision: 0.9807 - val_recall: 0.9737 - learning_rate: 0.0010\n",
+      "Epoch 19/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9716 - loss: 0.1032 - precision: 0.9759 - recall: 0.9671 - val_accuracy: 0.9756 - val_loss: 0.0870 - val_precision: 0.9807 - val_recall: 0.9713 - learning_rate: 0.0010\n",
+      "Epoch 20/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9730 - loss: 0.0973 - precision: 0.9770 - recall: 0.9698 - val_accuracy: 0.9753 - val_loss: 0.0908 - val_precision: 0.9780 - val_recall: 0.9727 - learning_rate: 0.0010\n",
+      "Epoch 21/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9741 - loss: 0.0904 - precision: 0.9780 - recall: 0.9706 - val_accuracy: 0.9751 - val_loss: 0.0878 - val_precision: 0.9790 - val_recall: 0.9723 - learning_rate: 0.0010\n",
+      "Epoch 22/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9741 - loss: 0.0961 - precision: 0.9770 - recall: 0.9707 - val_accuracy: 0.9788 - val_loss: 0.0774 - val_precision: 0.9810 - val_recall: 0.9761 - learning_rate: 0.0010\n",
+      "Epoch 23/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9740 - loss: 0.0885 - precision: 0.9778 - recall: 0.9712 - val_accuracy: 0.9727 - val_loss: 0.1036 - val_precision: 0.9756 - val_recall: 0.9700 - learning_rate: 0.0010\n",
+      "Epoch 24/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9751 - loss: 0.0873 - precision: 0.9780 - recall: 0.9723 - val_accuracy: 0.9816 - val_loss: 0.0633 - val_precision: 0.9836 - val_recall: 0.9796 - learning_rate: 0.0010\n",
+      "Epoch 25/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9775 - loss: 0.0802 - precision: 0.9803 - recall: 0.9749 - val_accuracy: 0.9814 - val_loss: 0.0656 - val_precision: 0.9838 - val_recall: 0.9792 - learning_rate: 0.0010\n",
+      "Epoch 26/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9774 - loss: 0.0799 - precision: 0.9803 - recall: 0.9746 - val_accuracy: 0.9797 - val_loss: 0.0684 - val_precision: 0.9821 - val_recall: 0.9786 - learning_rate: 0.0010\n",
+      "Epoch 27/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9773 - loss: 0.0794 - precision: 0.9801 - recall: 0.9750 - val_accuracy: 0.9815 - val_loss: 0.0633 - val_precision: 0.9830 - val_recall: 0.9804 - learning_rate: 0.0010\n",
+      "Epoch 28/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9765 - loss: 0.0834 - precision: 0.9794 - recall: 0.9740 - val_accuracy: 0.9808 - val_loss: 0.0683 - val_precision: 0.9826 - val_recall: 0.9792 - learning_rate: 0.0010\n",
+      "Epoch 29/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9771 - loss: 0.0809 - precision: 0.9797 - recall: 0.9747 - val_accuracy: 0.9817 - val_loss: 0.0624 - val_precision: 0.9842 - val_recall: 0.9801 - learning_rate: 0.0010\n",
+      "Epoch 30/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9794 - loss: 0.0735 - precision: 0.9820 - recall: 0.9775 - val_accuracy: 0.9733 - val_loss: 0.0848 - val_precision: 0.9766 - val_recall: 0.9712 - learning_rate: 0.0010\n",
+      "Epoch 31/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9787 - loss: 0.0763 - precision: 0.9810 - recall: 0.9765 - val_accuracy: 0.9771 - val_loss: 0.0795 - val_precision: 0.9790 - val_recall: 0.9760 - learning_rate: 0.0010\n",
+      "Epoch 32/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9776 - loss: 0.0781 - precision: 0.9804 - recall: 0.9758 - val_accuracy: 0.9821 - val_loss: 0.0603 - val_precision: 0.9844 - val_recall: 0.9804 - learning_rate: 0.0010\n",
+      "Epoch 33/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9795 - loss: 0.0713 - precision: 0.9818 - recall: 0.9773 - val_accuracy: 0.9800 - val_loss: 0.0723 - val_precision: 0.9819 - val_recall: 0.9782 - learning_rate: 0.0010\n",
+      "Epoch 34/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9794 - loss: 0.0728 - precision: 0.9814 - recall: 0.9775 - val_accuracy: 0.9827 - val_loss: 0.0665 - val_precision: 0.9834 - val_recall: 0.9818 - learning_rate: 0.0010\n",
+      "Epoch 35/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9796 - loss: 0.0743 - precision: 0.9815 - recall: 0.9776 - val_accuracy: 0.9701 - val_loss: 0.1098 - val_precision: 0.9725 - val_recall: 0.9665 - learning_rate: 0.0010\n",
+      "Epoch 36/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9780 - loss: 0.0797 - precision: 0.9804 - recall: 0.9754 - val_accuracy: 0.9831 - val_loss: 0.0575 - val_precision: 0.9850 - val_recall: 0.9816 - learning_rate: 0.0010\n",
+      "Epoch 37/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9800 - loss: 0.0688 - precision: 0.9822 - recall: 0.9780 - val_accuracy: 0.9831 - val_loss: 0.0612 - val_precision: 0.9841 - val_recall: 0.9814 - learning_rate: 0.0010\n",
+      "Epoch 38/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9809 - loss: 0.0657 - precision: 0.9827 - recall: 0.9792 - val_accuracy: 0.9841 - val_loss: 0.0580 - val_precision: 0.9849 - val_recall: 0.9833 - learning_rate: 0.0010\n",
+      "Epoch 39/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9821 - loss: 0.0622 - precision: 0.9839 - recall: 0.9808 - val_accuracy: 0.9834 - val_loss: 0.0585 - val_precision: 0.9845 - val_recall: 0.9828 - learning_rate: 0.0010\n",
+      "Epoch 40/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9818 - loss: 0.0647 - precision: 0.9837 - recall: 0.9802 - val_accuracy: 0.9802 - val_loss: 0.0716 - val_precision: 0.9820 - val_recall: 0.9785 - learning_rate: 0.0010\n",
+      "Epoch 41/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9818 - loss: 0.0637 - precision: 0.9837 - recall: 0.9801 - val_accuracy: 0.9850 - val_loss: 0.0503 - val_precision: 0.9861 - val_recall: 0.9841 - learning_rate: 0.0010\n",
+      "Epoch 42/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9814 - loss: 0.0628 - precision: 0.9830 - recall: 0.9796 - val_accuracy: 0.9809 - val_loss: 0.0715 - val_precision: 0.9821 - val_recall: 0.9794 - learning_rate: 0.0010\n",
+      "Epoch 43/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m32s\u001b[0m 112ms/step - accuracy: 0.9817 - loss: 0.0659 - precision: 0.9835 - recall: 0.9803 - val_accuracy: 0.9831 - val_loss: 0.0611 - val_precision: 0.9847 - val_recall: 0.9823 - learning_rate: 0.0010\n",
+      "Epoch 44/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m32s\u001b[0m 112ms/step - accuracy: 0.9828 - loss: 0.0611 - precision: 0.9845 - recall: 0.9814 - val_accuracy: 0.9848 - val_loss: 0.0538 - val_precision: 0.9858 - val_recall: 0.9836 - learning_rate: 0.0010\n",
+      "Epoch 45/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 112ms/step - accuracy: 0.9827 - loss: 0.0581 - precision: 0.9847 - recall: 0.9815 - val_accuracy: 0.9855 - val_loss: 0.0519 - val_precision: 0.9866 - val_recall: 0.9845 - learning_rate: 0.0010\n",
+      "Epoch 46/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 112ms/step - accuracy: 0.9834 - loss: 0.0567 - precision: 0.9849 - recall: 0.9817 - val_accuracy: 0.9858 - val_loss: 0.0524 - val_precision: 0.9866 - val_recall: 0.9848 - learning_rate: 0.0010\n",
+      "Epoch 47/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 112ms/step - accuracy: 0.9855 - loss: 0.0477 - precision: 0.9874 - recall: 0.9842 - val_accuracy: 0.9879 - val_loss: 0.0457 - val_precision: 0.9882 - val_recall: 0.9868 - learning_rate: 2.0000e-04\n",
+      "Epoch 48/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 112ms/step - accuracy: 0.9877 - loss: 0.0427 - precision: 0.9888 - recall: 0.9866 - val_accuracy: 0.9883 - val_loss: 0.0456 - val_precision: 0.9893 - val_recall: 0.9875 - learning_rate: 2.0000e-04\n",
+      "Epoch 49/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m32s\u001b[0m 112ms/step - accuracy: 0.9888 - loss: 0.0397 - precision: 0.9897 - recall: 0.9879 - val_accuracy: 0.9879 - val_loss: 0.0461 - val_precision: 0.9887 - val_recall: 0.9876 - learning_rate: 2.0000e-04\n",
+      "Epoch 50/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m32s\u001b[0m 112ms/step - accuracy: 0.9888 - loss: 0.0386 - precision: 0.9899 - recall: 0.9880 - val_accuracy: 0.9875 - val_loss: 0.0466 - val_precision: 0.9881 - val_recall: 0.9867 - learning_rate: 2.0000e-04\n",
+      "Epoch 51/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m32s\u001b[0m 112ms/step - accuracy: 0.9887 - loss: 0.0380 - precision: 0.9898 - recall: 0.9878 - val_accuracy: 0.9885 - val_loss: 0.0469 - val_precision: 0.9891 - val_recall: 0.9880 - learning_rate: 2.0000e-04\n",
+      "Epoch 52/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m32s\u001b[0m 112ms/step - accuracy: 0.9886 - loss: 0.0376 - precision: 0.9896 - recall: 0.9877 - val_accuracy: 0.9885 - val_loss: 0.0466 - val_precision: 0.9893 - val_recall: 0.9882 - learning_rate: 2.0000e-04\n",
+      "Epoch 53/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 112ms/step - accuracy: 0.9902 - loss: 0.0338 - precision: 0.9910 - recall: 0.9891 - val_accuracy: 0.9880 - val_loss: 0.0468 - val_precision: 0.9889 - val_recall: 0.9874 - learning_rate: 2.0000e-04\n",
+      "Epoch 54/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m32s\u001b[0m 112ms/step - accuracy: 0.9896 - loss: 0.0360 - precision: 0.9911 - recall: 0.9890 - val_accuracy: 0.9887 - val_loss: 0.0461 - val_precision: 0.9894 - val_recall: 0.9881 - learning_rate: 4.0000e-05\n",
+      "Epoch 55/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m32s\u001b[0m 112ms/step - accuracy: 0.9902 - loss: 0.0324 - precision: 0.9911 - recall: 0.9895 - val_accuracy: 0.9886 - val_loss: 0.0464 - val_precision: 0.9895 - val_recall: 0.9881 - learning_rate: 4.0000e-05\n",
+      "Epoch 56/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m32s\u001b[0m 112ms/step - accuracy: 0.9904 - loss: 0.0319 - precision: 0.9916 - recall: 0.9895 - val_accuracy: 0.9885 - val_loss: 0.0467 - val_precision: 0.9893 - val_recall: 0.9882 - learning_rate: 4.0000e-05\n",
+      "Epoch 57/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m32s\u001b[0m 112ms/step - accuracy: 0.9906 - loss: 0.0310 - precision: 0.9913 - recall: 0.9897 - val_accuracy: 0.9890 - val_loss: 0.0469 - val_precision: 0.9898 - val_recall: 0.9885 - learning_rate: 4.0000e-05\n",
+      "Epoch 58/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 112ms/step - accuracy: 0.9908 - loss: 0.0317 - precision: 0.9915 - recall: 0.9901 - val_accuracy: 0.9890 - val_loss: 0.0468 - val_precision: 0.9898 - val_recall: 0.9887 - learning_rate: 4.0000e-05\n",
+      "Epoch 59/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m32s\u001b[0m 112ms/step - accuracy: 0.9909 - loss: 0.0301 - precision: 0.9919 - recall: 0.9902 - val_accuracy: 0.9890 - val_loss: 0.0471 - val_precision: 0.9898 - val_recall: 0.9887 - learning_rate: 8.0000e-06\n",
+      "Epoch 60/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m32s\u001b[0m 112ms/step - accuracy: 0.9917 - loss: 0.0300 - precision: 0.9927 - recall: 0.9908 - val_accuracy: 0.9888 - val_loss: 0.0471 - val_precision: 0.9897 - val_recall: 0.9886 - learning_rate: 8.0000e-06\n",
+      "Epoch 61/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 112ms/step - accuracy: 0.9912 - loss: 0.0307 - precision: 0.9921 - recall: 0.9905 - val_accuracy: 0.9890 - val_loss: 0.0470 - val_precision: 0.9899 - val_recall: 0.9887 - learning_rate: 8.0000e-06\n",
+      "Epoch 62/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 112ms/step - accuracy: 0.9910 - loss: 0.0307 - precision: 0.9918 - recall: 0.9902 - val_accuracy: 0.9890 - val_loss: 0.0474 - val_precision: 0.9898 - val_recall: 0.9887 - learning_rate: 8.0000e-06\n",
+      "Epoch 63/100\n",
+      "\u001b[1m282/282\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 111ms/step - accuracy: 0.9907 - loss: 0.0307 - precision: 0.9915 - recall: 0.9900 - val_accuracy: 0.9889 - val_loss: 0.0472 - val_precision: 0.9897 - val_recall: 0.9886 - learning_rate: 8.0000e-06\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"\\nTraining model...\")\n",
+    "history = model.fit(\n",
+    "    X_train, y_train,\n",
+    "    validation_data=(X_val, y_val),\n",
+    "    epochs=100, # Train for longer, EarlyStopping will handle it\n",
+    "    batch_size=256,\n",
+    "    callbacks=[early_stop, reduce_lr],\n",
+    "    verbose=1\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-10-21T18:11:58.557155Z",
+     "iopub.status.busy": "2025-10-21T18:11:58.556880Z",
+     "iopub.status.idle": "2025-10-21T18:11:58.658338Z",
+     "shell.execute_reply": "2025-10-21T18:11:58.657691Z",
+     "shell.execute_reply.started": "2025-10-21T18:11:58.557135Z"
+    },
+    "trusted": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Saving model...\n",
+      "Model saved successfully!\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"\\nSaving model...\")\n",
+    "model.save('ecg_classifier.keras')\n",
+    "print(\"Model saved successfully!\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-10-21T18:12:05.161385Z",
+     "iopub.status.busy": "2025-10-21T18:12:05.161118Z",
+     "iopub.status.idle": "2025-10-21T18:12:06.934627Z",
+     "shell.execute_reply": "2025-10-21T18:12:06.933821Z",
+     "shell.execute_reply.started": "2025-10-21T18:12:05.161365Z"
+    },
+    "trusted": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Plotting training history...\n",
+      "Training history saved to: training_history.png\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1500x1000 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "print(\"\\nPlotting training history...\")\n",
+    "fig, axes = plt.subplots(2, 2, figsize=(15, 10))\n",
+    "\n",
+    "# Accuracy\n",
+    "axes[0, 0].plot(history.history['accuracy'], label='Train')\n",
+    "axes[0, 0].plot(history.history['val_accuracy'], label='Validation')\n",
+    "axes[0, 0].set_title('Model Accuracy', fontsize=14)\n",
+    "axes[0, 0].set_xlabel('Epoch')\n",
+    "axes[0, 0].set_ylabel('Accuracy')\n",
+    "axes[0, 0].legend()\n",
+    "axes[0, 0].grid(alpha=0.3)\n",
+    "\n",
+    "# Loss\n",
+    "axes[0, 1].plot(history.history['loss'], label='Train')\n",
+    "axes[0, 1].plot(history.history['val_loss'], label='Validation')\n",
+    "axes[0, 1].set_title('Model Loss', fontsize=14)\n",
+    "axes[0, 1].set_xlabel('Epoch')\n",
+    "axes[0, 1].set_ylabel('Loss')\n",
+    "axes[0, 1].legend()\n",
+    "axes[0, 1].grid(alpha=0.3)\n",
+    "\n",
+    "# Precision\n",
+    "axes[1, 0].plot(history.history['precision'], label='Train')\n",
+    "axes[1, 0].plot(history.history['val_precision'], label='Validation')\n",
+    "axes[1, 0].set_title('Model Precision', fontsize=14)\n",
+    "axes[1, 0].set_xlabel('Epoch')\n",
+    "axes[1, 0].set_ylabel('Precision')\n",
+    "axes[1, 0].legend()\n",
+    "axes[1, 0].grid(alpha=0.3)\n",
+    "\n",
+    "# Recall\n",
+    "axes[1, 1].plot(history.history['recall'], label='Train')\n",
+    "axes[1, 1].plot(history.history['val_recall'], label='Validation')\n",
+    "axes[1, 1].set_title('Model Recall', fontsize=14)\n",
+    "axes[1, 1].set_xlabel('Epoch')\n",
+    "axes[1, 1].set_ylabel('Recall')\n",
+    "axes[1, 1].legend()\n",
+    "axes[1, 1].grid(alpha=0.3)\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.savefig('training_history.png', dpi=150, bbox_inches='tight')\n",
+    "print(\"Training history saved to: training_history.png\")\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-10-21T18:12:15.414453Z",
+     "iopub.status.busy": "2025-10-21T18:12:15.414189Z",
+     "iopub.status.idle": "2025-10-21T18:12:36.658002Z",
+     "shell.execute_reply": "2025-10-21T18:12:36.657231Z",
+     "shell.execute_reply.started": "2025-10-21T18:12:15.414433Z"
+    },
+    "trusted": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "======================================================================\n",
+      "EVALUATION ON TEST SET\n",
+      "======================================================================\n",
+      "\u001b[1m704/704\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 14ms/step\n",
+      "\n",
+      "Test Loss: 0.0469\n",
+      "Test Accuracy: 0.9874\n",
+      "Test Precision: 0.9886\n",
+      "Test Recall: 0.9865\n",
+      "\n",
+      "Classification Report:\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           F     0.9124    0.7812    0.8418       160\n",
+      "           N     0.9915    0.9950    0.9933     18119\n",
+      "           Q     0.9808    0.9852    0.9830      2230\n",
+      "           S     0.9399    0.8435    0.8891       556\n",
+      "           V     0.9704    0.9737    0.9721      1447\n",
+      "\n",
+      "    accuracy                         0.9874     22512\n",
+      "   macro avg     0.9590    0.9157    0.9358     22512\n",
+      "weighted avg     0.9872    0.9874    0.9872     22512\n",
+      "\n",
+      "\n",
+      "Per-Class Detailed Metrics:\n",
+      "----------------------------------------------------------------------\n",
+      "Class      Precision    Recall       F1-Score     Support   \n",
+      "----------------------------------------------------------------------\n",
+      "F          0.9124       0.7812       0.8418       160       \n",
+      "N          0.9915       0.9950       0.9933       18119     \n",
+      "Q          0.9808       0.9852       0.9830       2230      \n",
+      "S          0.9399       0.8435       0.8891       556       \n",
+      "V          0.9704       0.9737       0.9721       1447      \n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"\\n\" + \"=\"*70)\n",
+    "print(\"EVALUATION ON TEST SET\")\n",
+    "print(\"=\"*70)\n",
+    "\n",
+    "# Make predictions\n",
+    "y_pred_probs = model.predict(X_test)\n",
+    "y_pred = np.argmax(y_pred_probs, axis=1)\n",
+    "y_true = np.argmax(y_test, axis=1)\n",
+    "\n",
+    "# Calculate metrics\n",
+    "test_loss, test_acc, test_prec, test_rec = model.evaluate(X_test, y_test, verbose=0)\n",
+    "print(f\"\\nTest Loss: {test_loss:.4f}\")\n",
+    "print(f\"Test Accuracy: {test_acc:.4f}\")\n",
+    "print(f\"Test Precision: {test_prec:.4f}\")\n",
+    "print(f\"Test Recall: {test_rec:.4f}\")\n",
+    "\n",
+    "# Classification Report\n",
+    "print(\"\\nClassification Report:\")\n",
+    "print(classification_report(y_true, y_pred, target_names=label_names, digits=4))\n",
+    "\n",
+    "# Per-class metrics\n",
+    "precision, recall, f1, support = precision_recall_fscore_support(y_true, y_pred)\n",
+    "print(\"\\nPer-Class Detailed Metrics:\")\n",
+    "print(\"-\" * 70)\n",
+    "print(f\"{'Class':<10} {'Precision':<12} {'Recall':<12} {'F1-Score':<12} {'Support':<10}\")\n",
+    "print(\"-\" * 70)\n",
+    "for i, label in enumerate(label_names):\n",
+    "    print(f\"{label:<10} {precision[i]:<12.4f} {recall[i]:<12.4f} {f1[i]:<12.4f} {support[i]:<10}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-10-21T18:15:44.093868Z",
+     "iopub.status.busy": "2025-10-21T18:15:44.093535Z",
+     "iopub.status.idle": "2025-10-21T18:15:45.358682Z",
+     "shell.execute_reply": "2025-10-21T18:15:45.358020Z",
+     "shell.execute_reply.started": "2025-10-21T18:15:44.093846Z"
+    },
+    "trusted": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Generating confusion matrix...\n",
+      "Confusion matrix saved to: confusion_matrix.png\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x800 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Normalized confusion matrix saved to: confusion_matrix_normalized.png\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "print(\"\\nGenerating confusion matrix...\")\n",
+    "cm = confusion_matrix(y_true, y_pred)\n",
+    "\n",
+    "plt.figure(figsize=(10, 8))\n",
+    "sns.heatmap(cm, annot=True, fmt='d', cmap='Blues',\n",
+    "            xticklabels=label_names, yticklabels=label_names,\n",
+    "            cbar_kws={'label': 'Count'})\n",
+    "plt.title('Confusion Matrix - Test Set', fontsize=16, pad=20)\n",
+    "plt.xlabel('Predicted Label', fontsize=12)\n",
+    "plt.ylabel('True Label', fontsize=12)\n",
+    "plt.tight_layout()\n",
+    "plt.savefig('confusion_matrix.png', dpi=150, bbox_inches='tight')\n",
+    "print(\"Confusion matrix saved to: confusion_matrix.png\")\n",
+    "plt.show()\n",
+    "\n",
+    "# Normalized confusion matrix\n",
+    "cm_norm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n",
+    "\n",
+    "plt.figure(figsize=(6, 4))\n",
+    "sns.heatmap(cm_norm, annot=True, fmt='.2%', cmap='Blues',\n",
+    "            xticklabels=label_names, yticklabels=label_names,\n",
+    "            cbar_kws={'label': 'Percentage'})\n",
+    "plt.title('Normalized Confusion Matrix - Test Set', fontsize=16, pad=20)\n",
+    "plt.xlabel('Predicted Label', fontsize=12)\n",
+    "plt.ylabel('True Label', fontsize=12)\n",
+    "plt.tight_layout()\n",
+    "plt.savefig('confusion_matrix_normalized.png', dpi=150, bbox_inches='tight')\n",
+    "print(\"Normalized confusion matrix saved to: confusion_matrix_normalized.png\")\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-10-21T18:17:51.649302Z",
+     "iopub.status.busy": "2025-10-21T18:17:51.648559Z",
+     "iopub.status.idle": "2025-10-21T18:17:53.777549Z",
+     "shell.execute_reply": "2025-10-21T18:17:53.776755Z",
+     "shell.execute_reply.started": "2025-10-21T18:17:51.649280Z"
+    },
+    "trusted": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Visualizing sample predictions...\n",
+      "Sample predictions saved to: sample_predictions.png\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x800 with 9 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "print(\"\\nVisualizing sample predictions...\")\n",
+    "num_samples = min(9, len(X_test))\n",
+    "random_indices = np.random.choice(len(X_test), num_samples, replace=False)\n",
+    "\n",
+    "fig, axes = plt.subplots(3, 3, figsize=(10, 8))\n",
+    "axes = axes.ravel()\n",
+    "\n",
+    "for i, idx in enumerate(random_indices):\n",
+    "    true_label = label_names[y_true[idx]]\n",
+    "    pred_label = label_names[y_pred[idx]]\n",
+    "    confidence = y_pred_probs[idx][y_pred[idx]] * 100\n",
+    "\n",
+    "    axes[i].plot(X_test[idx, :, 0])\n",
+    "\n",
+    "    color = 'green' if true_label == pred_label else 'red'\n",
+    "    axes[i].set_title(f'True: {true_label} | Pred: {pred_label} ({confidence:.1f}%)',\n",
+    "                     color=color, fontsize=10, fontweight='bold')\n",
+    "    axes[i].set_xlabel('Sample')\n",
+    "    axes[i].set_ylabel('Amplitude')\n",
+    "    axes[i].grid(alpha=0.3)\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.savefig('sample_predictions.png', dpi=150, bbox_inches='tight')\n",
+    "print(\"Sample predictions saved to: sample_predictions.png\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "trusted": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "trusted": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "trusted": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "trusted": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "trusted": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kaggle": {
+   "accelerator": "nvidiaTeslaT4",
+   "dataSources": [
+    {
+     "datasetId": 8542062,
+     "sourceId": 13457031,
+     "sourceType": "datasetVersion"
+    }
+   ],
+   "dockerImageVersionId": 31154,
+   "isGpuEnabled": true,
+   "isInternetEnabled": true,
+   "language": "python",
+   "sourceType": "notebook"
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}