LSTM_Forecast3Month.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "## Step 1: Imports and Data Loading\n",
    "# In this step, we import the necessary libraries and load the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as mdates\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import Dense, LSTM\n",
    "from sklearn.metrics import mean_squared_error, mean_absolute_error\n",
    "\n",
    "# Define the window size\n",
    "window_size = 5\n",
    "\n",
    "# Load dataset\n",
    "data = pd.read_csv('data.csv', parse_dates=['Date'], index_col='Date')\n",
    "\n",
    "# Convert 'Page.Loads' from string to integer\n",
    "data['Page.Loads'] = data['Page.Loads'].str.replace(',', '').astype(int)\n",
    "\n",
    "# Drop unnecessary columns\n",
    "columns_to_drop = [\"Row\", \"Day\", \"Day.Of.Week\", \"Unique.Visits\", \"Returning.Visits\", \"First.Time.Visits\"]\n",
    "data.drop(columns=columns_to_drop, inplace=True)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 2: Data Normalization and Sequence Creation\n",
    "# Here, we normalize the data and define functions to create sequences for the LSTM model.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler = MinMaxScaler(feature_range=(0, 1))\n",
    "\n",
    "# Function to create sequences\n",
    "def create_sequences(data, window_size):\n",
    "    X = []\n",
    "    y = []\n",
    "    for i in range(len(data) - window_size):\n",
    "        sequence = data[i:(i + window_size)]\n",
    "        label = data[i + window_size]\n",
    "        X.append(sequence)\n",
    "        y.append(label)\n",
    "    return np.array(X), np.array(y)\n",
    "\n",
    "# Function to prepare data\n",
    "def prepare_data(data, start_date, end_date, window_size, scaler):\n",
    "    data_filtered = data.loc[start_date:end_date, 'Page.Loads'].values.reshape(-1, 1)\n",
    "    data_normalized = scaler.transform(data_filtered)\n",
    "    X, y = create_sequences(data_normalized, window_size)\n",
    "    X = X.reshape((X.shape[0], window_size, 1))\n",
    "    return X, y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 3: Model Definition\n",
    "# We define the LSTM model architecture."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function to create the model\n",
    "def create_model(window_size):\n",
    "    model = Sequential([\n",
    "        LSTM(50, activation='relu', input_shape=(window_size, 1)),\n",
    "        Dense(1)\n",
    "    ])\n",
    "    model.compile(optimizer='adam', loss='mean_squared_error')\n",
    "    return model\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 4: Prediction and Plotting\n",
    "# This part contains the function to plot the predictions and actual values, providing a visual comparison.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_predictions(test, y_test, predicted_test, start_date, end_date, window_size, date_time):\n",
    "    test_dates = test[start_date:end_date].index  # Adjusting the test_dates to match y_test and predicted_test\n",
    "    uncertainty = 0.10 * predicted_test.flatten()\n",
    "    fig, ax = plt.subplots(figsize=(10, 5))\n",
    "    ax.scatter(test_dates, y_test, color='red', label='Actual')\n",
    "    ax.plot(test_dates, predicted_test, color='blue', label='Predicted')\n",
    "    ax.fill_between(test_dates, \n",
    "                    (predicted_test.flatten() - uncertainty), \n",
    "                    (predicted_test.flatten() + uncertainty), \n",
    "                    color='blue', alpha=0.2)\n",
    "    ax.set_title( 'LSTM Page Load Time Prediction with ' + date_time + ' of training data')\n",
    "    ax.set_xlabel('Date')\n",
    "    ax.set_ylabel('Page Loads')\n",
    "    ax.xaxis.set_major_locator(mdates.WeekdayLocator(interval=1))\n",
    "    ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))\n",
    "    ax.set_xlim([pd.Timestamp(start_date) - pd.DateOffset(days=5), pd.Timestamp(end_date) + pd.DateOffset(days=5)])\n",
    "    ax.set_ylim([0, max(max(y_test), max(predicted_test)) + 1000])\n",
    "    plt.setp(ax.get_xticklabels(), rotation=45, ha='right')\n",
    "    ax.grid(True)\n",
    "    ax.legend()\n",
    "    plt.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 5: Training and Evaluation Loop\n",
    "# In this final step, we train the model using different training periods and evaluate its performance.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Zebbe\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\sklearn\\base.py:493: UserWarning: X does not have valid feature names, but MinMaxScaler was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "# Prepare training data for 2019\n",
    "start_date = '2019-01-01'\n",
    "end_date = '2019-12-26'\n",
    "\n",
    "# Define testing period\n",
    "testing_start_date = '2019-12-27'\n",
    "testing_end_date = '2020-03-31'\n",
    "\n",
    "scaler.fit(data.loc[start_date:end_date, ['Page.Loads']])\n",
    "X_train, y_train = prepare_data(data, start_date, end_date, window_size, scaler)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Train the model for 2019 data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Zebbe\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\keras\\src\\layers\\rnn\\rnn.py:204: 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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.3340  \n",
      "Epoch 2/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.2286 \n",
      "Epoch 3/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.1461 \n",
      "Epoch 4/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0841 \n",
      "Epoch 5/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0510 \n",
      "Epoch 6/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0509 \n",
      "Epoch 7/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0465 \n",
      "Epoch 8/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0463 \n",
      "Epoch 9/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0426 \n",
      "Epoch 10/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1000us/step - loss: 0.0462\n",
      "Epoch 11/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1000us/step - loss: 0.0431\n",
      "Epoch 12/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1000us/step - loss: 0.0416\n",
      "Epoch 13/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0433 \n",
      "Epoch 14/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1000us/step - loss: 0.0430\n",
      "Epoch 15/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0394 \n",
      "Epoch 16/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0404 \n",
      "Epoch 17/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0400 \n",
      "Epoch 18/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0379 \n",
      "Epoch 19/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0355 \n",
      "Epoch 20/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0358 \n",
      "Epoch 21/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1000us/step - loss: 0.0314\n",
      "Epoch 22/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0315 \n",
      "Epoch 23/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0269 \n",
      "Epoch 24/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0288 \n",
      "Epoch 25/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0276 \n",
      "Epoch 26/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0229 \n",
      "Epoch 27/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0233 \n",
      "Epoch 28/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1000us/step - loss: 0.0201\n",
      "Epoch 29/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0197 \n",
      "Epoch 30/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1000us/step - loss: 0.0182\n",
      "Epoch 31/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0162 \n",
      "Epoch 32/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0157 \n",
      "Epoch 33/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0149 \n",
      "Epoch 34/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0159 \n",
      "Epoch 35/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0158 \n",
      "Epoch 36/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0142 \n",
      "Epoch 37/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0139 \n",
      "Epoch 38/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0154 \n",
      "Epoch 39/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0152 \n",
      "Epoch 40/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0130 \n",
      "Epoch 41/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0129 \n",
      "Epoch 42/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1000us/step - loss: 0.0136\n",
      "Epoch 43/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0148 \n",
      "Epoch 44/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0126 \n",
      "Epoch 45/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0115 \n",
      "Epoch 46/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1000us/step - loss: 0.0123\n",
      "Epoch 47/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0139 \n",
      "Epoch 48/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1000us/step - loss: 0.0137\n",
      "Epoch 49/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0114 \n",
      "Epoch 50/50\n",
      "\u001b[1m12/12\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0115 \n",
      "CPU times: total: 1.11 s\n",
      "Wall time: 2.37 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x13033150740>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "model = create_model(window_size)\n",
    "model.fit(X_train, y_train, epochs=50, batch_size=32, verbose=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m1/3\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 87ms/step"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Zebbe\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\sklearn\\base.py:493: UserWarning: X does not have valid feature names, but MinMaxScaler was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Prepare testing data\n",
    "X_test, y_test = prepare_data(data, testing_start_date, testing_end_date, window_size, scaler)\n",
    "\n",
    "# Predict on test data\n",
    "predicted_test = model.predict(X_test)\n",
    "predicted_test = scaler.inverse_transform(predicted_test)\n",
    "\n",
    "# Correctly get the actual values for the test period\n",
    "y_test_actual = data.loc['2020-01-01':'2020-03-31', 'Page.Loads']\n",
    "date_time = '1 year'\n",
    "# Ensure 1-dimensional arrays for metric calculation\n",
    "y_test_actual = y_test_actual.to_numpy().flatten()\n",
    "predicted_test = predicted_test.flatten()[:len(y_test_actual)]  # Ensure the prediction length matches the actual data length\n",
    "\n",
    "# Calculate metrics\n",
    "mse = mean_squared_error(y_test_actual, predicted_test)\n",
    "rmse = np.sqrt(mse)  # Calculate RMSE\n",
    "mae = mean_absolute_error(y_test_actual, predicted_test)\n",
    "mape = np.mean(np.abs((y_test_actual - predicted_test) / y_test_actual)) * 100\n",
    "\n",
    "# Store results\n",
    "results_2019 = (start_date, end_date, rmse, mae, mape)\n",
    "\n",
    "# Plot predictions\n",
    "plot_predictions(data, y_test_actual, predicted_test, '2020-01-01', '2020-03-31', window_size, date_time)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 6: Training and Evaluation for 2018 Data\n",
    "# We train the model using data from 2018 and measure the training time.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Zebbe\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\sklearn\\base.py:493: UserWarning: X does not have valid feature names, but MinMaxScaler was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "# Prepare training data for 2018\n",
    "start_date = '2018-01-01'\n",
    "end_date = '2019-12-26'\n",
    "scaler.fit(data.loc[start_date:end_date, ['Page.Loads']])\n",
    "X_train, y_train = prepare_data(data, start_date, end_date, window_size, scaler)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Zebbe\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\keras\\src\\layers\\rnn\\rnn.py:204: 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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.1814   \n",
      "Epoch 2/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0531 \n",
      "Epoch 3/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0416 \n",
      "Epoch 4/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0392 \n",
      "Epoch 5/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0359 \n",
      "Epoch 6/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0367 \n",
      "Epoch 7/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0338 \n",
      "Epoch 8/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0326 \n",
      "Epoch 9/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0323 \n",
      "Epoch 10/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0318 \n",
      "Epoch 11/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0264 \n",
      "Epoch 12/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0257 \n",
      "Epoch 13/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0239 \n",
      "Epoch 14/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0220 \n",
      "Epoch 15/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0192 \n",
      "Epoch 16/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0184 \n",
      "Epoch 17/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0159 \n",
      "Epoch 18/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0152 \n",
      "Epoch 19/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0135 \n",
      "Epoch 20/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0136 \n",
      "Epoch 21/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0158 \n",
      "Epoch 22/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0131 \n",
      "Epoch 23/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0128 \n",
      "Epoch 24/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0136 \n",
      "Epoch 25/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0121 \n",
      "Epoch 26/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0132 \n",
      "Epoch 27/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0125 \n",
      "Epoch 28/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0128 \n",
      "Epoch 29/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0130 \n",
      "Epoch 30/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0142 \n",
      "Epoch 31/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0129 \n",
      "Epoch 32/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0124 \n",
      "Epoch 33/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0131 \n",
      "Epoch 34/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0119 \n",
      "Epoch 35/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0121 \n",
      "Epoch 36/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0118 \n",
      "Epoch 37/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0115 \n",
      "Epoch 38/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0120 \n",
      "Epoch 39/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0118 \n",
      "Epoch 40/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0121 \n",
      "Epoch 41/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0104 \n",
      "Epoch 42/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0109 \n",
      "Epoch 43/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0109 \n",
      "Epoch 44/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0105 \n",
      "Epoch 45/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0098 \n",
      "Epoch 46/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0097 \n",
      "Epoch 47/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0093 \n",
      "Epoch 48/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0094 \n",
      "Epoch 49/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0084 \n",
      "Epoch 50/50\n",
      "\u001b[1m23/23\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0083 \n",
      "CPU times: total: 1.12 s\n",
      "Wall time: 3.04 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x13037e8f4a0>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "# Train the model for 2018 data\n",
    "model = create_model(window_size)\n",
    "model.fit(X_train, y_train, epochs=50, batch_size=32, verbose=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m1/3\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 89ms/step"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Zebbe\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\sklearn\\base.py:493: UserWarning: X does not have valid feature names, but MinMaxScaler was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:5 out of the last 19 calls to <function TensorFlowTrainer.make_predict_function.<locals>.one_step_on_data_distributed at 0x000001303819B600> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Prepare testing data\n",
    "X_test, y_test = prepare_data(data, testing_start_date, testing_end_date, window_size, scaler)\n",
    "\n",
    "# Predict on test data\n",
    "predicted_test = model.predict(X_test)\n",
    "predicted_test = scaler.inverse_transform(predicted_test)\n",
    "\n",
    "# Correctly get the actual values for the test period\n",
    "y_test_actual = data.loc['2020-01-01':'2020-03-31', 'Page.Loads']\n",
    "date_time = '2 years'\n",
    "# Ensure 1-dimensional arrays for metric calculation\n",
    "y_test_actual = y_test_actual.to_numpy().flatten()\n",
    "predicted_test = predicted_test.flatten()[:len(y_test_actual)]  # Ensure the prediction length matches the actual data length\n",
    "\n",
    "# Calculate metrics\n",
    "mse = mean_squared_error(y_test_actual, predicted_test)\n",
    "rmse = np.sqrt(mse)  # Calculate RMSE\n",
    "mae = mean_absolute_error(y_test_actual, predicted_test)\n",
    "mape = np.mean(np.abs((y_test_actual - predicted_test) / y_test_actual)) * 100\n",
    "\n",
    "# Store results\n",
    "results_2018 = (start_date, end_date, rmse, mae, mape)\n",
    "\n",
    "# Plot predictions\n",
    "plot_predictions(data, y_test_actual, predicted_test, '2020-01-01', '2020-03-31', window_size, date_time)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 7: Training and Evaluation for 2017 Data\n",
    "# We train the model using data from 2017 and measure the training time.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Zebbe\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\sklearn\\base.py:493: UserWarning: X does not have valid feature names, but MinMaxScaler was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "# Prepare training data for 2017\n",
    "start_date = '2017-01-01'\n",
    "end_date = '2019-12-26'\n",
    "scaler.fit(data.loc[start_date:end_date, ['Page.Loads']])\n",
    "X_train, y_train = prepare_data(data, start_date, end_date, window_size, scaler)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Zebbe\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\keras\\src\\layers\\rnn\\rnn.py:204: 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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.1400   \n",
      "Epoch 2/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0329 \n",
      "Epoch 3/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0303 \n",
      "Epoch 4/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0297 \n",
      "Epoch 5/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0296 \n",
      "Epoch 6/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0281 \n",
      "Epoch 7/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0264 \n",
      "Epoch 8/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0239 \n",
      "Epoch 9/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0216 \n",
      "Epoch 10/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0156 \n",
      "Epoch 11/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0136 \n",
      "Epoch 12/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0131 \n",
      "Epoch 13/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0112 \n",
      "Epoch 14/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0111 \n",
      "Epoch 15/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0118 \n",
      "Epoch 16/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0103 \n",
      "Epoch 17/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0107 \n",
      "Epoch 18/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 970us/step - loss: 0.0096\n",
      "Epoch 19/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1000us/step - loss: 0.0093\n",
      "Epoch 20/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0087 \n",
      "Epoch 21/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0088 \n",
      "Epoch 22/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0082 \n",
      "Epoch 23/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0080 \n",
      "Epoch 24/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0078 \n",
      "Epoch 25/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0078 \n",
      "Epoch 26/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0080 \n",
      "Epoch 27/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0082 \n",
      "Epoch 28/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0072 \n",
      "Epoch 29/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1000us/step - loss: 0.0074\n",
      "Epoch 30/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0069 \n",
      "Epoch 31/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0067 \n",
      "Epoch 32/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0061 \n",
      "Epoch 33/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0066 \n",
      "Epoch 34/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0069 \n",
      "Epoch 35/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0065 \n",
      "Epoch 36/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0061 \n",
      "Epoch 37/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0059 \n",
      "Epoch 38/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0053 \n",
      "Epoch 39/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0064 \n",
      "Epoch 40/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0057 \n",
      "Epoch 41/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0058 \n",
      "Epoch 42/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0051 \n",
      "Epoch 43/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0055 \n",
      "Epoch 44/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0057 \n",
      "Epoch 45/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0053 \n",
      "Epoch 46/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0053 \n",
      "Epoch 47/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0052 \n",
      "Epoch 48/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0055 \n",
      "Epoch 49/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0048 \n",
      "Epoch 50/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0054 \n",
      "CPU times: total: 1.09 s\n",
      "Wall time: 3.55 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x130393bd1f0>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "# Train the model for 2017 data\n",
    "model = create_model(window_size)\n",
    "model.fit(X_train, y_train, epochs=50, batch_size=32, verbose=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:6 out of the last 20 calls to <function TensorFlowTrainer.make_predict_function.<locals>.one_step_on_data_distributed at 0x000001303A4F7E20> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
      "\u001b[1m1/3\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 95ms/step"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Zebbe\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\sklearn\\base.py:493: UserWarning: X does not have valid feature names, but MinMaxScaler was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 41ms/step\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Prepare testing data\n",
    "X_test, y_test = prepare_data(data, testing_start_date, testing_end_date, window_size, scaler)\n",
    "\n",
    "# Predict on test data\n",
    "predicted_test = model.predict(X_test)\n",
    "predicted_test = scaler.inverse_transform(predicted_test)\n",
    "\n",
    "# Correctly get the actual values for the test period\n",
    "y_test_actual = data.loc['2020-01-01':'2020-03-31', 'Page.Loads']\n",
    "date_time = '3 years'\n",
    "# Ensure 1-dimensional arrays for metric calculation\n",
    "y_test_actual = y_test_actual.to_numpy().flatten()\n",
    "predicted_test = predicted_test.flatten()[:len(y_test_actual)]  # Ensure the prediction length matches the actual data length\n",
    "\n",
    "# Calculate metrics\n",
    "mse = mean_squared_error(y_test_actual, predicted_test)\n",
    "rmse = np.sqrt(mse)  # Calculate RMSE\n",
    "mae = mean_absolute_error(y_test_actual, predicted_test)\n",
    "mape = np.mean(np.abs((y_test_actual - predicted_test) / y_test_actual)) * 100\n",
    "\n",
    "# Store results\n",
    "results_2017 = (start_date, end_date, rmse, mae, mape)\n",
    "\n",
    "# Plot predictions\n",
    "plot_predictions(data, y_test_actual, predicted_test, '2020-01-01', '2020-03-31', window_size, date_time)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 8: Training and Evaluation for 2016 Data\n",
    "# We train the model using data from 2016 and measure the training time.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Zebbe\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\sklearn\\base.py:493: UserWarning: X does not have valid feature names, but MinMaxScaler was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "# Prepare training data for 2016\n",
    "start_date = '2016-01-01'\n",
    "end_date = '2019-12-26'\n",
    "scaler.fit(data.loc[start_date:end_date, ['Page.Loads']])\n",
    "X_train, y_train = prepare_data(data, start_date, end_date, window_size, scaler)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Zebbe\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\keras\\src\\layers\\rnn\\rnn.py:204: 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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - loss: 0.1735\n",
      "Epoch 2/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0330\n",
      "Epoch 3/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0309 \n",
      "Epoch 4/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0296 \n",
      "Epoch 5/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0263 \n",
      "Epoch 6/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0226 \n",
      "Epoch 7/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0187 \n",
      "Epoch 8/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0139 \n",
      "Epoch 9/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0126\n",
      "Epoch 10/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0125 \n",
      "Epoch 11/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 978us/step - loss: 0.0115\n",
      "Epoch 12/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 982us/step - loss: 0.0112\n",
      "Epoch 13/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0099 \n",
      "Epoch 14/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0092 \n",
      "Epoch 15/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0089 \n",
      "Epoch 16/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0086 \n",
      "Epoch 17/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0080 \n",
      "Epoch 18/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 979us/step - loss: 0.0073\n",
      "Epoch 19/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 978us/step - loss: 0.0075\n",
      "Epoch 20/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0069 \n",
      "Epoch 21/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0069 \n",
      "Epoch 22/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0065 \n",
      "Epoch 23/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0065 \n",
      "Epoch 24/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0064 \n",
      "Epoch 25/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0060 \n",
      "Epoch 26/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0067 \n",
      "Epoch 27/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0061 \n",
      "Epoch 28/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1000us/step - loss: 0.0056\n",
      "Epoch 29/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0057 \n",
      "Epoch 30/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0060 \n",
      "Epoch 31/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0057 \n",
      "Epoch 32/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0055 \n",
      "Epoch 33/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0052 \n",
      "Epoch 34/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0058 \n",
      "Epoch 35/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0053 \n",
      "Epoch 36/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0055 \n",
      "Epoch 37/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 993us/step - loss: 0.0060\n",
      "Epoch 38/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0057 \n",
      "Epoch 39/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0053 \n",
      "Epoch 40/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0055 \n",
      "Epoch 41/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1000us/step - loss: 0.0051\n",
      "Epoch 42/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 989us/step - loss: 0.0048\n",
      "Epoch 43/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0055 \n",
      "Epoch 44/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 978us/step - loss: 0.0047\n",
      "Epoch 45/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0050 \n",
      "Epoch 46/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1000us/step - loss: 0.0055\n",
      "Epoch 47/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 980us/step - loss: 0.0052\n",
      "Epoch 48/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - loss: 0.0046 \n",
      "Epoch 49/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 978us/step - loss: 0.0049\n",
      "Epoch 50/50\n",
      "\u001b[1m46/46\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 961us/step - loss: 0.0054\n",
      "CPU times: total: 1.77 s\n",
      "Wall time: 4.23 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x1303ba2f740>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "# Train the model for 2016 data\n",
    "model = create_model(window_size)\n",
    "model.fit(X_train, y_train, epochs=50, batch_size=32, verbose=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m1/3\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 104ms/step"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Zebbe\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\sklearn\\base.py:493: UserWarning: X does not have valid feature names, but MinMaxScaler was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 41ms/step\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Prepare testing data\n",
    "X_test, y_test = prepare_data(data, testing_start_date, testing_end_date, window_size, scaler)\n",
    "\n",
    "# Predict on test data\n",
    "predicted_test = model.predict(X_test)\n",
    "predicted_test = scaler.inverse_transform(predicted_test)\n",
    "\n",
    "# Correctly get the actual values for the test period\n",
    "y_test_actual = data.loc['2020-01-01':'2020-03-31', 'Page.Loads']\n",
    "date_time = '4 years'\n",
    "# Ensure 1-dimensional arrays for metric calculation\n",
    "y_test_actual = y_test_actual.to_numpy().flatten()\n",
    "predicted_test = predicted_test.flatten()[:len(y_test_actual)]  # Ensure the prediction length matches the actual data length\n",
    "\n",
    "# Calculate metrics\n",
    "mse = mean_squared_error(y_test_actual, predicted_test)\n",
    "rmse = np.sqrt(mse)  # Calculate RMSE\n",
    "mae = mean_absolute_error(y_test_actual, predicted_test)\n",
    "mape = np.mean(np.abs((y_test_actual - predicted_test) / y_test_actual)) * 100\n",
    "\n",
    "# Store results\n",
    "results_2016 = (start_date, end_date, rmse, mae, mape)\n",
    "\n",
    "# Plot predictions\n",
    "plot_predictions(data, y_test_actual, predicted_test, '2020-01-01', '2020-03-31', window_size, date_time)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 9: Display Results\n",
    "# Finally, we display the results for all training periods."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training period: 2016-01-01 to 2019-12-26\n",
      "  RMSE: 466.726582519793\n",
      "  MAE: 344.1026141826923\n",
      "  MAPE: 9.328509202992286\n",
      "\n",
      "--------------------------------------------------\n",
      "\n",
      "Training period: 2017-01-01 to 2019-12-26\n",
      "  RMSE: 474.9022093003813\n",
      "  MAE: 359.07443069625685\n",
      "  MAPE: 9.668213881568342\n",
      "\n",
      "--------------------------------------------------\n",
      "\n",
      "Training period: 2018-01-01 to 2019-12-26\n",
      "  RMSE: 488.94558407063414\n",
      "  MAE: 385.636962890625\n",
      "  MAPE: 11.139695751763453\n",
      "\n",
      "--------------------------------------------------\n",
      "\n",
      "Training period: 2019-01-01 to 2019-12-26\n",
      "  RMSE: 506.32558146680486\n",
      "  MAE: 415.464595585079\n",
      "  MAPE: 12.217131896545661\n",
      "\n",
      "--------------------------------------------------\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Print results\n",
    "for result in [results_2016, results_2017, results_2018, results_2019]:\n",
    "    print(f\"Training period: {result[0]} to {result[1]}\")\n",
    "    print(f\"  RMSE: {result[2]}\")\n",
    "    print(f\"  MAE: {result[3]}\")\n",
    "    print(f\"  MAPE: {result[4]}\")\n",
    "    print(\"\\n\" + \"-\"*50 + \"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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