BitcoinPricePredictor.ipynb

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      "name": "BitcoinPricePredictor",
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        "<a href=\"https://colab.research.google.com/github/kiran-lenka/Bitcoin-Price-Predictor/blob/main/BitcoinPricePredictor.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "source": [
        "%tensorflow_version 2.x\n",
        "import json\n",
        "import requests\n",
        "from keras.models import Sequential\n",
        "from keras.layers import Activation, Dense, Dropout, LSTM\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "from sklearn.metrics import mean_absolute_error\n",
        "%matplotlib inline"
      ],
      "execution_count": null,
      "outputs": []
    },
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        "trusted": true,
        "id": "6W__OM92pskF"
      },
      "source": [
        "endpoint = 'https://min-api.cryptocompare.com/data/histoday'\n",
        "res = requests.get(endpoint + '?fsym=BTC&tsym=USD&limit=1000')\n",
        "#print (res.content['Data'])\n",
        "hist = pd.DataFrame(json.loads(res.content)['Data'])\n",
        "hist = hist.set_index('time')\n",
        "hist.index = pd.to_datetime(hist.index, unit='s')\n",
        "target_col = 'close'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IJ81oAj4sw6x"
      },
      "source": [
        "hist.drop([\"conversionType\", \"conversionSymbol\"], axis = 'columns', inplace = True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
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        "outputId": "32139428-1a2c-4e3a-a732-608a116aeeed"
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      "source": [
        "hist.tail(5)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                high       low      open  volumefrom      volumeto     close\n",
              "time                                                                        \n",
              "2022-04-21  42996.50  39864.73  41375.35    31792.30  1.324053e+09  40490.97\n",
              "2022-04-22  40794.73  39190.22  40490.97    28863.91  1.154694e+09  39716.04\n",
              "2022-04-23  39988.54  39305.67  39716.04    11481.51  4.556596e+08  39445.97\n",
              "2022-04-24  39943.44  39044.29  39445.97    12668.56  5.012721e+08  39466.26\n",
              "2022-04-25  39515.99  38292.30  39466.26    12343.51  4.796738e+08  38534.33"
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              "      <th>2022-04-21</th>\n",
              "      <td>42996.50</td>\n",
              "      <td>39864.73</td>\n",
              "      <td>41375.35</td>\n",
              "      <td>31792.30</td>\n",
              "      <td>1.324053e+09</td>\n",
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              "      <th>2022-04-22</th>\n",
              "      <td>40794.73</td>\n",
              "      <td>39190.22</td>\n",
              "      <td>40490.97</td>\n",
              "      <td>28863.91</td>\n",
              "      <td>1.154694e+09</td>\n",
              "      <td>39716.04</td>\n",
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              "      <th>2022-04-23</th>\n",
              "      <td>39988.54</td>\n",
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              "      <td>39445.97</td>\n",
              "      <td>12668.56</td>\n",
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              "      <td>39515.99</td>\n",
              "      <td>38292.30</td>\n",
              "      <td>39466.26</td>\n",
              "      <td>12343.51</td>\n",
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      "source": [
        "def train_test_split(df, test_size=0.2):\n",
        "    split_row = len(df) - int(test_size * len(df))\n",
        "    train_data = df.iloc[:split_row]\n",
        "    test_data = df.iloc[split_row:]\n",
        "    return train_data, test_data"
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      "source": [
        "train, test = train_test_split(hist, test_size=0.2)"
      ],
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      "cell_type": "code",
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      "source": [
        "def line_plot(line1, line2, label1=None, label2=None, title='', lw=2):\n",
        "    fig, ax = plt.subplots(1, figsize=(13, 7))\n",
        "    ax.plot(line1, label=label1, linewidth=lw)\n",
        "    ax.plot(line2, label=label2, linewidth=lw)\n",
        "    ax.set_ylabel('price [CAD]', fontsize=14)\n",
        "    ax.set_title(title, fontsize=16)\n",
        "    ax.legend(loc='best', fontsize=16);"
      ],
      "execution_count": null,
      "outputs": []
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              "<Figure size 936x504 with 1 Axes>"
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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "iy-je3_bpskb"
      },
      "source": [
        "def normalise_zero_base(df):\n",
        "    return df / df.iloc[0] - 1\n",
        "\n",
        "def normalise_min_max(df):\n",
        "    return (df - df.min()) / (data.max() - df.min())"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "zteL5amIpskh"
      },
      "source": [
        "def extract_window_data(df, window_len=5, zero_base=True):\n",
        "    window_data = []\n",
        "    for idx in range(len(df) - window_len):\n",
        "        tmp = df[idx: (idx + window_len)].copy()\n",
        "        if zero_base:\n",
        "            tmp = normalise_zero_base(tmp)\n",
        "        window_data.append(tmp.values)\n",
        "    return np.array(window_data)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "aTBbhnezpskk"
      },
      "source": [
        "def prepare_data(df, target_col, window_len=10, zero_base=True, test_size=0.2):\n",
        "    train_data, test_data = train_test_split(df, test_size=test_size)\n",
        "    X_train = extract_window_data(train_data, window_len, zero_base)\n",
        "    X_test = extract_window_data(test_data, window_len, zero_base)\n",
        "    y_train = train_data[target_col][window_len:].values\n",
        "    y_test = test_data[target_col][window_len:].values\n",
        "    if zero_base:\n",
        "        y_train = y_train / train_data[target_col][:-window_len].values - 1\n",
        "        y_test = y_test / test_data[target_col][:-window_len].values - 1\n",
        "\n",
        "    return train_data, test_data, X_train, X_test, y_train, y_test"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "VjWtS2qJpskn"
      },
      "source": [
        "def build_lstm_model(input_data, output_size, neurons=100, activ_func='linear',\n",
        "                     dropout=0.2, loss='mse', optimizer='adam'):\n",
        "    model = Sequential()\n",
        "    model.add(LSTM(neurons, input_shape=(input_data.shape[1], input_data.shape[2])))\n",
        "    model.add(Dropout(dropout))\n",
        "    model.add(Dense(units=output_size))\n",
        "    model.add(Activation(activ_func))\n",
        "\n",
        "    model.compile(loss=loss, optimizer=optimizer)\n",
        "    return model"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "aADcao3Qpskq"
      },
      "source": [
        "np.random.seed(42)\n",
        "window_len = 5\n",
        "test_size = 0.2\n",
        "zero_base = True\n",
        "lstm_neurons = 100\n",
        "epochs = 20\n",
        "batch_size = 32\n",
        "loss = 'mse'\n",
        "dropout = 0.2\n",
        "optimizer = 'adam'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "rAw5VBtwpskt"
      },
      "source": [
        "train, test, X_train, X_test, y_train, y_test = prepare_data(\n",
        "    hist, target_col, window_len=window_len, zero_base=zero_base, test_size=test_size)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "E5T9OAwQpskw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0c2cac34-a184-4fbe-8292-ae533cd30042"
      },
      "source": [
        "model = build_lstm_model(\n",
        "    X_train, output_size=1, neurons=lstm_neurons, dropout=dropout, loss=loss,\n",
        "    optimizer=optimizer)\n",
        "history = model.fit(\n",
        "    X_train, y_train, validation_data=(X_test, y_test), epochs=epochs, batch_size=batch_size, verbose=1, shuffle=True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/20\n",
            "25/25 [==============================] - 7s 65ms/step - loss: 0.0060 - val_loss: 0.0024\n",
            "Epoch 2/20\n",
            "25/25 [==============================] - 0s 18ms/step - loss: 0.0040 - val_loss: 0.0022\n",
            "Epoch 3/20\n",
            "25/25 [==============================] - 0s 19ms/step - loss: 0.0034 - val_loss: 0.0018\n",
            "Epoch 4/20\n",
            "25/25 [==============================] - 1s 20ms/step - loss: 0.0030 - val_loss: 0.0019\n",
            "Epoch 5/20\n",
            "25/25 [==============================] - 0s 18ms/step - loss: 0.0029 - val_loss: 0.0024\n",
            "Epoch 6/20\n",
            "25/25 [==============================] - 0s 19ms/step - loss: 0.0032 - val_loss: 0.0017\n",
            "Epoch 7/20\n",
            "25/25 [==============================] - 0s 18ms/step - loss: 0.0028 - val_loss: 0.0016\n",
            "Epoch 8/20\n",
            "25/25 [==============================] - 0s 18ms/step - loss: 0.0025 - val_loss: 0.0020\n",
            "Epoch 9/20\n",
            "25/25 [==============================] - 0s 18ms/step - loss: 0.0026 - val_loss: 0.0015\n",
            "Epoch 10/20\n",
            "25/25 [==============================] - 0s 18ms/step - loss: 0.0022 - val_loss: 0.0016\n",
            "Epoch 11/20\n",
            "25/25 [==============================] - 1s 20ms/step - loss: 0.0022 - val_loss: 0.0016\n",
            "Epoch 12/20\n",
            "25/25 [==============================] - 0s 18ms/step - loss: 0.0021 - val_loss: 0.0014\n",
            "Epoch 13/20\n",
            "25/25 [==============================] - 0s 17ms/step - loss: 0.0021 - val_loss: 0.0014\n",
            "Epoch 14/20\n",
            "25/25 [==============================] - 1s 20ms/step - loss: 0.0021 - val_loss: 0.0015\n",
            "Epoch 15/20\n",
            "25/25 [==============================] - 1s 21ms/step - loss: 0.0021 - val_loss: 0.0014\n",
            "Epoch 16/20\n",
            "25/25 [==============================] - 1s 23ms/step - loss: 0.0020 - val_loss: 0.0014\n",
            "Epoch 17/20\n",
            "25/25 [==============================] - 0s 19ms/step - loss: 0.0019 - val_loss: 0.0013\n",
            "Epoch 18/20\n",
            "25/25 [==============================] - 0s 20ms/step - loss: 0.0020 - val_loss: 0.0013\n",
            "Epoch 19/20\n",
            "25/25 [==============================] - 1s 20ms/step - loss: 0.0019 - val_loss: 0.0013\n",
            "Epoch 20/20\n",
            "25/25 [==============================] - 1s 22ms/step - loss: 0.0020 - val_loss: 0.0015\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qhMsatri0miT",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "outputId": "37626d6d-843c-4d17-af6a-2674c60f86c8"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "plt.plot(history.history['loss'],'r',linewidth=2, label='Train loss')\n",
        "plt.plot(history.history['val_loss'], 'g',linewidth=2, label='Validation loss')\n",
        "plt.title('LSTM')\n",
        "plt.xlabel('Epochs')\n",
        "plt.ylabel('MSE')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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HTCPcw3G3u/dy93vdfXVSqquKmjYNbRwQGsq3bUttPSIi+RR3xHEx0AEYAXxsZlsij61mtiXx5VVR11wDRx0FK1fCnXfqlJWIlCvFtXFUc/cDI496UY8D3b1esoqscvIays1C1+u/+AXk5KS6KhERoARtHJIixxwDL70ENWrAQw/BkCGwY0eqqxIRUXCUa0OHwoQJUL8+vPYanHoqbNiQ6qpEpIpTcJR3/fvD1KnQsiV89BEcdxwsW5bqqkSkClNwVARdu8K0adCtW7gx8NhjYc6cVFclIlWUgqOiaNkSPvwQTjoJ1q6Ffv3CaazybOtW2LUr1VWISJwpOCqS+vXhf/+Dn/wkjBh45pkwcmSqq9qfOzz1FDRvDt27w7p1qa5IROJIwVHR1KgBzz0Ht90WLtG9/PIwemB5uddjy5YQbMOHh6vAFi6EM87Q0LgilYiCoyKqVi10TfLII2H6d78LNw1mZ6e2rlmzoEcPePllqFMH/vUvOOSQMP/88yErK7X1iUhcKDgqsuuvD/1Z1aoVumQfNCg1/7N3Dzcq9ukDixeH01OzZ8MNN4R2mGbNQt9bl18OuRqqXqSiU3BUdIMGwaRJ0LgxvP02nHgifPdd8va/fj2cfTbcfHPo1femm+CTT8KIhgDt24e66tYNNzT+6lfl57SaiJSKgqMyOPZY+PhjaNcunBbq0we+/jrx+50yBY48Et56Cxo2hDffhIcfhpo1912vZ0944w2oXj0cmTzwQOJrE5GEUXBUFocdFu71yMiAJUtCeEyblph95eTA3XeHS4O//TbclPjZZ+HopzCnnBIa9QF+/Wt49tnE1CYiCZfQ4DCzgWb2lZktMrPbClhe08xGRZZPN7O2Uctuj8z/yswGRObVMrMZZjbXzOab2d2JrL/Cad4cJk8OVzFt2BD+sP/jH/DNN/E7PbR6NZx8Mtx1V9jmb38b9tm6dfHvHTo09LsFYcCqt96KT00iklzunpAHkAYsBg4BagBzgc751rke+HdkeigwKjLdObJ+TaBdZDtphDHP60bWqU4YB/2Y4mrp2bOnVym7d7sPH+4e/rSHR6tW7pde6v7cc+6rVpVuu+PGuTdpErb3ox+5v/de6bZz++1hG7Vru0+bVrptiEhCAbO8kL+piTzi6A0scvcl7p4FvALkP5cxCMg7ZzEGONnMLDL/FXff5e5LCUPW9o58nrzLhqpHHmppzS89HR5/HF58ES64IDScr1wZTg9dckm4C71jx3DV02uvwQ8/FL29rCz45S/hrLNCY/hpp4VTUyefXLr6/vhHuOKKcJ/HmWfCggWl246IpEQig+NgYGXU61WReQWu4+7ZwGagcVHvNbM0M/sM+B54192nF7RzM7vazGaZ2ax1VfHOZTO46CJ49VX4/vvwh/7BB8Mf6rp1Q59Xjz4KgwdDkyahAfuWW2D8+H1HHVy8OLRh/O1vIZDuvz/cvd68edlq+89/QhD98AMMGACrVpX9M4tIUqSnuoBYuXsO0N3MGgBvmFlXd/+igPUeBx4HyMjIqNpHJdWqhaufjjxy72WzM2eGy3gnTgxXZM2eHR4PPBCufjr66NDQ/tRToc+ptm3DjX3HHBOfmtLTYdSo0Gg+bRoMHBj64mrYMD7bF5GESeQRx2qgVdTrlpF5Ba5jZulAfWBDSd7r7puA94GBca26KqhePVx1dccd8P77sGkTvPtu6Makd+9w1dTUqaFhfevWcNf3nDnxC408BxwA48ZBp04wfz6cc44GqxKpABIZHDOBDmbWzsxqEBq/x+ZbZyxwaWR6MDAp0igzFhgaueqqHWHc8xlm1jRypIGZ1QZOBRYm8DNUDbVrh//533cfTJ8ersj673/DZbMvvgijR0ODBonZd6NG4e7yli1DWA0dmvquU0SkSAk7VeXu2WZ2IzCBcEXU0+4+38zuIbTWjwWeAp43s0XAD4RwIbLeq8CXQDZwg7vnmFkL4FkzSyOE3qvuPi5Rn6HKatAg/O//nHOSs79WrUJ49O0LY8fCddeFxn2z5OxfRGJiXgW6f8jIyPBZs2alugwpzscfhyOfHTvCabR77011RSJVlpl96u4ZBS3TneNSfvTpExrM09LgD38IveuKSLmj4JDy5eyzQ0+/AD/7GbzySmrrEZH9KDik/Ln8cvjTn8I978OGhftLNJaHSLmh4JDy6bbb4M9/DqetHnggNJwvWZLqqkQEBYeUV2Zw663wwQehA8WZM8MAUTp1JZJyCg4p3/r0Cd2l/PjH4WbEYcPCeObR3aKISFIpOKT8a9gQxowJfWvVrBm6QenVCz7/PNWViVRJCg6pGMzCjYEzZoQuShYsCOHx2GMailYkyRQcUrEccURo7xg+HHbtguuvDz38btyY6spEqgwFh1Q8deqEez1efhkOPBBefz00nH/8cXy2v2IFPP88XH11GCNdRzQi+6hw3aqL7DF0aOjNd+jQcBTSrx/cc0+4GistreTbWbYsDH87ZUp4XrZs3+W7doXLg0UEUF9VUhlkZYW+rf761/D65JPDEUOLFvuv6x7uB5kyZW9QrFix7zr168Pxx0OHDqFrefdwhDN8eMI/ikh5UVRfVTrikIqvRg34y1/gpJPC0LgTJ4ZBq557LowuuGjR3iOKKVP2H22wYcMQFP37wwknhPfmHbF06BDaUa65JoyUeO65yf50IuWOjjikclmzBn760xAeEIa4/e67fddp1CgExAknhLDo1i2MkliYu++Gu+4KlwJPmBDeJ1LJFXXEoeCQyicnJxyB3HlnmG7SZG9InHACdOlSdFDk5w433hjuI6lXLxy1dO+esPJFygMFh4Kjalq9GjZvDvd9lHVQqJwcuOgiePXVcBTz0Udw6KHxqVOkHNJ4HFI1HXwwdO4cn5EE09JCm8kpp4RTX6edBmvXln27IhWQgqMQ7s4t79zC3LVzU11KSrg7T81+iinLpqS6lPKjZs1wz0hGRrgya+DAcEQjUsUoOArx6vxXeWDaA2Q8kcHdk+8mK6dqjQfxj0/+wfD/G85ZL5/Fum3rUl1O+XHggfD223DYYTB3bhiXfefOVFclklQKjkKcediZ3NDrBrJzs7lryl30fqI3n639LNVlJcXkZZO55d1bAMjMyuS+qfeluKJypmnTcHXVQQeFbt+HDYPs7FRXJZI0Co5C1K1Rl3+d8S/ev/R92jVox9zv5tLriV7cNfmuSn30sWrLKi4cfSE5nsMFnS8A4JGZj7Bi84pi3lnFtG0bwqNBA3jzTbj2WnVNIlWGgqMY/dv2Z95187ix141k52Zz95S7K+3Rx67sXQx+dTDrtq/jlENO4aXzX2JY12Fk5WRx1+S7Ul1e+dO1K4wbB7Vrh67ef/vbVFckkhQKjhKoW6Mu/zzjn5X+6GPE+BFMXz2d1vVb8/L5L5NeLZ17TryH9GrpPDv3WRasW5DqEsuf446D0aPDVVf33Rc6RRSp5BQcMajMRx9Pz3ma/3z6H2qm1eS1C1+jyQFNAGjfqD3DjxpOrudyx/t3pLjKcurMM+Hpp8P0zTfDCy+kth6RBFNwxCjv6GPypZM5pOEhe44+fv/+7yvs0cesb2dx/VvXA/DomY+ScdC+9/zcecKd1E6vzesLXmfm6pmpKLH8u+QSePDBMH355eHKK5FKSsFRSie0PYF5187jpt43kZ2bzT0f3EOvJ3oxZ82cVJcWk/Xb13P+q+ezK2cX1/S8hiuOumK/dQ468CBGHD0CgNsn3p7sEiuOm28OXbpnZ4fBpaZNS3VFIgmh4CiDOjXq8PDpD+85+pj33Tx6P9m7whx9ZOdmM3TMUFZsXsHRBx/NQwMfKnTdXx/3axrUasDEpRN5b8l7SayygrnvPrjiCtixI5zCmj49dPsuUomor6o42Za1jdsn3s4/Z/wTgCOaH8HIQSM5qsVRCd1vWdz23m3c/9H9NKvTjE+v/pSW9VoWuf6fp/6Z2yfeTsZBGcwYPgOLR1celVF2Npx/Powdu3de48ZhfJC8x49+tO/rvEfduqmrWySKOjlMYieHU5ZN4YqxV7Bk45JwVVL/e7it723l7o/sa1++xuDRg0mzNN675D36t+1f7Hu2795O+4fbsyZzDWMuGMP5nc9PfKEV1Y4dYejZiRND31a5uSV7X506+wdM8+bh0azZ3unmzaFWrcR+BqnSFBxJ7h13W9Y2fjPxNzw842EALu9+Of856z9UT6uetBqKsmDdAno/2ZvMrEwePO1Bbj725hK/97GZj3H929dzeOPD+eL6L0ivprHAipWTA+vXh7FC8j/Wrt33dSzdl9Srt2+QFBQuBx8cHun6d5LYKDhS1K36fxf+l2GvDWNH9g5OPeRUxlw4hno16yW9jmhbdm3h6CePZuH6hQzpMoSXz385pqOh3Tm76fRIJxZvXMxT5zxVYGO6lJJ76DQxOlDWrg1HLN99B99/v+/07t0l2256OrRqFe52b9du3+e2bUPXKbGMTyJVgoIjheNxzFg9g7NeOot129dxRPMjePuitzm43sEpqcXdOf/V83lj4Rt0adqFT4Z/Qt0asZ9Tf/nzl7no9YtoWa8l39z0DbXSdcok6dxh48a9QZI/WPIeq1bBt98Wva0aNaB1633DJG+6ceOy1ZmeDgccEE7BHXDA3iF5pdxTcKR4IKclG5dw+oun8/WGr2lZryVvX/Q23Zp3S3odeY3b9WrWY9ZVs+jQuEOptpPrufT4Tw/mfjc35lNdkgI7d8KKFbB0KSxbtvc5b/r775NXS82a+wZJcc+NG0ObNiHE2rQJr8tZe2FllbLgMLOBwENAGvCku/853/KawHNAT2ADMMTdl0WW3Q5cCeQAP3P3CWbWKrJ+c8CBx9298GtII1IdHAAbtm9g0CuD+GjlR9SrWY/XL3ydkw85OWn7f3fxuwx8cSC5nsvYoWM5+/Czy7S9t795mzNfOpPGtRuzZMSSlJ+CkzLYvn3fIIme3ry5bH+od+8O29+2LTyX9e9NnTp7gyQvTKKfmzVTsMRJSoLDzNKAr4FTgVXATGCYu38Ztc71wBHufq2ZDQXOc/chZtYZeBnoDRwEvAccBjQDWrj7bDM7EPgUODd6mwUpD8EBsDN7J5e8cQmjvxxNerV0njz7SS7tfmnC97t803J6Pt6TDTs2cGe/O7nnxHvKvE13p9/IfkxdMZXf9fsdd594dxwqlUrNPRz95AVJXpgU9bxuXQix5cvD85YtRe+jVq19w6RTJ+jbN4wRrwsEYpKq4DgWuMvdB0Re3w7g7vdFrTMhss40M0sH1gJNgdui141eL98+/gv8y93fLaqW8hIcEE7z3PrurTww7QEA7u5/N3f2uzNhl+vu2L2Dvs/0Zfaa2Zze/nT+b9j/kVYtPueZp66YyvHPHE+d6nVYMmIJzeo0i8t242Vn9k7SLK3cXM0mcbBp094jorwwyXtetiy0+xSkbt3QIWW/fuHRq1c4bRZv27bBvHnw2WcwZw7s2gU9ekDv3iG8ateO/z4Lq+Pzz0Mtw4eX6uKHooIjkRF8MLAy6vUq4OjC1nH3bDPbDDSOzP8k33v3aVE2s7bAUcD0gnZuZlcDVwO0bt26lB8h/qpZNf562l9p06ANI8aP4PeTf8+yTcsScrmuu3P929cze81s2jVoxws/fiFuoQHQt3VfzjrsLMZ9PY4/ffgn/jHwH3HbdlnNXD2TM146g6YHNOXDyz+k8QFlbOSV8qFBg/AHuHv3gpdv2RKCZPnycKptzhz48ENYtCiMnzJhQlivZk04+ugQIscfD8ceG0Z3jMX69WH7c+bsDYqvv97/np3nngvP6enQrVsIrd69w6NTp7IdCbmHix/mzg015D1/883e04InnQTt25d+HwWokMduZlYXeA34ubsXeOzq7o8Dj0M44khieSVyY+8baVWvFcNeG8Yznz3Dqi2r4nq5rrvz2KzHGPnZSGqn1+aNIW/QqHajuGw72h9P+iNvff0Wj816jF8c8wvaNGgT933Eavqq6Zz2wmls2bWF9dvXM3j0YCZcPIEaaTVSXZokWr164Y9zt3wXn3z7bQiQDz4Iz59/HqY/+CAsT0sLRwZ5QdK3794rytzD0UxeOOQ9Vq/ef//p6WGclqOOCuFWqxbMmgUzZsD8+TldWMsAABPuSURBVHvf+/jjYf0DDoCePfeGSa9e4Yq2gs5A7N4NCxfuGxBz54YAK6iOzp3hyCMTMsBYhTtVZWbVgXHABHf/W0lqKU+nqvKL5+W6W3ZtYdLSSUxYNIEJiyewdNNSAJ4/73kuPuLieJa9j4tfv5gXP3+Ry7pfxjODnknYfkpi2sppDHhhAFuztnLO4ecwc/VM1mSu4eoeV/Pvs/5d7u7glxTZsAE++mhveMyeHW7UjNa1awiPuXPDKbL86tTZe/Rz1FHh0aVL4afAtm0L+5k5MwTJzJmwZMn+6zVuvDdIGjQIp5vmzg3BU1C/Zw0bhoDo3n3vc6dOZT4Vl6o2jnRC4/jJwGpC4/hF7j4/ap0bgG5RjeM/dvcLzawL8BJ7G8cnAh2AXOBZ4Ad3/3lJaynPwQGlv1w313OZs2YOExZPYPyi8UxbNY3s3L1jXzeq3Yhb+tzCbX1vS2T5LNm4hMP/dTi5nsu8a+fRpVmXhO6vMB+v/JiBLwxka9ZWLuxyIS+c9wJz1s7hhJEnsDN7Jw8NfIifHf2zlNQm5VxmZujNOC9Ipk8P7RN5mjXbGw55QdG+fdlvnFy/PgRIdJgUdXl0+/b7h0TLlgm5kiyVl+OeAfyDcDnu0+7+RzO7B5jl7mPNrBbwPKGt4gdgqLsvibz3t8AVQDbhlNT/zKwv8CHwOSFEAH7j7kUOflDegwNKfrnu2sy1vLP4HSYsnsC7i99l3fZ1e5alWRrHtDyGAYcOYED7AfRs0TOubRpFueGtG3h01qOc2/Fc3hjyRlL2GW3qiqmc/uLpZGZlMqzrMJ4777k93aHk3bBYzarx1kVvMbD9wKTXJxXMrl3hj/jWreEPdIsWybnM1z3cc5MXJFu3htNu3buH51jbYcpANwBWgOCAgi/XHdZtGB+t+IgJi8Ppp/yjDbau35oBhw5gYPuBnNTuJBrUapCS2tdsXUP7f7Zn++7tfHLlJxzdMv91EInzwfIPOOPFM9i2exs/6fYTRp47cr8+tH73/u+494N7qVezHp9c+QmdmnZKWn0iFZGCo4IEB+x/ue4B1Q9g++7te5bXTq9N/7b99xxVHN748HJz3v63E3/Ln6b+if5t+zPpkklJqWvyssmc+dKZbN+9nZ8e8VOeGfRMgUdZuZ7LhaMv5LUFr3Fow0OZPny6rrQSKYKCowIFR55HZjzCz8b/jFzPpWuzriEoDh3A8W2OL7d9Q23auYlDHjqEjTs3MuHiCZx26GkJ3d+kpZM466Wz2JG9g8u6X8aTZz9Z5Km5bVnbOP6Z45mzdg792/bXlVYiRVBwVMDgAFj8w2JqpddKWaeIpfGXj/7Cre/dSs8WPZlx1QyqWWJ6XX1vyXuc/fLZ7MzeyRXdr+CJc54o0b5WbVlFryd6sTZzra60EilCUcGhvpTLsUMbHVqhQgPC/Skt6rbg0zWf8tqXryVkH+8sfmdPaFzV46oShwZAy3ot+e/Q/1IrvRaPz358z4iNIlJyCg6JqwOqH8DvT/g9AHe8f8c+lwfHw/hF4znn5XPYmb2Ta3tey7/P+nfMRzW9D+7N0+c8DcAvJvyCCYsmxLVGkcpOwSFxd8VRV9C+UXu+3vA1/5z+T3Jyc4p/Uwm8/c3bDHplELtydnF9xvU8euajpT4VNqzbMO44/g5yPZchY4awcP3CuNQoUhUoOCTuqqdV594T7wXg5ndupvFfGnPOy+fwt2l/Y86aOaUKknFfj+O8UeeRlZPFjb1u5F9n/KvMbRN3n3g353c6n827NnPWS2exYfuGMm1PpKpQ47gkRK7nctfku3hh3gt7uj7J06BWA/q16Uf/Nv05sd2JHNH8iCKPHMZ+NZbBrw5md+5uRhw9gr8P+HvcGrTzX2n1zsXvqDddEXRVlYIjxZZvWs6U5VN4f9n7TF42mWWblu2zvGGthvRr048T255I/7b96da8254geXPhm1w4+kJ25+7m5mNu5oHTHoj7VVDRV1pd0/MaHjvzsaRcabUtaxsrt6xk5eaVrNqyas/0yi3hsWrLKg5vfDj/Puvf9GjRI+H1iERTcCg4ypVlm5YxedlkJi+bzPvL3mfF5hX7LG9UuxH92vSjY+OOPDDtAbJzs7mlzy3cf8r9CfuDPn3VdE4YeQK7cnbx8MCHuenom8q0PXdn9dbVLPph0d4wiAqFlZtXsnFnIWNH5JNeLZ07jr+D3xz/Gx0NSdIoOBQc5drSjUtDkCyfzPtL32fllpX7LL/1uFu57+T7En4UEN2n1f9+8r+YbmD8LvM7Zn07KzzWhOe1mWuLfE/NtJq0rNeSVvVb0apeeES/blanGfd/dD8PTQ+jI/do0YNnz32Wrs26lulzipSEgkPBUWG4O0s3hSD5cMWHHNn8SEYcPSJpN+ndOelO/vDhH6hfsz6fDP+Ejk067rfOhu0b+HTNp3uD4ttZ+4UdhLacLk277BMMe6brt6LpAU1L9LneX/o+l//3cpZvXk6NtBrc0/8eftXnV0nrwFKqJgWHgkNKKLpPq/aN2vPuT99l6cal+xxJLNm4/xgKdWvUpWeLnmQclEGvg3qRcVAGhzQ8JG6Bt3XXVn75zi95YvYTABzb8lhGnjuSwxofFpfti+Sn4FBwSAyir7QqSO302hzV4igyWmTQ6+AQEoc1Pixh3atEG79oPMPHDmf11tXUTq/NfSffx01H35SUfUvVouBQcEiMVm1ZxXFPH8fazLUc2fzIfY4kOjXttF+37cm0ccdGRowfwfPzngegf9v+PH3O07Rr2C5lNUVbm7mWMV+O4bUFr5HruQzrOowhXYbQsHbDVJcmMVBwKDikFHbn7AYot1cyvbnwTa4Zdw3fb/ueujXq8uBpD3JVj6tS0mnj+u3reX3B64yaP4rJyyaT67n7LK+ZVpNzO57LZd0v49RDTlX7TIJlZmUy7utxTFo6if+c9Z9S/UwoOBQcUkmt27aO6966jtcWhA4lBxw6gCfPeZKW9VomfN+bdm7izYVvMmr+KN5b8t6efsmqV6vOwPYDGdJlCADPzn2W95a8hxP+1hx04EH89Iifcln3ywq8+EBKZ8uuLYz7ehyjvxzN+EXj2Zm9E4AZw2fQ6+BeMW9PwaHgkErM3Xnli1e44e0b2LhzI/Vr1ufh0x/mp0f8NO5HH5lZmYz9aiyj5o9i/KLxZOVkAWHY4lMOOYUhXYZwbsdz9zsttXLzSp6f9zwjPxvJNz98s2f+MS2P4bIjL2NI1yEpG72yItu8czNjvxrLmAVjmLBoArty9o6T3qdVHy7ofAEXdbuIZnWaxbxtBYeCQ6qANVvXcNX/XcVb37wFwKDDB3H/KffT5IAm1K1RlxppNUoVJDt27+Ctb95i1PxRjPt63J7/yRpG/7b9GdJlCD/u9GOa1mla7LbcnWmrpvHMnGcYNX8UW7O2AuFU1nmdzuOyIy/jlENOielU1vbd21mxeQXLNi1j+ablLN8ceWxaTnq1dPq06kPf1n05tuWxlaKdZeOOjYz9aiyjvxzNO4vfYXduOKVqGH1b92Vw58Gc3+n8Mg/JoOBQcEgV4e6M/GwkI8aP2PNHOU+apVG3Rl3q1KhDnep19kzXrVGXOtXrhOnqe5fXqVGHOWvnMParsWRmZe7ZznGtjmNIlyEM7jyYFge2KHWt23dv540FbzBy7kgmLpm4z6msS464hEu7X0rHJh3ZvHMzyzcv3y8Y8l6v276uxPvs2qwrfVv1pW/r8Ghdv3WFGMjrhx0/8ObCNxnz5RjeW/LenrCoZtXo16YfgzsN5sedflymf4/8FBwKDqliVmxewYjxI5i5eibbdm8jMyuzTGOjZByUwdAuQ7mgywW0rt86jpUGKzav4Pm5zzNy7kgW/bBoz/wDaxy4XwDmV71adVrXb02bBm1oUz882jZoS5sGbdi6aysfrfyIqSumMvPbmXtOreVpWa8lx7U6bk+QdGvWLaUN97tzdrNl15Y9j5nfzmT0l6OZtHTSnn+/alaNE9ueyODOgzmv43k0r9s8IbUoOBQcImTlZLEtK4RIXphsy9pW6HRmViY/qvsjBncezKGNDk1Kje7Oxys/ZuRnI/ecyqqdXntPEOQPhjb12/Cjuj8q0R/7ndk7+fTbT5m6YipTV07loxUf7ddf2IE1DqRPqz57wqRjk47kei7Zudn7PHI8Z/95uTn7rbNj9449IbB51+Z9QiH69eadYXpH9o4Ca0+zNE5qdxIXdL6AczueW6LTgmWl4FBwiFQ4O7N3kpmVSePajRNyOinXc1mwbgFTV0zdc1SSfwiAZKtm1ahXs96eR5v6bTiv43mc2/FcGh/QOKm1KDgUHCJSAqu3rN4TIlNXTGX11tWkV0snzdJIr5a+zyOt2v7z8q9bM70m9WvW3ycMol/Xr7XvsjrV65SbNhcFh4JDRCQmRQWHOrgREZGYKDhERCQmCg4REYmJgkNERGKi4BARkZgoOEREJCYKDhERiYmCQ0REYlIlbgA0s3XA8lK+vQmwPo7lxJvqKxvVVzaqr2zKc31t3L3ATrGqRHCUhZnNKuzuyfJA9ZWN6isb1Vc25b2+wuhUlYiIxETBISIiMVFwFO/xVBdQDNVXNqqvbFRf2ZT3+gqkNg4REYmJjjhERCQmCg4REYmJgiPCzAaa2VdmtsjMbitgeU0zGxVZPt3M2iaxtlZm9r6ZfWlm881sRAHr9DezzWb2WeTxu2TVF9n/MjP7PLLv/UbNsuDhyPc3z8x6JLG2w6O+l8/MbIuZ/TzfOkn9/szsaTP73sy+iJrXyMzeNbNvIs8NC3nvpZF1vjGzS5NY31/NbGHk3+8NM2tQyHuL/FlIYH13mdnqqH/DMwp5b5G/6wmsb1RUbcvM7LNC3pvw76/M3L3KP4A0YDFwCFADmAt0zrfO9cC/I9NDgVFJrK8F0CMyfSDwdQH19QfGpfA7XAY0KWL5GcD/AAOOAaan8N96LeHmppR9f0A/oAfwRdS8vwC3RaZvA+4v4H2NgCWR54aR6YZJqu80ID0yfX9B9ZXkZyGB9d0F/KoE//5F/q4nqr58yx8Efpeq76+sDx1xBL2BRe6+xN2zgFeAQfnWGQQ8G5keA5xsSRoc2N3XuPvsyPRWYAFwcDL2HUeDgOc8+ARoYGYtUlDHycBidy9tTwJx4e4fAD/kmx39M/YscG4Bbx0AvOvuP7j7RuBdYGAy6nP3d9w9O/LyE6BlvPdbUoV8fyVRkt/1MiuqvsjfjQuBl+O932RRcAQHAyujXq9i/z/Me9aJ/PJsBhonpbookVNkRwHTC1h8rJnNNbP/mVmXpBYGDrxjZp+a2dUFLC/Jd5wMQyn8FzaV3x9Ac3dfE5leCzQvYJ3y8j1eQTiCLEhxPwuJdGPkVNrThZzqKw/f3/HAd+7+TSHLU/n9lYiCowIxs7rAa8DP3X1LvsWzCadfjgT+CbyZ5PL6unsP4HTgBjPrl+T9F8vMagDnAKMLWJzq728fHs5ZlMtr5c3st0A28GIhq6TqZ+Ex4FCgO7CGcDqoPBpG0Ucb5f53ScERrAZaRb1uGZlX4Dpmlg7UBzYkpbqwz+qE0HjR3V/Pv9zdt7h7ZmT6baC6mTVJVn3uvjry/D3wBuGUQLSSfMeJdjow292/y78g1d9fxHd5p+8iz98XsE5Kv0czuww4C/hJJNz2U4KfhYRw9+/cPcfdc4EnCtlvqr+/dODHwKjC1knV9xcLBUcwE+hgZu0i/ysdCozNt85YIO8KlsHApMJ+ceItck70KWCBu/+tkHV+lNfmYma9Cf+2SQk2M6tjZgfmTRMaUb/It9pY4JLI1VXHAJujTsskS6H/00vl9xcl+mfsUuC/BawzATjNzBpGTsWcFpmXcGY2EPg1cI67by9knZL8LCSqvug2s/MK2W9JftcT6RRgobuvKmhhKr+/mKS6db68PAhX/XxNuOLit5F59xB+SQBqEU5xLAJmAIcksba+hNMW84DPIo8zgGuBayPr3AjMJ1wl8gnQJ4n1HRLZ79xIDXnfX3R9BjwS+X4/BzKS/O9bhxAE9aPmpez7IwTYGmA34Tz7lYQ2s4nAN8B7QKPIuhnAk1HvvSLyc7gIuDyJ9S0itA/k/QzmXWV4EPB2UT8LSarv+cjP1jxCGLTIX1/k9X6/68moLzJ/ZN7PXNS6Sf/+yvpQlyMiIhITnaoSEZGYKDhERCQmCg4REYmJgkNERGKi4BARkZgoOERKycxy8vW6G7eeVs2sbXTPqiLlSXqqCxCpwHa4e/dUFyGSbDriEImzyHgKf4mMqTDDzNpH5rc1s0mRTvgmmlnryPzmkfEt5kYefSKbSjOzJyyMwfKOmdWOrP8zC2OzzDOzV1L0MaUKU3CIlF7tfKeqhkQt2+zu3YB/Af+IzPsn8Ky7H0HoIPDhyPyHgSkeOljsQbhjGKAD8Ii7dwE2AedH5t8GHBXZzrWJ+nAihdGd4yKlZGaZ7l63gPnLgJPcfUmkc8q17t7YzNYTusHYHZm/xt2bmNk6oKW774raRlvCuBsdIq9vBaq7+x/MbDyQSejB902PdM4okiw64hBJDC9kOha7oqZz2NsmeSah368ewMxIj6siSaPgEEmMIVHP0yLTHxN6YwX4CfBhZHoicB2AmaWZWf3CNmpm1YBW7v4+cCuhe//9jnpEEkn/UxEpvdpm9lnU6/HunndJbkMzm0c4ahgWmXcT8IyZ3QKsAy6PzB8BPG5mVxKOLK4j9KxakDTghUi4GPCwu2+K2ycSKQG1cYjEWaSNI8Pd16e6FpFE0KkqERGJiY44REQkJjriEBGRmCg4REQkJgoOERGJiYJDRERiouAQEZGY/D+XkRxt8PqNSgAAAABJRU5ErkJggg==\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "mS6SPIGNpskz",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "29af7065-9226-443b-d73f-74a142dcf23c"
      },
      "source": [
        "targets = test[target_col][window_len:]\n",
        "preds = model.predict(X_test).squeeze()\n",
        "mean_absolute_error(preds, y_test)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.027840373111286353"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sbhTW5T6zVAU",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ace7f5ff-4e40-4555-a68f-bd0176f43e30"
      },
      "source": [
        "from sklearn.metrics import mean_squared_error\n",
        "MAE=mean_squared_error(preds, y_test)\n",
        "MAE\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.0014670034539688284"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jnFOCI9ezb8T",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "52cdd6a6-1ad2-4b44-f6c3-3be81e095a23"
      },
      "source": [
        "from sklearn.metrics import r2_score\n",
        "R2=r2_score(y_test, preds)\n",
        "R2"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.6824564946267051"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "4jU0wERepsk2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 428
        },
        "outputId": "f9168fa0-fa1f-4628-c56d-ae8636c4fdd6"
      },
      "source": [
        "preds = test[target_col].values[:-window_len] * (preds + 1)\n",
        "preds = pd.Series(index=targets.index, data=preds)\n",
        "line_plot(targets, preds, 'actual', 'prediction', lw=3)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 936x504 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}