LP5_DL_Assignment_1.ipynb

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      "source": [
        "\n",
        "# Importing Necesarry Packages\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from sklearn.datasets import load_boston\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn.metrics import r2_score\n",
        "from sklearn.metrics import mean_squared_error\n",
        "import keras\n",
        "from keras.layers import Dense, Activation,Dropout\n",
        "from keras.models import Sequential\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\") "
      ]
    },
    {
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      "source": [
        "!pip install scikit-learn==1.1.3"
      ],
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      "id": "cyFwct3x7dGn",
      "execution_count": 5,
      "outputs": [
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          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: scikit-learn==1.1.3 in /usr/local/lib/python3.10/dist-packages (1.1.3)\n",
            "Requirement already satisfied: numpy>=1.17.3 in /usr/local/lib/python3.10/dist-packages (from scikit-learn==1.1.3) (1.22.4)\n",
            "Requirement already satisfied: scipy>=1.3.2 in /usr/local/lib/python3.10/dist-packages (from scikit-learn==1.1.3) (1.10.1)\n",
            "Requirement already satisfied: joblib>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn==1.1.3) (1.2.0)\n",
            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn==1.1.3) (3.1.0)\n"
          ]
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              "      CRIM    ZN  INDUS  CHAS    NOX     RM   AGE     DIS  RAD    TAX  \\\n",
              "0  0.00632  18.0   2.31   0.0  0.538  6.575  65.2  4.0900  1.0  296.0   \n",
              "1  0.02731   0.0   7.07   0.0  0.469  6.421  78.9  4.9671  2.0  242.0   \n",
              "2  0.02729   0.0   7.07   0.0  0.469  7.185  61.1  4.9671  2.0  242.0   \n",
              "3  0.03237   0.0   2.18   0.0  0.458  6.998  45.8  6.0622  3.0  222.0   \n",
              "4  0.06905   0.0   2.18   0.0  0.458  7.147  54.2  6.0622  3.0  222.0   \n",
              "\n",
              "   PTRATIO       B  LSTAT  PRICE  \n",
              "0     15.3  396.90   4.98   24.0  \n",
              "1     17.8  396.90   9.14   21.6  \n",
              "2     17.8  392.83   4.03   34.7  \n",
              "3     18.7  394.63   2.94   33.4  \n",
              "4     18.7  396.90   5.33   36.2  "
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              "      <td>18.7</td>\n",
              "      <td>394.63</td>\n",
              "      <td>2.94</td>\n",
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              "      <td>7.147</td>\n",
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          },
          "metadata": {},
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        }
      ],
      "source": [
        "# Loading Data\n",
        "boston = load_boston()\n",
        "data = pd.DataFrame(boston.data)\n",
        "data.columns = boston.feature_names\n",
        "data['PRICE'] = boston.target \n",
        "data.head()"
      ]
    },
    {
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      "execution_count": 7,
      "id": "3d55efd3",
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          "name": "stdout",
          "text": [
            "(506, 14)\n",
            "CRIM       float64\n",
            "ZN         float64\n",
            "INDUS      float64\n",
            "CHAS       float64\n",
            "NOX        float64\n",
            "RM         float64\n",
            "AGE        float64\n",
            "DIS        float64\n",
            "RAD        float64\n",
            "TAX        float64\n",
            "PTRATIO    float64\n",
            "B          float64\n",
            "LSTAT      float64\n",
            "PRICE      float64\n",
            "dtype: object\n",
            "CRIM       0\n",
            "ZN         0\n",
            "INDUS      0\n",
            "CHAS       0\n",
            "NOX        0\n",
            "RM         0\n",
            "AGE        0\n",
            "DIS        0\n",
            "RAD        0\n",
            "TAX        0\n",
            "PTRATIO    0\n",
            "B          0\n",
            "LSTAT      0\n",
            "PRICE      0\n",
            "dtype: int64\n",
            "             CRIM          ZN       INDUS        CHAS         NOX          RM  \\\n",
            "count  506.000000  506.000000  506.000000  506.000000  506.000000  506.000000   \n",
            "mean     3.613524   11.363636   11.136779    0.069170    0.554695    6.284634   \n",
            "std      8.601545   23.322453    6.860353    0.253994    0.115878    0.702617   \n",
            "min      0.006320    0.000000    0.460000    0.000000    0.385000    3.561000   \n",
            "25%      0.082045    0.000000    5.190000    0.000000    0.449000    5.885500   \n",
            "50%      0.256510    0.000000    9.690000    0.000000    0.538000    6.208500   \n",
            "75%      3.677083   12.500000   18.100000    0.000000    0.624000    6.623500   \n",
            "max     88.976200  100.000000   27.740000    1.000000    0.871000    8.780000   \n",
            "\n",
            "              AGE         DIS         RAD         TAX     PTRATIO           B  \\\n",
            "count  506.000000  506.000000  506.000000  506.000000  506.000000  506.000000   \n",
            "mean    68.574901    3.795043    9.549407  408.237154   18.455534  356.674032   \n",
            "std     28.148861    2.105710    8.707259  168.537116    2.164946   91.294864   \n",
            "min      2.900000    1.129600    1.000000  187.000000   12.600000    0.320000   \n",
            "25%     45.025000    2.100175    4.000000  279.000000   17.400000  375.377500   \n",
            "50%     77.500000    3.207450    5.000000  330.000000   19.050000  391.440000   \n",
            "75%     94.075000    5.188425   24.000000  666.000000   20.200000  396.225000   \n",
            "max    100.000000   12.126500   24.000000  711.000000   22.000000  396.900000   \n",
            "\n",
            "            LSTAT       PRICE  \n",
            "count  506.000000  506.000000  \n",
            "mean    12.653063   22.532806  \n",
            "std      7.141062    9.197104  \n",
            "min      1.730000    5.000000  \n",
            "25%      6.950000   17.025000  \n",
            "50%     11.360000   21.200000  \n",
            "75%     16.955000   25.000000  \n",
            "max     37.970000   50.000000  \n"
          ]
        }
      ],
      "source": [
        "# Data Exploration\n",
        "print(data.shape)\n",
        "print(data.dtypes)\n",
        "print(data.isnull().sum())\n",
        "print(data.describe())"
      ]
    },
    {
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      "execution_count": 8,
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          "height": 1000
        }
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      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 8
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 500x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x1200 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Data Visualization\n",
        "sns.displot(data.PRICE)\n",
        "\n",
        "correlation = data.corr()\n",
        "correlation.loc['PRICE']\n",
        "\n",
        "fig,axes = plt.subplots(figsize=(15,12))\n",
        "sns.heatmap(correlation,square = True,annot = True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "id": "3c3c3062",
      "metadata": {
        "id": "3c3c3062"
      },
      "outputs": [],
      "source": [
        "# Splitting Data into testing and training data\n",
        "X = data.iloc[:,:-1]\n",
        "y= data.PRICE\n",
        "X_train, X_test, y_train, y_test = train_test_split(X,y, test_size = 0.2, random_state = 4)\n",
        "\n",
        "# Normalizing the data\n",
        "sc = StandardScaler()\n",
        "X_train = sc.fit_transform(X_train)\n",
        "X_test = sc.transform(X_test)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "id": "1f2f8bd3",
      "metadata": {
        "id": "1f2f8bd3",
        "outputId": "5ab0f82e-bc70-4ee5-d912-229d898cf9f5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " dense (Dense)               (None, 128)               1792      \n",
            "                                                                 \n",
            " dense_1 (Dense)             (None, 64)                8256      \n",
            "                                                                 \n",
            " dense_2 (Dense)             (None, 32)                2080      \n",
            "                                                                 \n",
            " dense_3 (Dense)             (None, 16)                528       \n",
            "                                                                 \n",
            " dense_4 (Dense)             (None, 1)                 17        \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 12,673\n",
            "Trainable params: 12,673\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ]
        }
      ],
      "source": [
        "# Model Building\n",
        "model = Sequential()\n",
        "model.add(Dense(128,activation  = 'relu',input_dim =13))\n",
        "model.add(Dense(64,activation  = 'relu'))\n",
        "model.add(Dense(32,activation  = 'relu'))\n",
        "model.add(Dense(16,activation  = 'relu'))\n",
        "model.add(Dense(1))\n",
        "model.compile(optimizer = 'adam',loss = 'mean_squared_error')\n",
        "model.summary()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "id": "f285526d",
      "metadata": {
        "scrolled": false,
        "id": "f285526d",
        "outputId": "cd80185c-12d4-4c34-c29e-21a951419c33",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/200\n",
            "13/13 [==============================] - 1s 3ms/step - loss: 543.5594\n",
            "Epoch 2/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 447.2952\n",
            "Epoch 3/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 252.9198\n",
            "Epoch 4/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 84.5379\n",
            "Epoch 5/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 51.7606\n",
            "Epoch 6/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 32.5212\n",
            "Epoch 7/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 24.7836\n",
            "Epoch 8/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 21.1458\n",
            "Epoch 9/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 19.5076\n",
            "Epoch 10/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 18.0832\n",
            "Epoch 11/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 17.5749\n",
            "Epoch 12/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 16.2284\n",
            "Epoch 13/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 15.3629\n",
            "Epoch 14/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 14.5727\n",
            "Epoch 15/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 14.0604\n",
            "Epoch 16/200\n",
            "13/13 [==============================] - 0s 4ms/step - loss: 14.2048\n",
            "Epoch 17/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 13.2472\n",
            "Epoch 18/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 13.0326\n",
            "Epoch 19/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 12.3411\n",
            "Epoch 20/200\n",
            "13/13 [==============================] - 0s 4ms/step - loss: 11.9793\n",
            "Epoch 21/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 11.8390\n",
            "Epoch 22/200\n",
            "13/13 [==============================] - 0s 4ms/step - loss: 11.4758\n",
            "Epoch 23/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 11.3799\n",
            "Epoch 24/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 10.9624\n",
            "Epoch 25/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 10.8080\n",
            "Epoch 26/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 10.8890\n",
            "Epoch 27/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 10.4642\n",
            "Epoch 28/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 9.9496\n",
            "Epoch 29/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 9.7272\n",
            "Epoch 30/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 9.6598\n",
            "Epoch 31/200\n",
            "13/13 [==============================] - 0s 4ms/step - loss: 9.8143\n",
            "Epoch 32/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 9.2965\n",
            "Epoch 33/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 9.1502\n",
            "Epoch 34/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 8.9508\n",
            "Epoch 35/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 9.3155\n",
            "Epoch 36/200\n",
            "13/13 [==============================] - 0s 2ms/step - loss: 9.1956\n",
            "Epoch 37/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 8.8950\n",
            "Epoch 38/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 8.6873\n",
            "Epoch 39/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 8.3605\n",
            "Epoch 40/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 7.9757\n",
            "Epoch 41/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 7.8511\n",
            "Epoch 42/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 7.5915\n",
            "Epoch 43/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 7.5034\n",
            "Epoch 44/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 7.4278\n",
            "Epoch 45/200\n",
            "13/13 [==============================] - 0s 4ms/step - loss: 7.4035\n",
            "Epoch 46/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 7.3011\n",
            "Epoch 47/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 7.1948\n",
            "Epoch 48/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 6.7771\n",
            "Epoch 49/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 6.6370\n",
            "Epoch 50/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 6.6152\n",
            "Epoch 51/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 6.5547\n",
            "Epoch 52/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 6.5068\n",
            "Epoch 53/200\n",
            "13/13 [==============================] - 0s 4ms/step - loss: 6.2597\n",
            "Epoch 54/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 6.1241\n",
            "Epoch 55/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 6.4913\n",
            "Epoch 56/200\n",
            "13/13 [==============================] - 0s 2ms/step - loss: 5.9780\n",
            "Epoch 57/200\n",
            "13/13 [==============================] - 0s 2ms/step - loss: 6.1544\n",
            "Epoch 58/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 5.7926\n",
            "Epoch 59/200\n",
            "13/13 [==============================] - 0s 4ms/step - loss: 5.7146\n",
            "Epoch 60/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 5.8690\n",
            "Epoch 61/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 6.1040\n",
            "Epoch 62/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 5.5559\n",
            "Epoch 63/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 5.4735\n",
            "Epoch 64/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 5.2070\n",
            "Epoch 65/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 5.1415\n",
            "Epoch 66/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 4.8747\n",
            "Epoch 67/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 4.8613\n",
            "Epoch 68/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 4.8156\n",
            "Epoch 69/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 4.7094\n",
            "Epoch 70/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 4.5729\n",
            "Epoch 71/200\n",
            "13/13 [==============================] - 0s 4ms/step - loss: 4.7063\n",
            "Epoch 72/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 4.6944\n",
            "Epoch 73/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 4.4388\n",
            "Epoch 74/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 4.6444\n",
            "Epoch 75/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 4.4011\n",
            "Epoch 76/200\n",
            "13/13 [==============================] - 0s 4ms/step - loss: 4.6692\n",
            "Epoch 77/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 4.5761\n",
            "Epoch 78/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 4.4116\n",
            "Epoch 79/200\n",
            "13/13 [==============================] - 0s 2ms/step - loss: 4.2576\n",
            "Epoch 80/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 4.3408\n",
            "Epoch 81/200\n",
            "13/13 [==============================] - 0s 2ms/step - loss: 4.3872\n",
            "Epoch 82/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 4.4313\n",
            "Epoch 83/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 4.0737\n",
            "Epoch 84/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 3.7575\n",
            "Epoch 85/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 3.8850\n",
            "Epoch 86/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 3.7731\n",
            "Epoch 87/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 3.8064\n",
            "Epoch 88/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 3.7380\n",
            "Epoch 89/200\n",
            "13/13 [==============================] - 0s 4ms/step - loss: 3.8341\n",
            "Epoch 90/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 3.8333\n",
            "Epoch 91/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 4.0507\n",
            "Epoch 92/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 3.4602\n",
            "Epoch 93/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 3.2958\n",
            "Epoch 94/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 3.4342\n",
            "Epoch 95/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 3.5815\n",
            "Epoch 96/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 3.9246\n",
            "Epoch 97/200\n",
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            "Epoch 98/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 3.1284\n",
            "Epoch 99/200\n",
            "13/13 [==============================] - 0s 2ms/step - loss: 3.2322\n",
            "Epoch 100/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 3.3772\n",
            "Epoch 101/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 3.2850\n",
            "Epoch 102/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 3.1533\n",
            "Epoch 103/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 3.1392\n",
            "Epoch 104/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.9314\n",
            "Epoch 105/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.9122\n",
            "Epoch 106/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.8809\n",
            "Epoch 107/200\n",
            "13/13 [==============================] - 0s 4ms/step - loss: 3.1026\n",
            "Epoch 108/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.9683\n",
            "Epoch 109/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.8418\n",
            "Epoch 110/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.7979\n",
            "Epoch 111/200\n",
            "13/13 [==============================] - 0s 4ms/step - loss: 2.7499\n",
            "Epoch 112/200\n",
            "13/13 [==============================] - 0s 4ms/step - loss: 2.6783\n",
            "Epoch 113/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.6260\n",
            "Epoch 114/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.7788\n",
            "Epoch 115/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.8095\n",
            "Epoch 116/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 3.4805\n",
            "Epoch 117/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.8857\n",
            "Epoch 118/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.8118\n",
            "Epoch 119/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.6094\n",
            "Epoch 120/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.7203\n",
            "Epoch 121/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.4688\n",
            "Epoch 122/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.5056\n",
            "Epoch 123/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.4870\n",
            "Epoch 124/200\n",
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            "Epoch 125/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.5009\n",
            "Epoch 126/200\n",
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            "Epoch 127/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.2765\n",
            "Epoch 128/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.2993\n",
            "Epoch 129/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.1589\n",
            "Epoch 130/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.2546\n",
            "Epoch 131/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.1749\n",
            "Epoch 132/200\n",
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            "Epoch 133/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.4869\n",
            "Epoch 134/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.5429\n",
            "Epoch 135/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.2510\n",
            "Epoch 136/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.0663\n",
            "Epoch 137/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.2254\n",
            "Epoch 138/200\n",
            "13/13 [==============================] - 0s 4ms/step - loss: 2.1651\n",
            "Epoch 139/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 1.9526\n",
            "Epoch 140/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.0794\n",
            "Epoch 141/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.1722\n",
            "Epoch 142/200\n",
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            "Epoch 143/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 2.1384\n",
            "Epoch 144/200\n",
            "13/13 [==============================] - 0s 2ms/step - loss: 2.0967\n",
            "Epoch 145/200\n",
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            "Epoch 146/200\n",
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            "Epoch 147/200\n",
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            "Epoch 148/200\n",
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            "Epoch 149/200\n",
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            "Epoch 150/200\n",
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            "Epoch 151/200\n",
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            "Epoch 152/200\n",
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            "Epoch 153/200\n",
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            "Epoch 154/200\n",
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            "Epoch 155/200\n",
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            "Epoch 156/200\n",
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            "Epoch 157/200\n",
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            "Epoch 158/200\n",
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            "Epoch 159/200\n",
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            "Epoch 160/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 1.6209\n",
            "Epoch 161/200\n",
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            "Epoch 162/200\n",
            "13/13 [==============================] - 0s 2ms/step - loss: 1.5732\n",
            "Epoch 163/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 1.6008\n",
            "Epoch 164/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 1.5388\n",
            "Epoch 165/200\n",
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            "Epoch 166/200\n",
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            "Epoch 167/200\n",
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            "Epoch 168/200\n",
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            "Epoch 169/200\n",
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            "Epoch 170/200\n",
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            "Epoch 171/200\n",
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            "Epoch 172/200\n",
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            "Epoch 173/200\n",
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            "Epoch 174/200\n",
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            "Epoch 175/200\n",
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            "Epoch 176/200\n",
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            "Epoch 177/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 1.2495\n",
            "Epoch 178/200\n",
            "13/13 [==============================] - 0s 4ms/step - loss: 1.2661\n",
            "Epoch 179/200\n",
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            "Epoch 180/200\n",
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            "Epoch 181/200\n",
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            "Epoch 182/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 1.3870\n",
            "Epoch 183/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 1.6022\n",
            "Epoch 184/200\n",
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            "Epoch 185/200\n",
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            "Epoch 186/200\n",
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            "Epoch 187/200\n",
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            "Epoch 188/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 1.2342\n",
            "Epoch 189/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 1.2369\n",
            "Epoch 190/200\n",
            "13/13 [==============================] - 0s 4ms/step - loss: 1.1834\n",
            "Epoch 191/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 1.3087\n",
            "Epoch 192/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 1.2256\n",
            "Epoch 193/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 1.1968\n",
            "Epoch 194/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 1.0619\n",
            "Epoch 195/200\n",
            "13/13 [==============================] - 0s 4ms/step - loss: 1.1304\n",
            "Epoch 196/200\n",
            "13/13 [==============================] - 0s 3ms/step - loss: 1.0764\n",
            "Epoch 197/200\n",
            "13/13 [==============================] - 0s 4ms/step - loss: 1.0869\n",
            "Epoch 198/200\n",
            "13/13 [==============================] - 0s 6ms/step - loss: 1.0861\n",
            "Epoch 199/200\n",
            "13/13 [==============================] - 0s 6ms/step - loss: 1.2810\n",
            "Epoch 200/200\n",
            "13/13 [==============================] - 0s 5ms/step - loss: 1.2445\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.callbacks.History at 0x7f7e1fc9d180>"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ],
      "source": [
        "# Fitting the data to the model\n",
        "model.fit(X_train, y_train, epochs = 200)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "id": "52ec3d3e",
      "metadata": {
        "id": "52ec3d3e",
        "outputId": "0d0db179-b976-47d4-a443-f373d80f5533",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "4/4 [==============================] - 0s 4ms/step\n",
            "R2 Score =  0.8993657890528004\n",
            "RMSE Score =  3.0574227376387824\n"
          ]
        }
      ],
      "source": [
        "# Evaluating the model\n",
        "y_pred = model.predict(X_test)\n",
        "r2 = r2_score(y_test, y_pred)\n",
        "rmse = (np.sqrt(mean_squared_error(y_test, y_pred)))\n",
        "print(\"R2 Score = \", r2)\n",
        "print(\"RMSE Score = \", rmse)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "f81f410b",
      "metadata": {
        "id": "f81f410b"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "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": "3.10.9"
    },
    "colab": {
      "provenance": []
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}