Project_1_MLP.ipynb

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        "import numpy as np\n",
        "import pandas as pd\n",
        "import pandas_datareader.data as web\n",
        "import matplotlib.pyplot as plt\n",
        "from keras.models import Sequential, Model\n",
        "from keras.layers import Dense, Input\n",
        "from tensorflow.keras.layers import concatenate"
      ]
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      "source": [
        "df = pd.read_csv('https://raw.githubusercontent.com/thieu1995/ai/master/data/preprocessing/international-airline-passengers.csv',parse_dates=True)"
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        "df.columns = ['date','Inter_Passengers']\n",
        "df['date'] = pd.to_datetime(df['date'], format='%Y/%m/%d')\n",
        "df = df.sort_index()\n",
        "df.head()"
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              "        date  Inter_Passengers\n",
              "0 1949-01-01               112\n",
              "1 1949-02-01               118\n",
              "2 1949-03-01               132\n",
              "3 1949-04-01               129\n",
              "4 1949-05-01               121"
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              "            Inter_Passengers\n",
              "date                        \n",
              "1949-01-01               112\n",
              "1949-02-01               118\n",
              "1949-03-01               132\n",
              "1949-04-01               129\n",
              "1949-05-01               121"
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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def split_sequence(seq, n_step):\n",
        "    targets = []\n",
        "    features = []\n",
        "    for i in range(len(seq)):\n",
        "        eidx = i + n_step\n",
        "        if eidx > len(seq)-1:\n",
        "            break\n",
        "        target = seq[i:eidx]\n",
        "        feature = seq[eidx]\n",
        "        targets.append(target)\n",
        "        features.append(feature)\n",
        "    return np.array(targets), np.array(features)"
      ],
      "metadata": {
        "id": "udBPoMbIESzK"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "n_steps=3"
      ],
      "metadata": {
        "id": "OAPEmDeSE8-A"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X, y = split_sequence(df['Inter_Passengers'], n_steps)\n",
        "print('X shape: %s'%str(X.shape))\n",
        "print('y shape: %s'%str(y.shape))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hgvFOWnQE54c",
        "outputId": "cd62854e-a3f1-4e30-f968-21776b46a7a9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "X shape: (141, 3)\n",
            "y shape: (141,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(5):\n",
        "  print('{} {:.2f}'.format(X[i, :], y[i]))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1rfLJidDFm22",
        "outputId": "73574d40-5f9e-4cd9-b819-63b317e1026d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[112 118 132] 129.00\n",
            "[118 132 129] 121.00\n",
            "[132 129 121] 135.00\n",
            "[129 121 135] 148.00\n",
            "[121 135 148] 148.00\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model = Sequential()\n",
        "model.add(Dense(100, activation = 'relu', input_dim = n_steps))\n",
        "model.add(Dense(1))\n",
        "model.compile(optimizer = 'adam', loss = 'mse')"
      ],
      "metadata": {
        "id": "C-3QnTdhF3_S"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.summary()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ile1XXG0F-qW",
        "outputId": "d65ac0d8-ae07-4e3f-b237-93759750c5c9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " dense (Dense)               (None, 100)               400       \n",
            "                                                                 \n",
            " dense_1 (Dense)             (None, 1)                 101       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 501\n",
            "Trainable params: 501\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.fit(X, y, epochs = 50)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UtSITz7qGDpl",
        "outputId": "11eefc21-aadf-4458-dde9-836e39dde7d3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/50\n",
            "5/5 [==============================] - 0s 5ms/step - loss: 3322.9358\n",
            "Epoch 2/50\n",
            "5/5 [==============================] - 0s 7ms/step - loss: 3349.8906\n",
            "Epoch 3/50\n",
            "5/5 [==============================] - 0s 7ms/step - loss: 3396.2883\n",
            "Epoch 4/50\n",
            "5/5 [==============================] - 0s 9ms/step - loss: 3370.7354\n",
            "Epoch 5/50\n",
            "5/5 [==============================] - 0s 5ms/step - loss: 3313.0129\n",
            "Epoch 6/50\n",
            "5/5 [==============================] - 0s 4ms/step - loss: 3265.7739\n",
            "Epoch 7/50\n",
            "5/5 [==============================] - 0s 7ms/step - loss: 3208.5156\n",
            "Epoch 8/50\n",
            "5/5 [==============================] - 0s 6ms/step - loss: 3183.4231\n",
            "Epoch 9/50\n",
            "5/5 [==============================] - 0s 6ms/step - loss: 3165.7168\n",
            "Epoch 10/50\n",
            "5/5 [==============================] - 0s 6ms/step - loss: 3152.4395\n",
            "Epoch 11/50\n",
            "5/5 [==============================] - 0s 4ms/step - loss: 3139.7239\n",
            "Epoch 12/50\n",
            "5/5 [==============================] - 0s 5ms/step - loss: 3121.2727\n",
            "Epoch 13/50\n",
            "5/5 [==============================] - 0s 6ms/step - loss: 3107.6577\n",
            "Epoch 14/50\n",
            "5/5 [==============================] - 0s 6ms/step - loss: 3090.7544\n",
            "Epoch 15/50\n",
            "5/5 [==============================] - 0s 5ms/step - loss: 3075.1545\n",
            "Epoch 16/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 3057.2180\n",
            "Epoch 17/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 3041.7441\n",
            "Epoch 18/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 3022.3752\n",
            "Epoch 19/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 3008.8042\n",
            "Epoch 20/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2989.5830\n",
            "Epoch 21/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2970.5540\n",
            "Epoch 22/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2954.9521\n",
            "Epoch 23/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2956.9990\n",
            "Epoch 24/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2920.5886\n",
            "Epoch 25/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2892.9990\n",
            "Epoch 26/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2868.9358\n",
            "Epoch 27/50\n",
            "5/5 [==============================] - 0s 4ms/step - loss: 2848.4399\n",
            "Epoch 28/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2823.2896\n",
            "Epoch 29/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2807.8716\n",
            "Epoch 30/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2786.3872\n",
            "Epoch 31/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2767.3418\n",
            "Epoch 32/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2750.5725\n",
            "Epoch 33/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2728.3030\n",
            "Epoch 34/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2712.2227\n",
            "Epoch 35/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2692.7080\n",
            "Epoch 36/50\n",
            "5/5 [==============================] - 0s 4ms/step - loss: 2675.1438\n",
            "Epoch 37/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2655.1501\n",
            "Epoch 38/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2641.8809\n",
            "Epoch 39/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2631.3025\n",
            "Epoch 40/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2607.6748\n",
            "Epoch 41/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2589.8445\n",
            "Epoch 42/50\n",
            "5/5 [==============================] - 0s 4ms/step - loss: 2575.6843\n",
            "Epoch 43/50\n",
            "5/5 [==============================] - 0s 5ms/step - loss: 2554.7590\n",
            "Epoch 44/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2536.7820\n",
            "Epoch 45/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2521.4565\n",
            "Epoch 46/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2508.1382\n",
            "Epoch 47/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2493.0234\n",
            "Epoch 48/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2473.9487\n",
            "Epoch 49/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2460.8225\n",
            "Epoch 50/50\n",
            "5/5 [==============================] - 0s 3ms/step - loss: 2446.7422\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.callbacks.History at 0x7f6dc2520220>"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X_input = np.array(X[-5:]).reshape(-1, n_steps)\n",
        "print(X_input)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2n17Lp8bGGWe",
        "outputId": "2fdddd48-a2e9-44a6-84dd-1304a8bf9989"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[472 535 622]\n",
            " [535 622 606]\n",
            " [622 606 508]\n",
            " [606 508 461]\n",
            " [508 461 390]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print('Actual value: %s'%str(y[-5:]))\n",
        "print('Predict value:')\n",
        "yhat = model.predict(X_input)\n",
        "print(yhat)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qEmXIE9gGO4T",
        "outputId": "787de90b-b38c-49ba-de50-bede20b19316"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Actual value: [606 508 461 390 432]\n",
            "Predict value:\n",
            "1/1 [==============================] - 0s 59ms/step\n",
            "[[539.8327]\n",
            " [585.1644]\n",
            " [583.6499]\n",
            " [534.6738]\n",
            " [459.1827]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Hàm RMSE\n",
        "def RMSE(yhat, y):\n",
        "    return np.sqrt(np.mean((yhat - y)**2))\n",
        "\n",
        "yhat = model.predict(X)\n",
        "RMSE(yhat, y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gSGlueCMGSAs",
        "outputId": "717bdca6-66fd-4632-9a8d-dad2aa822bd3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "5/5 [==============================] - 0s 2ms/step\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "166.2966949096413"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def plt_graph(y, yhat):\n",
        "    plt.figure(figsize = (16, 8))\n",
        "    plt.plot(y, label = 'Actual')\n",
        "    plt.plot(yhat, label = 'Predict')\n",
        "    plt.xlabel('No transaction')\n",
        "    plt.ylabel('Price')\n",
        "    legend = plt.legend(loc = 'upper center', shadow = True, fontsize = 'x-large')\n",
        "    legend.get_frame().set_facecolor('C')\n",
        "    \n",
        "plt_graph(y, yhat)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 444
        },
        "id": "XF5XMyFTGY7S",
        "outputId": "ca85a130-dd28-4c94-ac7a-046a58f5393c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-16-d4cb0366c2aa>:8: MatplotlibDeprecationWarning: Support for uppercase single-letter colors is deprecated since Matplotlib 3.1 and will be removed in 3.3; please use lowercase instead.\n",
            "  legend.get_frame().set_facecolor('C')\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1152x576 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.xlabel?"
      ],
      "metadata": {
        "id": "cYEn57wVGtic"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "zSqLrbg2GeQw"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}