Project6.ipynb

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      "name": "Untitled5.ipynb",
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        "<a href=\"https://colab.research.google.com/github/zachmakki15/ADVDS/blob/main/Project6.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "cell_type": "markdown",
      "source": [
        "Zach Makki\n",
        "\n",
        "Advanced Data Science\n",
        "\n",
        "Project #6\n",
        "\n",
        "03/06/2022"
      ],
      "metadata": {
        "id": "uEvQ-Z1GeWqm"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Data Visualization"
      ],
      "metadata": {
        "id": "iN01Uu5ReIv6"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 42,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "I-mCCyVkeH-7",
        "outputId": "fc34cec9-7522-44b2-a009-bb660c8606a1"
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 2126 entries, 0 to 2125\n",
            "Data columns (total 22 columns):\n",
            " #   Column                                                  Non-Null Count  Dtype  \n",
            "---  ------                                                  --------------  -----  \n",
            " 0   baseline value                                          2126 non-null   float64\n",
            " 1   accelerations                                           2126 non-null   float64\n",
            " 2   fetal_movement                                          2126 non-null   float64\n",
            " 3   uterine_contractions                                    2126 non-null   float64\n",
            " 4   light_decelerations                                     2126 non-null   float64\n",
            " 5   severe_decelerations                                    2126 non-null   float64\n",
            " 6   prolongued_decelerations                                2126 non-null   float64\n",
            " 7   abnormal_short_term_variability                         2126 non-null   float64\n",
            " 8   mean_value_of_short_term_variability                    2126 non-null   float64\n",
            " 9   percentage_of_time_with_abnormal_long_term_variability  2126 non-null   float64\n",
            " 10  mean_value_of_long_term_variability                     2126 non-null   float64\n",
            " 11  histogram_width                                         2126 non-null   float64\n",
            " 12  histogram_min                                           2126 non-null   float64\n",
            " 13  histogram_max                                           2126 non-null   float64\n",
            " 14  histogram_number_of_peaks                               2126 non-null   float64\n",
            " 15  histogram_number_of_zeroes                              2126 non-null   float64\n",
            " 16  histogram_mode                                          2126 non-null   float64\n",
            " 17  histogram_mean                                          2126 non-null   float64\n",
            " 18  histogram_median                                        2126 non-null   float64\n",
            " 19  histogram_variance                                      2126 non-null   float64\n",
            " 20  histogram_tendency                                      2126 non-null   float64\n",
            " 21  fetal_health                                            2126 non-null   float64\n",
            "dtypes: float64(22)\n",
            "memory usage: 365.5 KB\n"
          ]
        }
      ],
      "source": [
        "#Import the needed libs\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "\n",
        "#Import training dataset\n",
        "dataFrame = pd.read_csv(\"https://raw.githubusercontent.com/zachmakki15/ADVDS/main/fetal_health.csv\")\n",
        "#Check data info\n",
        "dataFrame.info()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Visualize data\n",
        "dataFrame.head(10)"
      ],
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>baseline value</th>\n",
              "      <th>accelerations</th>\n",
              "      <th>fetal_movement</th>\n",
              "      <th>uterine_contractions</th>\n",
              "      <th>light_decelerations</th>\n",
              "      <th>severe_decelerations</th>\n",
              "      <th>prolongued_decelerations</th>\n",
              "      <th>abnormal_short_term_variability</th>\n",
              "      <th>mean_value_of_short_term_variability</th>\n",
              "      <th>percentage_of_time_with_abnormal_long_term_variability</th>\n",
              "      <th>...</th>\n",
              "      <th>histogram_min</th>\n",
              "      <th>histogram_max</th>\n",
              "      <th>histogram_number_of_peaks</th>\n",
              "      <th>histogram_number_of_zeroes</th>\n",
              "      <th>histogram_mode</th>\n",
              "      <th>histogram_mean</th>\n",
              "      <th>histogram_median</th>\n",
              "      <th>histogram_variance</th>\n",
              "      <th>histogram_tendency</th>\n",
              "      <th>fetal_health</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>120.0</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000</td>\n",
              "      <td>73.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>43.0</td>\n",
              "      <td>...</td>\n",
              "      <td>62.0</td>\n",
              "      <td>126.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>137.0</td>\n",
              "      <td>121.0</td>\n",
              "      <td>73.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>132.0</td>\n",
              "      <td>0.006</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.006</td>\n",
              "      <td>0.003</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000</td>\n",
              "      <td>17.0</td>\n",
              "      <td>2.1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>68.0</td>\n",
              "      <td>198.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>141.0</td>\n",
              "      <td>136.0</td>\n",
              "      <td>140.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>133.0</td>\n",
              "      <td>0.003</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.008</td>\n",
              "      <td>0.003</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000</td>\n",
              "      <td>16.0</td>\n",
              "      <td>2.1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>68.0</td>\n",
              "      <td>198.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>141.0</td>\n",
              "      <td>135.0</td>\n",
              "      <td>138.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>134.0</td>\n",
              "      <td>0.003</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.008</td>\n",
              "      <td>0.003</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000</td>\n",
              "      <td>16.0</td>\n",
              "      <td>2.4</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>53.0</td>\n",
              "      <td>170.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>137.0</td>\n",
              "      <td>134.0</td>\n",
              "      <td>137.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>132.0</td>\n",
              "      <td>0.007</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.008</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000</td>\n",
              "      <td>16.0</td>\n",
              "      <td>2.4</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>53.0</td>\n",
              "      <td>170.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>137.0</td>\n",
              "      <td>136.0</td>\n",
              "      <td>138.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>134.0</td>\n",
              "      <td>0.001</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.010</td>\n",
              "      <td>0.009</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.002</td>\n",
              "      <td>26.0</td>\n",
              "      <td>5.9</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>50.0</td>\n",
              "      <td>200.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>76.0</td>\n",
              "      <td>107.0</td>\n",
              "      <td>107.0</td>\n",
              "      <td>170.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
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              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>134.0</td>\n",
              "      <td>0.001</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.013</td>\n",
              "      <td>0.008</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.003</td>\n",
              "      <td>29.0</td>\n",
              "      <td>6.3</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>50.0</td>\n",
              "      <td>200.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>71.0</td>\n",
              "      <td>107.0</td>\n",
              "      <td>106.0</td>\n",
              "      <td>215.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
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              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>122.0</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000</td>\n",
              "      <td>83.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>6.0</td>\n",
              "      <td>...</td>\n",
              "      <td>62.0</td>\n",
              "      <td>130.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>122.0</td>\n",
              "      <td>122.0</td>\n",
              "      <td>123.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
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              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>122.0</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.002</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000</td>\n",
              "      <td>84.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>5.0</td>\n",
              "      <td>...</td>\n",
              "      <td>62.0</td>\n",
              "      <td>130.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>122.0</td>\n",
              "      <td>122.0</td>\n",
              "      <td>123.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>122.0</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.003</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000</td>\n",
              "      <td>86.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>6.0</td>\n",
              "      <td>...</td>\n",
              "      <td>62.0</td>\n",
              "      <td>130.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>122.0</td>\n",
              "      <td>122.0</td>\n",
              "      <td>123.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
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              "<p>10 rows × 22 columns</p>\n",
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            "text/plain": [
              "   baseline value  accelerations  fetal_movement  uterine_contractions  \\\n",
              "0           120.0          0.000             0.0                 0.000   \n",
              "1           132.0          0.006             0.0                 0.006   \n",
              "2           133.0          0.003             0.0                 0.008   \n",
              "3           134.0          0.003             0.0                 0.008   \n",
              "4           132.0          0.007             0.0                 0.008   \n",
              "5           134.0          0.001             0.0                 0.010   \n",
              "6           134.0          0.001             0.0                 0.013   \n",
              "7           122.0          0.000             0.0                 0.000   \n",
              "8           122.0          0.000             0.0                 0.002   \n",
              "9           122.0          0.000             0.0                 0.003   \n",
              "\n",
              "   light_decelerations  severe_decelerations  prolongued_decelerations  \\\n",
              "0                0.000                   0.0                     0.000   \n",
              "1                0.003                   0.0                     0.000   \n",
              "2                0.003                   0.0                     0.000   \n",
              "3                0.003                   0.0                     0.000   \n",
              "4                0.000                   0.0                     0.000   \n",
              "5                0.009                   0.0                     0.002   \n",
              "6                0.008                   0.0                     0.003   \n",
              "7                0.000                   0.0                     0.000   \n",
              "8                0.000                   0.0                     0.000   \n",
              "9                0.000                   0.0                     0.000   \n",
              "\n",
              "   abnormal_short_term_variability  mean_value_of_short_term_variability  \\\n",
              "0                             73.0                                   0.5   \n",
              "1                             17.0                                   2.1   \n",
              "2                             16.0                                   2.1   \n",
              "3                             16.0                                   2.4   \n",
              "4                             16.0                                   2.4   \n",
              "5                             26.0                                   5.9   \n",
              "6                             29.0                                   6.3   \n",
              "7                             83.0                                   0.5   \n",
              "8                             84.0                                   0.5   \n",
              "9                             86.0                                   0.3   \n",
              "\n",
              "   percentage_of_time_with_abnormal_long_term_variability  ...  histogram_min  \\\n",
              "0                                               43.0       ...           62.0   \n",
              "1                                                0.0       ...           68.0   \n",
              "2                                                0.0       ...           68.0   \n",
              "3                                                0.0       ...           53.0   \n",
              "4                                                0.0       ...           53.0   \n",
              "5                                                0.0       ...           50.0   \n",
              "6                                                0.0       ...           50.0   \n",
              "7                                                6.0       ...           62.0   \n",
              "8                                                5.0       ...           62.0   \n",
              "9                                                6.0       ...           62.0   \n",
              "\n",
              "   histogram_max  histogram_number_of_peaks  histogram_number_of_zeroes  \\\n",
              "0          126.0                        2.0                         0.0   \n",
              "1          198.0                        6.0                         1.0   \n",
              "2          198.0                        5.0                         1.0   \n",
              "3          170.0                       11.0                         0.0   \n",
              "4          170.0                        9.0                         0.0   \n",
              "5          200.0                        5.0                         3.0   \n",
              "6          200.0                        6.0                         3.0   \n",
              "7          130.0                        0.0                         0.0   \n",
              "8          130.0                        0.0                         0.0   \n",
              "9          130.0                        1.0                         0.0   \n",
              "\n",
              "   histogram_mode  histogram_mean  histogram_median  histogram_variance  \\\n",
              "0           120.0           137.0             121.0                73.0   \n",
              "1           141.0           136.0             140.0                12.0   \n",
              "2           141.0           135.0             138.0                13.0   \n",
              "3           137.0           134.0             137.0                13.0   \n",
              "4           137.0           136.0             138.0                11.0   \n",
              "5            76.0           107.0             107.0               170.0   \n",
              "6            71.0           107.0             106.0               215.0   \n",
              "7           122.0           122.0             123.0                 3.0   \n",
              "8           122.0           122.0             123.0                 3.0   \n",
              "9           122.0           122.0             123.0                 1.0   \n",
              "\n",
              "   histogram_tendency  fetal_health  \n",
              "0                 1.0           2.0  \n",
              "1                 0.0           1.0  \n",
              "2                 0.0           1.0  \n",
              "3                 1.0           1.0  \n",
              "4                 1.0           1.0  \n",
              "5                 0.0           3.0  \n",
              "6                 0.0           3.0  \n",
              "7                 1.0           3.0  \n",
              "8                 1.0           3.0  \n",
              "9                 1.0           3.0  \n",
              "\n",
              "[10 rows x 22 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "This dataset contains numeric attributes extraced from Cardiotocogram exams, the targets attribute (fetal health) represents classifications made by medical experts where 1 = normal, 2 = Suspect, 3 = Pathological\n",
        "\n",
        "The purpose of this study will be to create a model which can predict fetal health based on the numeric attribites provided. "
      ],
      "metadata": {
        "id": "DZSYaIoie572"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Attribute distrbition\n",
        "dataFrame.hist(bins=20,figsize=(30,20))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "cOUPqRUGgjOx",
        "outputId": "f7df8e4a-edd4-47da-e80d-37939c483fc2"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f7f8378c610>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f6ac1df10>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f6ac4aad0>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f6abf5b10>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f6abc0510>],\n",
              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f7f6ab78a10>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f6ab2ff90>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f6aaf5410>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f6aaf5450>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f651dda10>],\n",
              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f7f65158350>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f6510e7d0>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f65145c90>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f651081d0>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f650be6d0>],\n",
              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f7f65075bd0>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f65039110>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f64fee610>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f64fa5b10>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f64f5dfd0>],\n",
              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f7f64f1f550>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f64ed6a50>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f64e8ef50>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f64e51490>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f64e86990>]],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 44
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 2160x1440 with 25 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Individual historgram of target\n",
        "dataFrame['fetal_health'].value_counts().plot(kind='bar', figsize=(10,5))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 343
        },
        "id": "PBh3njt_l5eE",
        "outputId": "490a4f3b-fa88-4aae-ec1e-5f05ef067ff5"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f7f70a80d10>"
            ]
          },
          "metadata": {},
          "execution_count": 45
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAlwAAAE1CAYAAAAyDz6/AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAVAElEQVR4nO3df7CldX0f8PcnbKDRTAXkhprdJUvjJhmSRqUrIeM0Y0KroE7WP6IDk5atZWbbBk1SM2PW5A9mkrHFtFMjk4SGhq3QcSQMtWWrJJai1uk0IIsaBH+UW0TZHZA1INbSSNFP/7gP8brusnDP/d5z9+7rNXPmPM/n+33O8zkzZ+a853me85zq7gAAMM73zLsBAICNTuACABhM4AIAGEzgAgAYTOACABhM4AIAGGzTvBt4JmeccUZv27Zt3m0AABzTXXfd9ZXuXjjS2LoOXNu2bcv+/fvn3QYAwDFV1RePNuaUIgDAYAIXAMBgAhcAwGACFwDAYAIXAMBgAhcAwGACFwDAYAIXAMBgAhcAwGACFwDAYAIXAMBg6/q/FI9n2/Z8cN4tnHAeuPK1824BAI7IES4AgMEELgCAwQQuAIDBBC4AgMGOGbiqam9VPVJV9xxWf0tVfa6q7q2q31lWf3tVLVbV56vq1cvqF061xaras7pvAwBg/Xo2v1J8T5LfS3L904Wq+tkkO5O8pLu/UVU/MNXPSXJxkh9P8oNJ/mtV/ci02e8n+XtJDiS5s6r2dfdnVuuNAACsV8cMXN39saradlj5nya5sru/Mc15ZKrvTHLDVP9CVS0mOW8aW+zu+5Okqm6Y5gpcAMCGt9JruH4kyd+pqjuq6r9V1cun+uYkDy6bd2CqHa0OALDhrfTGp5uSnJ7k/CQvT3JjVf3N1WioqnYn2Z0kZ5111mq8JADAXK30CNeBJO/vJR9P8q0kZyQ5mGTrsnlbptrR6t+lu6/p7h3dvWNhYWGF7QEArB8rDVz/KcnPJsl0UfzJSb6SZF+Si6vqlKo6O8n2JB9PcmeS7VV1dlWdnKUL6/fN2jwAwPHgmKcUq+p9SV6Z5IyqOpDkiiR7k+ydbhXxZJJd3d1J7q2qG7N0MfxTSS7v7m9Or/PmJB9KclKSvd1974D3AwCw7jybXylecpShv3+U+e9I8o4j1G9Jcstz6g4AYANwp3kAgMEELgCAwQQuAIDBBC4AgMEELgCAwQQuAIDBBC4AgMEELgCAwQQuAIDBBC4AgMEELgCAwQQuAIDBBC4AgMEELgCAwQQuAIDBBC4AgMEELgCAwQQuAIDBBC4AgMEELgCAwQQuAIDBBC4AgMGOGbiqam9VPVJV9xxh7NeqqqvqjGm9quqqqlqsqrur6txlc3dV1X3TY9fqvg0AgPXr2Rzhek+SCw8vVtXWJK9K8qVl5YuSbJ8eu5NcPc09PckVSX4qyXlJrqiq02ZpHADgeHHMwNXdH0vy6BGG3pXkbUl6WW1nkut7ye1JTq2qFyV5dZJbu/vR7n4sya05QogDANiIVnQNV1XtTHKwu//8sKHNSR5ctn5gqh2tDgCw4W16rhtU1fOS/EaWTieuuqranaXTkTnrrLNG7AIAYE2t5AjXDyc5O8mfV9UDSbYk+URV/Y0kB5NsXTZ3y1Q7Wv27dPc13b2ju3csLCysoD0AgPXlOQeu7v50d/9Ad2/r7m1ZOj14bnc/nGRfkkunXyuen+Tx7n4oyYeSvKqqTpsuln/VVAMA2PCezW0h3pfkz5L8aFUdqKrLnmH6LUnuT7KY5N8m+aUk6e5Hk/x2kjunx29NNQCADe+Y13B19yXHGN+2bLmTXH6UeXuT7H2O/QEAHPfcaR4AYDCBCwBgMIELAGAwgQsAYDCBCwBgMIELAGAwgQsAYDCBCwBgMIELAGAwgQsAYDCBCwBgMIELAGAwgQsAYDCBCwBgMIELAGAwgQsAYDCBCwBgMIELAGAwgQsAYDCBCwBgMIELAGAwgQsAYLBjBq6q2ltVj1TVPctq/7KqPldVd1fVf6yqU5eNvb2qFqvq81X16mX1C6faYlXtWf23AgCwPj2bI1zvSXLhYbVbk/xEd/9kkv+Z5O1JUlXnJLk4yY9P2/xBVZ1UVScl+f0kFyU5J8kl01wAgA3vmIGruz+W5NHDav+lu5+aVm9PsmVa3pnkhu7+Rnd/IclikvOmx2J339/dTya5YZoLALDhrcY1XP8oyZ9My5uTPLhs7MBUO1odAGDDmylwVdVvJnkqyXtXp52kqnZX1f6q2n/o0KHVelkAgLlZceCqqn+Y5HVJfrG7eyofTLJ12bQtU+1o9e/S3dd0947u3rGwsLDS9gAA1o0VBa6qujDJ25L8fHc/sWxoX5KLq+qUqjo7yfYkH09yZ5LtVXV2VZ2cpQvr983WOgDA8WHTsSZU1fuSvDLJGVV1IMkVWfpV4ilJbq2qJLm9u/9Jd99bVTcm+UyWTjVe3t3fnF7nzUk+lOSkJHu7+94B7wcAYN05ZuDq7kuOUL72Gea/I8k7jlC/Jcktz6k7AIANwJ3mAQAGE7gAAAYTuAAABhO4AAAGE7gAAAYTuAAABhO4AAAGE7gAAAYTuAAABhO4AAAGE7gAAAYTuAAABhO4AAAGE7gAAAYTuAAABhO4AAAGE7gAAAYTuAAABhO4AAAGE7gAAAYTuAAABhO4AAAGE7gAAAY7ZuCqqr1V9UhV3bOsdnpV3VpV903Pp031qqqrqmqxqu6uqnOXbbNrmn9fVe0a83YAANafZ3OE6z1JLjystifJbd29Pclt03qSXJRk+/TYneTqZCmgJbkiyU8lOS/JFU+HNACAje6Ygau7P5bk0cPKO5NcNy1fl+T1y+rX95Lbk5xaVS9K8uokt3b3o939WJJb890hDgBgQ1rpNVxndvdD0/LDSc6cljcneXDZvANT7Wh1AIANb+aL5ru7k/Qq9JIkqardVbW/qvYfOnRotV4WAGBuVhq4vjydKsz0/MhUP5hk67J5W6ba0erfpbuv6e4d3b1jYWFhhe0BAKwfKw1c+5I8/UvDXUluXla/dPq14vlJHp9OPX4oyauq6rTpYvlXTTUAgA1v07EmVNX7krwyyRlVdSBLvza8MsmNVXVZki8meeM0/ZYkr0mymOSJJG9Kku5+tKp+O8md07zf6u7DL8QHANiQjhm4uvuSowxdcIS5neTyo7zO3iR7n1N3AAAbgDvNAwAMJnABAAwmcAEADCZwAQAMJnABAAwmcAEADCZwAQAMJnABAAwmcAEADCZwAQAMJnABAAwmcAEADCZwAQAMJnABAAwmcAEADCZwAQAMJnABAAwmcAEADCZwAQAMJnABAAwmcAEADCZwAQAMNlPgqqp/VlX3VtU9VfW+qvprVXV2Vd1RVYtV9cdVdfI095RpfXEa37YabwAAYL1bceCqqs1JfjnJju7+iSQnJbk4yTuTvKu7X5zksSSXTZtcluSxqf6uaR4AwIY36ynFTUm+r6o2JXlekoeS/FySm6bx65K8flreOa1nGr+gqmrG/QMArHsrDlzdfTDJv0rypSwFrceT3JXkq9391DTtQJLN0/LmJA9O2z41zX/hSvcPAHC8mOWU4mlZOmp1dpIfTPL8JBfO2lBV7a6q/VW1/9ChQ7O+HADA3M1ySvHvJvlCdx/q7v+X5P1JXpHk1OkUY5JsSXJwWj6YZGuSTOMvSPIXh79od1/T3Tu6e8fCwsIM7QEArA+zBK4vJTm/qp43XYt1QZLPJPlIkl+Y5uxKcvO0vG9azzT+4e7uGfYPAHBcmOUarjuydPH7J5J8enqta5L8epK3VtVilq7Runba5NokL5zqb02yZ4a+AQCOG5uOPeXouvuKJFccVr4/yXlHmPuXSd4wy/4AAI5H7jQPADCYwAUAMJjABQAwmMAFADCYwAUAMJjABQAwmMAFADCYwAUAMJjABQAwmMAFADCYwAUAMJjABQAwmMAFADCYwAUAMJjABQAwmMAFADCYwAUAMJjABQAwmMAFADCYwAUAMJjABQAwmMAFADDYTIGrqk6tqpuq6nNV9dmq+umqOr2qbq2q+6bn06a5VVVXVdViVd1dVeeuzlsAAFjfZj3C9e4kf9rdP5bkJUk+m2RPktu6e3uS26b1JLkoyfbpsTvJ1TPuGwDguLDiwFVVL0jyM0muTZLufrK7v5pkZ5LrpmnXJXn9tLwzyfW95PYkp1bVi1bcOQDAcWKWI1xnJzmU5N9V1Ser6o+q6vlJzuzuh6Y5Dyc5c1renOTBZdsfmGoAABvaLIFrU5Jzk1zd3S9L8n/y7dOHSZLu7iT9XF60qnZX1f6q2n/o0KEZ2gMAWB9mCVwHkhzo7jum9ZuyFMC+/PSpwun5kWn8YJKty7bfMtW+Q3df0907unvHwsLCDO0BAKwPKw5c3f1wkger6ken0gVJPpNkX5JdU21Xkpun5X1JLp1+rXh+kseXnXoEANiwNs24/VuSvLeqTk5yf5I3ZSnE3VhVlyX5YpI3TnNvSfKaJItJnpjmAgBseDMFru7+VJIdRxi64AhzO8nls+wPAOB45E7zAACDCVwAAIMJXAAAgwlcAACDCVwAAIMJXAAAgwlcAACDCVwAAIMJXAAAgwlcAACDCVwAAIMJXAAAgwlcAACDCVwAAIMJXAAAgwlcAACDCVwAAIMJXAAAgwlcAACDCVwAAIMJXAAAgwlcAACDzRy4quqkqvpkVX1gWj+7qu6oqsWq+uOqOnmqnzKtL07j22bdNwDA8WA1jnD9SpLPLlt/Z5J3dfeLkzyW5LKpflmSx6b6u6Z5AAAb3kyBq6q2JHltkj+a1ivJzyW5aZpyXZLXT8s7p/VM4xdM8wEANrRZj3D9bpK3JfnWtP7CJF/t7qem9QNJNk/Lm5M8mCTT+OPTfACADW3FgauqXpfkke6+axX7SVXtrqr9VbX/0KFDq/nSAABzMcsRrlck+fmqeiDJDVk6lfjuJKdW1aZpzpYkB6flg0m2Jsk0/oIkf3H4i3b3Nd29o7t3LCwszNAeAMD6sOLA1d1v7+4t3b0tycVJPtzdv5jkI0l+YZq2K8nN0/K+aT3T+Ie7u1e6fwCA48WI+3D9epK3VtVilq7RunaqX5vkhVP9rUn2DNg3AMC6s+nYU46tuz+a5KPT8v1JzjvCnL9M8obV2B8AwPHEneYBAAYTuAAABhO4AAAGE7gAAAYTuAAABhO4AAAGE7gAAAYTuAAABhO4AAAGE7gAAAYTuAAABhO4AAAGW5U/rwZOTNv2fHDeLZxwHrjytfNuAVgBR7gAAAYTuAAABhO4AAAGE7gAAAYTuAAABhO4AAAGE7gAAAYTuAAABhO4AAAGE7gAAAZbceCqqq1V9ZGq+kxV3VtVvzLVT6+qW6vqvun5tKleVXVVVS1W1d1Vde5qvQkAgPVsliNcTyX5te4+J8n5SS6vqnOS7ElyW3dvT3LbtJ4kFyXZPj12J7l6hn0DABw3Vhy4uvuh7v7EtPy/k3w2yeYkO5NcN027Lsnrp+WdSa7vJbcnObWqXrTizgEAjhOrcg1XVW1L8rIkdyQ5s7sfmoYeTnLmtLw5yYPLNjsw1QAANrSZA1dVfX+S/5DkV7v7a8vHuruT9HN8vd1Vtb+q9h86dGjW9gAA5m6mwFVV35ulsPXe7n7/VP7y06cKp+dHpvrBJFuXbb5lqn2H7r6mu3d0946FhYVZ2gMAWBdm+ZViJbk2yWe7+18vG9qXZNe0vCvJzcvql06/Vjw/yePLTj0CAGxYm2bY9hVJ/kGST1fVp6babyS5MsmNVXVZki8meeM0dkuS1yRZTPJEkjfNsG8AWBPb9nxw3i2ccB648rXzbmHVrThwdfd/T1JHGb7gCPM7yeUr3R8AwPHKneYBAAYTuAAABhO4AAAGE7gAAAYTuAAABhO4AAAGE7gAAAYTuAAABhO4AAAGE7gAAAYTuAAABhO4AAAGE7gAAAYTuAAABhO4AAAGE7gAAAYTuAAABhO4AAAGE7gAAAYTuAAABhO4AAAGE7gAAAZb88BVVRdW1eerarGq9qz1/gEA1tqaBq6qOinJ7ye5KMk5SS6pqnPWsgcAgLW21ke4zkuy2N33d/eTSW5IsnONewAAWFNrHbg2J3lw2fqBqQYAsGFtmncDh6uq3Ul2T6tfr6rPz7OfE9AZSb4y7yZWot457w44jviccyLwOV97P3S0gbUOXAeTbF22vmWq/ZXuvibJNWvZFN9WVfu7e8e8+4CRfM45Eficry9rfUrxziTbq+rsqjo5ycVJ9q1xDwAAa2pNj3B191NV9eYkH0pyUpK93X3vWvYAALDW1vwaru6+Jckta71fnjWnczkR+JxzIvA5X0equ+fdAwDAhuavfQAABhO4AAAGE7gAAAZbdzc+BRihqs7Mt//Z4mB3f3me/cAoVXV6knT3o/PuhW9z0TxJfBmxcVXVS5P8myQvyLdvtLwlyVeT/FJ3f2JevcFqqaqzkvxOkguy9NmuJH89yYeT7OnuB+bXHYnAdcLzZcRGV1WfSvKPu/uOw+rnJ/nD7n7JfDqD1VNVf5bkd5Pc1N3fnGonJXlDkl/t7vPn2R8C1wnPlxEbXVXd193bjzK22N0vXuueYLUd43N+1DHWjmu4eP7hYStJuvv2qnr+PBqCVfYnVfXBJNcneXCqbU1yaZI/nVtXsLruqqo/SHJdvvNzvivJJ+fWFX/FEa4TXFVdleSHc+Qvoy9095vn1Ruslqq6KMnOLLtOMcm+6Z8v4Lg3/T/xZfnOz/mBJP85ybXd/Y159cYSgQtfRgAwmMAFnLCqand3+785NrSqel13f2DefZzo3PiUo6qq3fPuAQareTcAa+Dl824AF83zzHwZsSFU1Y9l6ZT5Hd399WVDX5xTS7Dqquq8JN3dd1bVOUkuTPK57r5izq0RR7h4Zk/OuwGYVVX9cpKbk7wlyT1VtXPZ8D+fT1ewuqrqiiRXJbm6qv5Fkt9L8vwke6rqN+faHElcw8UzqKovdfdZ8+4DZlFVn07y09399araluSmJP++u99dVZ/s7pfNtUFYBdPn/KVJTknycJIt3f21qvq+LB3Z/cm5NohTiie6qrr7aENJzlzLXmCQ73n6NGJ3P1BVr0xyU1X9UJw2Z+N4arrD/BNV9b+6+2tJ0t3/t6q+NefeiMDFUqh6dZLHDqtXkv+x9u3AqvtyVb20uz+VJNORrtcl2Zvkb823NVg1T1bV87r7iSR/++liVb0gicC1DghcfCDJ9z/9ZbRcVX107duBVXdpkqeWF7r7qSSXVtUfzqclWHU/8/TNTbt7ecD63izdbZ45cw0XAMBgfqUIADCYwAUAMJjABQAwmMAFADCYwAUAMNj/BwJXGoXOV0yLAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The dataset does not have any null vales (seen from info) and the 0 values make up a large portion of the dataset and most likley do not represent missing values in all attributes. The attributes in which 0s may represent missing values are histogram_number_of_peaks, histogram_width, mean_value_of_short_term_variablity and mean_value_of_long_term_variablity. These attributes will be imputed using their respective medians.\n",
        "\n",
        "To further inspect the attributes a correlation check with the target attribute (fetal health) will be done. Also, the target attribute distribition is skewed with the majority of the instances in the dataset classfied as Normal (1). "
      ],
      "metadata": {
        "id": "dHebEMXuhUX9"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Data Normalization and Correlation"
      ],
      "metadata": {
        "id": "SEoNgudJe3iO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Impute numeric attributes\n",
        "dataFrame.histogram_number_of_peaks.replace(0., dataFrame.histogram_number_of_peaks.median(), inplace=True)\n",
        "dataFrame.histogram_width.replace(0., dataFrame.histogram_width.median(), inplace=True)\n",
        "dataFrame.mean_value_of_long_term_variability.replace(0., dataFrame.mean_value_of_long_term_variability.median(), inplace=True)\n",
        "dataFrame.mean_value_of_short_term_variability.replace(0., dataFrame.mean_value_of_short_term_variability.median(), inplace=True)"
      ],
      "metadata": {
        "id": "HeE6_DQvzEbr"
      },
      "execution_count": 46,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Attribute correlation\n",
        "corr_matrix = dataFrame.corr()\n",
        "corr_matrix['fetal_health'].sort_values(ascending=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HxemlDTkiFXI",
        "outputId": "4d62f730-c7db-437f-cc2d-6ba29d26f52a"
      },
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "fetal_health                                              1.000000\n",
              "prolongued_decelerations                                  0.484859\n",
              "abnormal_short_term_variability                           0.471191\n",
              "percentage_of_time_with_abnormal_long_term_variability    0.426146\n",
              "histogram_variance                                        0.206630\n",
              "baseline value                                            0.148151\n",
              "severe_decelerations                                      0.131934\n",
              "fetal_movement                                            0.088010\n",
              "histogram_min                                             0.063175\n",
              "light_decelerations                                       0.058870\n",
              "histogram_number_of_peaks                                -0.005673\n",
              "histogram_number_of_zeroes                               -0.016682\n",
              "histogram_max                                            -0.045265\n",
              "histogram_width                                          -0.068789\n",
              "mean_value_of_short_term_variability                     -0.103382\n",
              "histogram_tendency                                       -0.131976\n",
              "mean_value_of_long_term_variability                      -0.133643\n",
              "uterine_contractions                                     -0.204894\n",
              "histogram_median                                         -0.205033\n",
              "histogram_mean                                           -0.226985\n",
              "histogram_mode                                           -0.250412\n",
              "accelerations                                            -0.364066\n",
              "Name: fetal_health, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Create correlation matrix heatmap\n",
        "plt.figure(figsize=(30, 20))\n",
        "heatmap = sns.heatmap(dataFrame.corr(), vmin=-1, vmax=1, annot=True, cmap='Greens')\n",
        "heatmap.set_title('Correlation Heatmap', fontdict={'fontsize':20}, pad=12)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 939
        },
        "id": "YxtgKin9ige4",
        "outputId": "31625d5d-70db-46df-92f7-365a4500f024"
      },
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Correlation Heatmap')"
            ]
          },
          "metadata": {},
          "execution_count": 48
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 2160x1440 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "From the heatmap and list displayed above the attributes which have the highest correlation to the target attribute (fetal_health) are prolongued_decelerations, abnormal_short_term_variability, and percentage_of_time_with_abnormal_long_term_variability. These attributes have a mild correlation with the target. Attributes which have a weak correlation but something above 0 include, histogram_variance, and severe_decelerations."
      ],
      "metadata": {
        "id": "ELzwtUO2kkeb"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "The data will be normalized and the correlation will be checked again to see if any difference has been made."
      ],
      "metadata": {
        "id": "Td-iPmhnpqa2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Seperate x and y (target) so that y values will not be changed\n",
        "x = dataFrame.drop(columns=['fetal_health'])\n",
        "\n",
        "#Normalize using standard scalar\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "myscalar = StandardScaler()\n",
        "x_arr = myscalar.fit_transform(x)\n",
        "x_tr = pd.DataFrame(x_arr, columns=x.columns, index=x.index)\n",
        "x_tr.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 411
        },
        "id": "emFbfCM2n9Gy",
        "outputId": "1d248eff-52cb-4f9e-b6f3-30dfbcca0aca"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-5d580fcd-eca9-4188-9785-a038b66be20a\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>baseline value</th>\n",
              "      <th>accelerations</th>\n",
              "      <th>fetal_movement</th>\n",
              "      <th>uterine_contractions</th>\n",
              "      <th>light_decelerations</th>\n",
              "      <th>severe_decelerations</th>\n",
              "      <th>prolongued_decelerations</th>\n",
              "      <th>abnormal_short_term_variability</th>\n",
              "      <th>mean_value_of_short_term_variability</th>\n",
              "      <th>percentage_of_time_with_abnormal_long_term_variability</th>\n",
              "      <th>...</th>\n",
              "      <th>histogram_width</th>\n",
              "      <th>histogram_min</th>\n",
              "      <th>histogram_max</th>\n",
              "      <th>histogram_number_of_peaks</th>\n",
              "      <th>histogram_number_of_zeroes</th>\n",
              "      <th>histogram_mode</th>\n",
              "      <th>histogram_mean</th>\n",
              "      <th>histogram_median</th>\n",
              "      <th>histogram_variance</th>\n",
              "      <th>histogram_tendency</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>2.126000e+03</td>\n",
              "      <td>2.126000e+03</td>\n",
              "      <td>2.126000e+03</td>\n",
              "      <td>2.126000e+03</td>\n",
              "      <td>2.126000e+03</td>\n",
              "      <td>2.126000e+03</td>\n",
              "      <td>2.126000e+03</td>\n",
              "      <td>2.126000e+03</td>\n",
              "      <td>2.126000e+03</td>\n",
              "      <td>2.126000e+03</td>\n",
              "      <td>...</td>\n",
              "      <td>2.126000e+03</td>\n",
              "      <td>2.126000e+03</td>\n",
              "      <td>2.126000e+03</td>\n",
              "      <td>2.126000e+03</td>\n",
              "      <td>2.126000e+03</td>\n",
              "      <td>2.126000e+03</td>\n",
              "      <td>2.126000e+03</td>\n",
              "      <td>2.126000e+03</td>\n",
              "      <td>2.126000e+03</td>\n",
              "      <td>2.126000e+03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>4.161509e-16</td>\n",
              "      <td>-1.803982e-16</td>\n",
              "      <td>-1.958452e-15</td>\n",
              "      <td>-2.625683e-15</td>\n",
              "      <td>-5.127706e-15</td>\n",
              "      <td>7.254767e-16</td>\n",
              "      <td>4.324961e-15</td>\n",
              "      <td>2.687304e-16</td>\n",
              "      <td>-2.481552e-16</td>\n",
              "      <td>2.291362e-15</td>\n",
              "      <td>...</td>\n",
              "      <td>8.564279e-17</td>\n",
              "      <td>-6.120326e-17</td>\n",
              "      <td>-4.047144e-17</td>\n",
              "      <td>-4.797041e-16</td>\n",
              "      <td>8.397171e-17</td>\n",
              "      <td>6.141215e-17</td>\n",
              "      <td>-4.183964e-16</td>\n",
              "      <td>1.404751e-16</td>\n",
              "      <td>-3.634597e-17</td>\n",
              "      <td>5.783500e-16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>1.000235e+00</td>\n",
              "      <td>1.000235e+00</td>\n",
              "      <td>1.000235e+00</td>\n",
              "      <td>1.000235e+00</td>\n",
              "      <td>1.000235e+00</td>\n",
              "      <td>1.000235e+00</td>\n",
              "      <td>1.000235e+00</td>\n",
              "      <td>1.000235e+00</td>\n",
              "      <td>1.000235e+00</td>\n",
              "      <td>1.000235e+00</td>\n",
              "      <td>...</td>\n",
              "      <td>1.000235e+00</td>\n",
              "      <td>1.000235e+00</td>\n",
              "      <td>1.000235e+00</td>\n",
              "      <td>1.000235e+00</td>\n",
              "      <td>1.000235e+00</td>\n",
              "      <td>1.000235e+00</td>\n",
              "      <td>1.000235e+00</td>\n",
              "      <td>1.000235e+00</td>\n",
              "      <td>1.000235e+00</td>\n",
              "      <td>1.000235e+00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>-2.775197e+00</td>\n",
              "      <td>-8.223883e-01</td>\n",
              "      <td>-2.032096e-01</td>\n",
              "      <td>-1.482465e+00</td>\n",
              "      <td>-6.384375e-01</td>\n",
              "      <td>-5.747560e-02</td>\n",
              "      <td>-2.687543e-01</td>\n",
              "      <td>-2.035639e+00</td>\n",
              "      <td>-1.282833e+00</td>\n",
              "      <td>-5.353613e-01</td>\n",
              "      <td>...</td>\n",
              "      <td>-1.731757e+00</td>\n",
              "      <td>-1.474609e+00</td>\n",
              "      <td>-2.342558e+00</td>\n",
              "      <td>-1.145594e+00</td>\n",
              "      <td>-4.584438e-01</td>\n",
              "      <td>-4.729191e+00</td>\n",
              "      <td>-3.951945e+00</td>\n",
              "      <td>-4.223849e+00</td>\n",
              "      <td>-6.492081e-01</td>\n",
              "      <td>-2.162031e+00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>-7.423728e-01</td>\n",
              "      <td>-8.223883e-01</td>\n",
              "      <td>-2.032096e-01</td>\n",
              "      <td>-8.034341e-01</td>\n",
              "      <td>-6.384375e-01</td>\n",
              "      <td>-5.747560e-02</td>\n",
              "      <td>-2.687543e-01</td>\n",
              "      <td>-8.720881e-01</td>\n",
              "      <td>-7.166031e-01</td>\n",
              "      <td>-5.353613e-01</td>\n",
              "      <td>...</td>\n",
              "      <td>-8.587648e-01</td>\n",
              "      <td>-8.993760e-01</td>\n",
              "      <td>-6.703135e-01</td>\n",
              "      <td>-7.897301e-01</td>\n",
              "      <td>-4.584438e-01</td>\n",
              "      <td>-5.160773e-01</td>\n",
              "      <td>-6.164580e-01</td>\n",
              "      <td>-6.285137e-01</td>\n",
              "      <td>-5.801731e-01</td>\n",
              "      <td>-5.245255e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>-3.088439e-02</td>\n",
              "      <td>-3.048813e-01</td>\n",
              "      <td>-2.032096e-01</td>\n",
              "      <td>-1.244037e-01</td>\n",
              "      <td>-6.384375e-01</td>\n",
              "      <td>-5.747560e-02</td>\n",
              "      <td>-2.687543e-01</td>\n",
              "      <td>1.169297e-01</td>\n",
              "      <td>-1.503732e-01</td>\n",
              "      <td>-5.353613e-01</td>\n",
              "      <td>...</td>\n",
              "      <td>-7.563980e-02</td>\n",
              "      <td>-1.960840e-02</td>\n",
              "      <td>-1.128988e-01</td>\n",
              "      <td>-4.338661e-01</td>\n",
              "      <td>-4.584438e-01</td>\n",
              "      <td>9.451891e-02</td>\n",
              "      <td>8.912573e-02</td>\n",
              "      <td>6.289690e-02</td>\n",
              "      <td>-4.075856e-01</td>\n",
              "      <td>-5.245255e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>6.806040e-01</td>\n",
              "      <td>7.301328e-01</td>\n",
              "      <td>-1.389076e-01</td>\n",
              "      <td>8.941419e-01</td>\n",
              "      <td>3.752430e-01</td>\n",
              "      <td>-5.747560e-02</td>\n",
              "      <td>-2.687543e-01</td>\n",
              "      <td>8.150599e-01</td>\n",
              "      <td>4.158567e-01</td>\n",
              "      <td>6.270688e-02</td>\n",
              "      <td>...</td>\n",
              "      <td>7.588376e-01</td>\n",
              "      <td>8.939964e-01</td>\n",
              "      <td>5.559989e-01</td>\n",
              "      <td>6.337257e-01</td>\n",
              "      <td>-4.584438e-01</td>\n",
              "      <td>6.440555e-01</td>\n",
              "      <td>6.664215e-01</td>\n",
              "      <td>6.851664e-01</td>\n",
              "      <td>1.792117e-01</td>\n",
              "      <td>1.112980e+00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>2.713428e+00</td>\n",
              "      <td>4.093929e+00</td>\n",
              "      <td>1.010654e+01</td>\n",
              "      <td>3.610264e+00</td>\n",
              "      <td>4.429965e+00</td>\n",
              "      <td>1.739869e+01</td>\n",
              "      <td>8.208570e+00</td>\n",
              "      <td>2.327675e+00</td>\n",
              "      <td>6.417893e+00</td>\n",
              "      <td>4.412293e+00</td>\n",
              "      <td>...</td>\n",
              "      <td>2.812936e+00</td>\n",
              "      <td>2.213648e+00</td>\n",
              "      <td>4.123453e+00</td>\n",
              "      <td>4.904093e+00</td>\n",
              "      <td>1.370800e+01</td>\n",
              "      <td>3.025381e+00</td>\n",
              "      <td>3.039749e+00</td>\n",
              "      <td>3.312527e+00</td>\n",
              "      <td>8.635997e+00</td>\n",
              "      <td>1.112980e+00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8 rows × 21 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5d580fcd-eca9-4188-9785-a038b66be20a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-5d580fcd-eca9-4188-9785-a038b66be20a button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-5d580fcd-eca9-4188-9785-a038b66be20a');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       baseline value  accelerations  fetal_movement  uterine_contractions  \\\n",
              "count    2.126000e+03   2.126000e+03    2.126000e+03          2.126000e+03   \n",
              "mean     4.161509e-16  -1.803982e-16   -1.958452e-15         -2.625683e-15   \n",
              "std      1.000235e+00   1.000235e+00    1.000235e+00          1.000235e+00   \n",
              "min     -2.775197e+00  -8.223883e-01   -2.032096e-01         -1.482465e+00   \n",
              "25%     -7.423728e-01  -8.223883e-01   -2.032096e-01         -8.034341e-01   \n",
              "50%     -3.088439e-02  -3.048813e-01   -2.032096e-01         -1.244037e-01   \n",
              "75%      6.806040e-01   7.301328e-01   -1.389076e-01          8.941419e-01   \n",
              "max      2.713428e+00   4.093929e+00    1.010654e+01          3.610264e+00   \n",
              "\n",
              "       light_decelerations  severe_decelerations  prolongued_decelerations  \\\n",
              "count         2.126000e+03          2.126000e+03              2.126000e+03   \n",
              "mean         -5.127706e-15          7.254767e-16              4.324961e-15   \n",
              "std           1.000235e+00          1.000235e+00              1.000235e+00   \n",
              "min          -6.384375e-01         -5.747560e-02             -2.687543e-01   \n",
              "25%          -6.384375e-01         -5.747560e-02             -2.687543e-01   \n",
              "50%          -6.384375e-01         -5.747560e-02             -2.687543e-01   \n",
              "75%           3.752430e-01         -5.747560e-02             -2.687543e-01   \n",
              "max           4.429965e+00          1.739869e+01              8.208570e+00   \n",
              "\n",
              "       abnormal_short_term_variability  mean_value_of_short_term_variability  \\\n",
              "count                     2.126000e+03                          2.126000e+03   \n",
              "mean                      2.687304e-16                         -2.481552e-16   \n",
              "std                       1.000235e+00                          1.000235e+00   \n",
              "min                      -2.035639e+00                         -1.282833e+00   \n",
              "25%                      -8.720881e-01                         -7.166031e-01   \n",
              "50%                       1.169297e-01                         -1.503732e-01   \n",
              "75%                       8.150599e-01                          4.158567e-01   \n",
              "max                       2.327675e+00                          6.417893e+00   \n",
              "\n",
              "       percentage_of_time_with_abnormal_long_term_variability  ...  \\\n",
              "count                                       2.126000e+03       ...   \n",
              "mean                                        2.291362e-15       ...   \n",
              "std                                         1.000235e+00       ...   \n",
              "min                                        -5.353613e-01       ...   \n",
              "25%                                        -5.353613e-01       ...   \n",
              "50%                                        -5.353613e-01       ...   \n",
              "75%                                         6.270688e-02       ...   \n",
              "max                                         4.412293e+00       ...   \n",
              "\n",
              "       histogram_width  histogram_min  histogram_max  \\\n",
              "count     2.126000e+03   2.126000e+03   2.126000e+03   \n",
              "mean      8.564279e-17  -6.120326e-17  -4.047144e-17   \n",
              "std       1.000235e+00   1.000235e+00   1.000235e+00   \n",
              "min      -1.731757e+00  -1.474609e+00  -2.342558e+00   \n",
              "25%      -8.587648e-01  -8.993760e-01  -6.703135e-01   \n",
              "50%      -7.563980e-02  -1.960840e-02  -1.128988e-01   \n",
              "75%       7.588376e-01   8.939964e-01   5.559989e-01   \n",
              "max       2.812936e+00   2.213648e+00   4.123453e+00   \n",
              "\n",
              "       histogram_number_of_peaks  histogram_number_of_zeroes  histogram_mode  \\\n",
              "count               2.126000e+03                2.126000e+03    2.126000e+03   \n",
              "mean               -4.797041e-16                8.397171e-17    6.141215e-17   \n",
              "std                 1.000235e+00                1.000235e+00    1.000235e+00   \n",
              "min                -1.145594e+00               -4.584438e-01   -4.729191e+00   \n",
              "25%                -7.897301e-01               -4.584438e-01   -5.160773e-01   \n",
              "50%                -4.338661e-01               -4.584438e-01    9.451891e-02   \n",
              "75%                 6.337257e-01               -4.584438e-01    6.440555e-01   \n",
              "max                 4.904093e+00                1.370800e+01    3.025381e+00   \n",
              "\n",
              "       histogram_mean  histogram_median  histogram_variance  \\\n",
              "count    2.126000e+03      2.126000e+03        2.126000e+03   \n",
              "mean    -4.183964e-16      1.404751e-16       -3.634597e-17   \n",
              "std      1.000235e+00      1.000235e+00        1.000235e+00   \n",
              "min     -3.951945e+00     -4.223849e+00       -6.492081e-01   \n",
              "25%     -6.164580e-01     -6.285137e-01       -5.801731e-01   \n",
              "50%      8.912573e-02      6.289690e-02       -4.075856e-01   \n",
              "75%      6.664215e-01      6.851664e-01        1.792117e-01   \n",
              "max      3.039749e+00      3.312527e+00        8.635997e+00   \n",
              "\n",
              "       histogram_tendency  \n",
              "count        2.126000e+03  \n",
              "mean         5.783500e-16  \n",
              "std          1.000235e+00  \n",
              "min         -2.162031e+00  \n",
              "25%         -5.245255e-01  \n",
              "50%         -5.245255e-01  \n",
              "75%          1.112980e+00  \n",
              "max          1.112980e+00  \n",
              "\n",
              "[8 rows x 21 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#New data distributions\n",
        "x_tr.hist(bins=20, figsize=(30,20))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "x0OfCWZYtMIu",
        "outputId": "7c51cb1e-4dc5-49d3-f31a-7c6f30ba12e2"
      },
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f7f82aef890>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f8137ecd0>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f8146b2d0>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f812cd710>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f81276790>],\n",
              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f7f7b340b10>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f7b253c50>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f7b22c4d0>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f7b22ce10>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f7b317d10>],\n",
              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f7f7b08c7d0>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f7aea49d0>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f70b51e50>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f714401d0>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f7ad7e3d0>],\n",
              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f7f7ad65150>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f7ae3a510>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f7b053450>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f7b156150>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f70889fd0>],\n",
              "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f7f708c15d0>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f82055b50>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f82199590>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f833d91d0>,\n",
              "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f7f7a9f06d0>]],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 50
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 2160x1440 with 25 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Normalized data correlation matrix\n",
        "xy = pd.concat([x_tr,dataFrame['fetal_health']], axis=1)\n",
        "corr_matrix = xy.corr()\n",
        "corr_matrix['fetal_health'].sort_values(ascending=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9AM7440Dtg2j",
        "outputId": "dde90f78-3c4e-4b63-9805-727777a5c4f9"
      },
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "fetal_health                                              1.000000\n",
              "prolongued_decelerations                                  0.484859\n",
              "abnormal_short_term_variability                           0.471191\n",
              "percentage_of_time_with_abnormal_long_term_variability    0.426146\n",
              "histogram_variance                                        0.206630\n",
              "baseline value                                            0.148151\n",
              "severe_decelerations                                      0.131934\n",
              "fetal_movement                                            0.088010\n",
              "histogram_min                                             0.063175\n",
              "light_decelerations                                       0.058870\n",
              "histogram_number_of_peaks                                -0.005673\n",
              "histogram_number_of_zeroes                               -0.016682\n",
              "histogram_max                                            -0.045265\n",
              "histogram_width                                          -0.068789\n",
              "mean_value_of_short_term_variability                     -0.103382\n",
              "histogram_tendency                                       -0.131976\n",
              "mean_value_of_long_term_variability                      -0.133643\n",
              "uterine_contractions                                     -0.204894\n",
              "histogram_median                                         -0.205033\n",
              "histogram_mean                                           -0.226985\n",
              "histogram_mode                                           -0.250412\n",
              "accelerations                                            -0.364066\n",
              "Name: fetal_health, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "No major change to correlation matrix after normalization, the NN model will now be created."
      ],
      "metadata": {
        "id": "6RrT-_BIt-WG"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#ANN Sequential Model\n",
        "Now that the data has been visualized, normalized, and correlated an ANN will be created to attempt to accuractly make predictions on fetal health based on the numeric attributes provided."
      ],
      "metadata": {
        "id": "KpASYqyWepxa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Get y\n",
        "y = xy['fetal_health']\n",
        "\n",
        "#The keras model layer density is 0 indexed, the data that is in the dataset is 1 indexed. To deal with this I will change the data from 1,2,3\n",
        "#to 0,1,2 where 0 is 1, 1 is 2, and 2 is 3\n",
        "yList = []\n",
        "for i in y:\n",
        "  if (i == 1): \n",
        "    yList.append(0)\n",
        "  if (i == 2): \n",
        "    yList.append(1)\n",
        "  if (i == 3): \n",
        "    yList.append(2)\n",
        "\n",
        "dataFrame['updated_fetal_health'] = yList\n",
        "\n",
        "#Seperate training and testing data using 80/20 split\n",
        "from sklearn.model_selection import train_test_split\n",
        "x_Train, x_Test, y_Train, y_Test = train_test_split(x_tr, dataFrame['updated_fetal_health'], test_size=0.2, random_state=42)\n",
        "\n",
        "#Import the libs needed for neural networks\n",
        "import tensorflow as tf\n",
        "from tensorflow import keras\n",
        "from keras.layers import Dense, Dropout, Flatten\n",
        "\n",
        "#Intialize the neural network\n",
        "myNeural_Network = keras.models.Sequential([keras.layers.Flatten(input_shape=[x_Train.shape[1],]), keras.layers.Dense(100, activation=\"relu\"), \n",
        "        keras.layers.Dense(3, activation=\"softmax\")])\n",
        "\n",
        "#Summarize the network created\n",
        "myNeural_Network.summary()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9cAIOziuuCFD",
        "outputId": "a848ffef-c5dc-4c68-e157-38920f17ab88"
      },
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential_86\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " flatten_86 (Flatten)        (None, 21)                0         \n",
            "                                                                 \n",
            " dense_172 (Dense)           (None, 100)               2200      \n",
            "                                                                 \n",
            " dense_173 (Dense)           (None, 3)                 303       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 2,503\n",
            "Trainable params: 2,503\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Compile the network\n",
        "myNeural_Network.compile(loss=\"sparse_categorical_crossentropy\", optimizer=\"sgd\", metrics=[\"accuracy\"])\n",
        "\n",
        "#Run the model\n",
        "myNN_History = myNeural_Network.fit(x_Train, y_Train, epochs=100, batch_size=42, validation_data=(x_Test, y_Test), verbose=0)"
      ],
      "metadata": {
        "id": "Vrn26qhE5m4z"
      },
      "execution_count": 53,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Plot the model and accuracy loss graph\n",
        "pd.DataFrame(myNN_History.history).plot(figsize=(10, 5))\n",
        "plt.grid(True)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        },
        "id": "s_5-HC9bASYf",
        "outputId": "7d4b61f6-7919-46d0-c606-bcfda4958276"
      },
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Based on the accuracy and loss graph the above ANN performed well on the fetal health dataset."
      ],
      "metadata": {
        "id": "xQi4K5gyj8sz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Create the confusion matrix\n",
        "from sklearn.metrics import classification_report, confusion_matrix\n",
        "y_Pred = myNeural_Network.predict(x_Test)\n",
        "y_Pred = np.argmax(y_Pred, axis=1)\n",
        "\n",
        "#Labels\n",
        "labels = [0,1,2]\n",
        "confusionMatrix = confusion_matrix(y_Test, y_Pred, labels=labels)\n",
        "\n",
        "#Plot confusion matrix\n",
        "sns.heatmap(confusionMatrix, annot=True, linewidths=.5, square = True, cmap=\"BuPu\")\n",
        "plt.ylabel('Actual')\n",
        "plt.xlabel('Predicted')\n",
        "\n",
        "#Print classification report\n",
        "classReport = classification_report(y_true=y_Test, y_pred = y_Pred, labels = labels)\n",
        "print(classReport)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 453
        },
        "id": "3CkTUEPBAmaK",
        "outputId": "b85881f8-710b-4bac-efcb-24e7736f666e"
      },
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.96      0.96      0.96       333\n",
            "           1       0.73      0.75      0.74        64\n",
            "           2       0.89      0.83      0.86        29\n",
            "\n",
            "    accuracy                           0.92       426\n",
            "   macro avg       0.86      0.85      0.85       426\n",
            "weighted avg       0.92      0.92      0.92       426\n",
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The confusion matrix shows that while the model overall performed well, it did much better in prediciting normal (0) fetal health then it did for suspect (1) and pathelogical (2) cases. This is most likley due to the uneven distribution of the target attribute in the dataset, with there being far more normal instances then suspect and pathelogical instances.\n",
        "\n",
        "The same model will now be tested through k-cross folds validation."
      ],
      "metadata": {
        "id": "1c8cbtm3kEWW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#The same model will now be tested with cross validation\n",
        "from keras.wrappers.scikit_learn import KerasClassifier\n",
        "from sklearn.model_selection import StratifiedKFold\n",
        "from sklearn.model_selection import cross_val_score\n",
        "\n",
        "#Re-create model in callable function for kerasClassifier\n",
        "def create_model(neurons=100):\n",
        "  my_model = keras.models.Sequential([keras.layers.Flatten(), keras.layers.Dense(neurons, activation=\"relu\"), \n",
        "        keras.layers.Dense(3, activation=\"softmax\")])\n",
        "  my_model.compile(loss=\"sparse_categorical_crossentropy\", optimizer=\"sgd\", metrics=[\"accuracy\"])\n",
        "  return my_model\n",
        "\n",
        "estimator = KerasClassifier(build_fn=create_model, epochs=100, verbose=0)\n",
        "kfold = StratifiedKFold(n_splits=5, shuffle=True)\n",
        "results = cross_val_score(estimator, x_tr, dataFrame['updated_fetal_health'], cv=kfold)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_6E41-7qKjQP",
        "outputId": "e8067bcc-9d88-4bba-f203-c6353306fe6b"
      },
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:13: DeprecationWarning: KerasClassifier is deprecated, use Sci-Keras (https://github.com/adriangb/scikeras) instead. See https://www.adriangb.com/scikeras/stable/migration.html for help migrating.\n",
            "  del sys.path[0]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Display results\n",
        "accuracy = results.mean()*100\n",
        "percent_Error = results.std()*100\n",
        "\n",
        "print(\"Model Accuracy: \" + str(accuracy))\n",
        "print(\"Percent error: +/- \" + str(percent_Error))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bwyqV8WpO7xL",
        "outputId": "e2fbec7f-cb7b-4346-dcf7-a7d7545f1520"
      },
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model Accuracy: 91.25147819519043\n",
            "Percent error: +/- 1.7171035164988266\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Model accuracy calculated through K-cross folds validation is similar to the accuray shown with the accuracy/loss graph and the confusion matrix displayed above."
      ],
      "metadata": {
        "id": "X_DH4dwSklq4"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#ANN Grid Search\n",
        "Even though the model has performed well on this dataset, we will try to further optimize it using Grid Search, the hyper-parameters that will be grid searched are hidden layer neuron counts, batch sizes, and number of epochs. "
      ],
      "metadata": {
        "id": "7-hbXltufbzp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Run a grid search experimenting with different numbers of neurons in the hidden layer, batch sizes, and number of epochs\n",
        "from sklearn.model_selection import GridSearchCV\n",
        "ann_GridSearch_Params = {'neurons':[100, 150], 'batch_size':[42,60,100], 'epochs':[100, 150]}\n",
        "grid = GridSearchCV(estimator, ann_GridSearch_Params, cv=3)\n",
        "grid.fit(x_tr, dataFrame['updated_fetal_health'])\n",
        "print(\"The best NN grid search accuracy: %.2f\\n\" % grid.best_score_)\n",
        "print(\"The best NN hyperparameters:\", grid.best_params_)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6Dy1EQdwQW4C",
        "outputId": "2892114b-cfc1-47d9-e8d3-f60b0f7804d2"
      },
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The best NN grid search accuracy: 0.85\n",
            "\n",
            "The best NN hyperparameters: {'batch_size': 60, 'epochs': 150, 'neurons': 100}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Create bar graph\n",
        "labels = ['ANN', 'GS ANN']\n",
        "modelScores = [accuracy, grid.best_score_*100]\n",
        "\n",
        "x = np.arange(len(labels))\n",
        "width = 0.5\n",
        "\n",
        "fig, ax = plt.subplots()\n",
        "rects1 = ax.bar(x - width/2, modelScores, width, label='ANN Accuracy', color='pink')\n",
        "\n",
        "ax.set_ylabel('ANN Accuracy')\n",
        "ax.set_xticks(x)\n",
        "ax.set_ylim(0,100)\n",
        "ax.set_xticklabels(labels)\n",
        "ax.legend(bbox_to_anchor = (1.4, 1.0), loc='upper right')\n",
        "\n",
        "plt.title('ANN vs GS ANN')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "id": "-etO4S6NdeyM",
        "outputId": "2f3e06eb-c8d6-40a3-a52a-858307b26030"
      },
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The above grid search took a very long time to run (over 3 minutes) and did not provide an improvement in model accuracy over the orginally tested model. This is surprising as the original model hyper-parameters (batch_size = 42, neurons = 100, number of epochs = 100) are included in the hyper-parameter options for this grid search, I would have assumed that the grid search would have at least returned the same level of accuracy as the original model. Perphas the grid search is not properly changing the ANNs hyper-parameters. 84% is still a decent result though."
      ],
      "metadata": {
        "id": "UscrLobLlmth"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Report Summary"
      ],
      "metadata": {
        "id": "nKIm8qECDz4C"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "The fetal health dataset is composed of numeric attributes extracted from Cardiotocogram exams. The attributes represent the overall health of a fetus. The objective of this report is to create an ANN (Artificial Neural Network) capable of using the numeric attributes provided to determine fetal health. The determination will one of three options, normal (no health issues), suspect (possible health issues), and pathelogical (clear health issues). The training instances in this dataset have been labeled by renowned medical experts. \n",
        "\n",
        "****\n",
        "\n",
        "**Data Visualization Summary**\n",
        "\n",
        "In this report the dataset was analyzed using histograms for the numeric attributes, and a bar graph for the target attribute. One thing that stood out right away from visual analysis was the high number of values equal to 0 in the dataset. Multiple numeric attributes such as all of the accelerations/decelerations attributes, percentage_of_time_with_abnormal_long_term_variability, histogram_number_of_zeroes, and histogram_variance mostly consisted of values equal to 0, while other numeric attributes had a sparse amount of 0 values. Due to this the attributes that had a high amount of 0 values were not imputed, as I concluded that 0 values in those attributes most likley indicate the fetus may be healthy. The attributes that did not have a high frequency of 0 values and for which 0 values seemed to be missing data based on the attribute description provided on Kaggle were imputed using their respective medians. These attributes are histogram_number_of_peaks, histogram_width, mean_value_of_short_term_variablity and mean_value_of_long_term_variablity. The second thing that stood out was the distribution of categories in the target attribute, the distribution was highly skewed with the overwhelming majority of instances being labeled as normal (1). This is most likely due to the fact that the overwhelming number of fetuses are healthy in the area in which this data was gathered. This lack of an even distribution will make it tough for our ANN to learn about suspect and pathelogical instances as well as it will for normal instances.\n",
        "\n",
        "****\n",
        "\n",
        "**Data Normalization Summary**\n",
        "\n",
        "After data visualization was complete the dataset was normalized using median imputing for the attributes named above, and the sckit-learn standard scalar (all numeric attributes except target). After imputing and scaling were performed the dataset was visualized again showing a slight improvement in data distribution for multiple numeric attributes.\n",
        "\n",
        "****\n",
        "\n",
        "**Data Correlation Summary**\n",
        "\n",
        "Both before and after scaling the numeric attributes a correlation matrix was created comparing the numeric attributes to the target attribute (fetal health). Visulization of the correlation matrix in both list and heatmap form showed the attributes with the highest correlation to the target attribute, these were prolongued_decelerations, abnormal_short_term_variability, and percentage_of_time_with_abnormal_long_term_variability. While they did have the highest correlation, at best the correlation was mild. No major difference was made to the correlation matrix after scaling was done.\n",
        "\n",
        "****\n",
        "\n",
        "**ANN Model Peformance Summary**\n",
        "\n",
        "After the dataset was imputed and scaled a sequential ANN with one hidden layer was created (100 neurons). The ANN created uses 0-indexing for its output layer, this means that if a target attribute has three numeric categories the ANN excepts them to be 0, 1, and 2, in this dataset the target attributes values are 1, 2, and 3. To work around this an additional column was added to the dataset updating the target attribute from 1,2,3 to 0,1,2, this new column was used as the y in the created ANN. The first method used to test the ANN was the model accuracy/loss graph. This showed a good performance as the accuracy and validation accuracy lines reach a deseriable accuracy score quickly and stay there. The next method used to test the model created was a confusion matrix and classification report, this also showed good model performance but provided more detail. This detail showed that as expected the model was much better at classifying normal fetal health then it was for suspect and pathelogical. This poses a problem if this model was ever to be used in the real world as the most important classifications are suspect and pathelogical (the whole point is to find issues early enough to make a difference). The third method used to test the model was k-cross folds validation. For this step the model needed to be re-created in a callable function, the results showed the same as the previous two methods with a model accuracy score of on average 90%. \n",
        "\n",
        "****\n",
        "\n",
        "**Grid Search Test**\n",
        "\n",
        "Even though the ANN model created in the previous section had an overall solid performance (90% accuracy), some things still need to be improved upon, such as the ability to accuratly classify suspect and pathelogical instances. To do so a Grid Search attempting to optimize the hyper-parameters batch-size, total neurons in the hidden layer, and total number of epochs was created. The orginal plan was to start with just these three parameters and then expand to include more such as the number of hidden layers but the grid search took over three minutes to complete and provided a less accurate model (best performing combo was 84%). Due to this no additional hyper-parameters were added to the grid search optimization. Reasons for the lack of improvement via Grid Search may be due to a mistake made which I have yet to identify. The original parameters were passed to the Grid Search so at worst I assumed it would return the same accuracy as the original model.\n",
        "\n",
        "****\n",
        "\n",
        "**Total Summary**\n",
        "\n",
        "In summary an ANN was modeled using the fetal health dataset that can very accuratly predict instances of normal fetal health. The model performed somewhat well in instances of suspect and pathelogical health but left alot to improve upon. To increase the accuracy of suspect and pathelogical classifications more training instances of those two types will need to be passed to the model."
      ],
      "metadata": {
        "id": "imX_UYIrD156"
      }
    }
  ]
}