Data Preprocessing - Encoding and Resampling.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "bf3ecd42",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sb\n",
    "import plotly.graph_objects as go\n",
    "\n",
    "sb.set()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "28752438",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Extract the cleaned dataset for data preprocessing\n",
    "df = pd.read_csv(\"1-cleaned-heart-disease-dataset.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "faea906f",
   "metadata": {},
   "source": [
    "# Encoding of categorical variables using OneHotEncoding\n",
    "#### This allows for our classification model from sklearn that require numeric data for categorcial variables to handle them directly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "17be86ea",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 319795 entries, 0 to 319794\n",
      "Data columns (total 44 columns):\n",
      " #   Column                               Non-Null Count   Dtype  \n",
      "---  ------                               --------------   -----  \n",
      " 0   AGECATEGORY_18_24                    319795 non-null  float64\n",
      " 1   AGECATEGORY_25_29                    319795 non-null  float64\n",
      " 2   AGECATEGORY_30_34                    319795 non-null  float64\n",
      " 3   AGECATEGORY_35_39                    319795 non-null  float64\n",
      " 4   AGECATEGORY_40_44                    319795 non-null  float64\n",
      " 5   AGECATEGORY_45_49                    319795 non-null  float64\n",
      " 6   AGECATEGORY_50_54                    319795 non-null  float64\n",
      " 7   AGECATEGORY_55_59                    319795 non-null  float64\n",
      " 8   AGECATEGORY_60_64                    319795 non-null  float64\n",
      " 9   AGECATEGORY_65_69                    319795 non-null  float64\n",
      " 10  AGECATEGORY_70_74                    319795 non-null  float64\n",
      " 11  AGECATEGORY_75_79                    319795 non-null  float64\n",
      " 12  AGECATEGORY_80_OR_OLDER              319795 non-null  float64\n",
      " 13  RACE_AMERICAN_INDIAN/ALASKAN_NATIVE  319795 non-null  float64\n",
      " 14  RACE_ASIAN                           319795 non-null  float64\n",
      " 15  RACE_BLACK                           319795 non-null  float64\n",
      " 16  RACE_HISPANIC                        319795 non-null  float64\n",
      " 17  RACE_OTHER                           319795 non-null  float64\n",
      " 18  RACE_WHITE                           319795 non-null  float64\n",
      " 19  SEX_FEMALE                           319795 non-null  float64\n",
      " 20  SEX_MALE                             319795 non-null  float64\n",
      " 21  SMOKING_NO                           319795 non-null  float64\n",
      " 22  SMOKING_YES                          319795 non-null  float64\n",
      " 23  ALCOHOLDRINKING_NO                   319795 non-null  float64\n",
      " 24  ALCOHOLDRINKING_YES                  319795 non-null  float64\n",
      " 25  STROKE_NO                            319795 non-null  float64\n",
      " 26  STROKE_YES                           319795 non-null  float64\n",
      " 27  DIFFWALKING_NO                       319795 non-null  float64\n",
      " 28  DIFFWALKING_YES                      319795 non-null  float64\n",
      " 29  DIABETIC_NO                          319795 non-null  float64\n",
      " 30  DIABETIC_YES                         319795 non-null  float64\n",
      " 31  PHYSICALACTIVITY_NO                  319795 non-null  float64\n",
      " 32  PHYSICALACTIVITY_YES                 319795 non-null  float64\n",
      " 33  GENHEALTH_EXCELLENT                  319795 non-null  float64\n",
      " 34  GENHEALTH_FAIR                       319795 non-null  float64\n",
      " 35  GENHEALTH_GOOD                       319795 non-null  float64\n",
      " 36  GENHEALTH_POOR                       319795 non-null  float64\n",
      " 37  GENHEALTH_VERY_GOOD                  319795 non-null  float64\n",
      " 38  ASTHMA_NO                            319795 non-null  float64\n",
      " 39  ASTHMA_YES                           319795 non-null  float64\n",
      " 40  KIDNEYDISEASE_NO                     319795 non-null  float64\n",
      " 41  KIDNEYDISEASE_YES                    319795 non-null  float64\n",
      " 42  SKINCANCER_NO                        319795 non-null  float64\n",
      " 43  SKINCANCER_YES                       319795 non-null  float64\n",
      "dtypes: float64(44)\n",
      "memory usage: 107.4 MB\n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import OneHotEncoder\n",
    "ohe = OneHotEncoder()\n",
    "\n",
    "# extract out the categorical variables for one hot encoding, except the response\n",
    "df_cat = df[['AGECATEGORY','RACE','SEX','SMOKING', 'ALCOHOLDRINKING', 'STROKE', 'DIFFWALKING', 'DIABETIC','PHYSICALACTIVITY', 'GENHEALTH', 'ASTHMA', 'KIDNEYDISEASE', 'SKINCANCER']]\n",
    "\n",
    "#onehotencoding\n",
    "ohe.fit(df_cat)\n",
    "\n",
    "#create the new one hot categorical variables dataframe\n",
    "df_cat_ohe = pd.DataFrame(ohe.transform(df_cat).toarray(), columns = ohe.get_feature_names(df_cat.columns))\n",
    "\n",
    "# Reformat the column names cleaner again\n",
    "df_cat_ohe.columns = df_cat_ohe.columns.str.replace(\" \", \"_\")\n",
    "df_cat_ohe.columns = df_cat_ohe.columns.str.replace(\"-\", \"_\")\n",
    "df_cat_ohe.columns = df_cat_ohe.columns.str.upper()\n",
    "df_cat_ohe.info()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "deab351a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>BMI</th>\n",
       "      <th>PHYSICALHEALTH</th>\n",
       "      <th>MENTALHEALTH</th>\n",
       "      <th>SLEEPTIME</th>\n",
       "      <th>AGECATEGORY_18_24</th>\n",
       "      <th>AGECATEGORY_25_29</th>\n",
       "      <th>AGECATEGORY_30_34</th>\n",
       "      <th>AGECATEGORY_35_39</th>\n",
       "      <th>AGECATEGORY_40_44</th>\n",
       "      <th>AGECATEGORY_45_49</th>\n",
       "      <th>...</th>\n",
       "      <th>GENHEALTH_GOOD</th>\n",
       "      <th>GENHEALTH_POOR</th>\n",
       "      <th>GENHEALTH_VERY_GOOD</th>\n",
       "      <th>ASTHMA_NO</th>\n",
       "      <th>ASTHMA_YES</th>\n",
       "      <th>KIDNEYDISEASE_NO</th>\n",
       "      <th>KIDNEYDISEASE_YES</th>\n",
       "      <th>SKINCANCER_NO</th>\n",
       "      <th>SKINCANCER_YES</th>\n",
       "      <th>HEARTDISEASE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.60</td>\n",
       "      <td>3.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20.34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>26.58</td>\n",
       "      <td>20.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>24.21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>23.71</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>319790</th>\n",
       "      <td>27.41</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>319791</th>\n",
       "      <td>29.84</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>319792</th>\n",
       "      <td>24.24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>1.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>319793</th>\n",
       "      <td>32.81</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>319794</th>\n",
       "      <td>46.56</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>319795 rows × 49 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          BMI  PHYSICALHEALTH  MENTALHEALTH  SLEEPTIME  AGECATEGORY_18_24  \\\n",
       "0       16.60             3.0          30.0        5.0                0.0   \n",
       "1       20.34             0.0           0.0        7.0                0.0   \n",
       "2       26.58            20.0          30.0        8.0                0.0   \n",
       "3       24.21             0.0           0.0        6.0                0.0   \n",
       "4       23.71            28.0           0.0        8.0                0.0   \n",
       "...       ...             ...           ...        ...                ...   \n",
       "319790  27.41             7.0           0.0        6.0                0.0   \n",
       "319791  29.84             0.0           0.0        5.0                0.0   \n",
       "319792  24.24             0.0           0.0        6.0                0.0   \n",
       "319793  32.81             0.0           0.0       12.0                0.0   \n",
       "319794  46.56             0.0           0.0        8.0                0.0   \n",
       "\n",
       "        AGECATEGORY_25_29  AGECATEGORY_30_34  AGECATEGORY_35_39  \\\n",
       "0                     0.0                0.0                0.0   \n",
       "1                     0.0                0.0                0.0   \n",
       "2                     0.0                0.0                0.0   \n",
       "3                     0.0                0.0                0.0   \n",
       "4                     0.0                0.0                0.0   \n",
       "...                   ...                ...                ...   \n",
       "319790                0.0                0.0                0.0   \n",
       "319791                0.0                0.0                1.0   \n",
       "319792                0.0                0.0                0.0   \n",
       "319793                1.0                0.0                0.0   \n",
       "319794                0.0                0.0                0.0   \n",
       "\n",
       "        AGECATEGORY_40_44  AGECATEGORY_45_49  ...  GENHEALTH_GOOD  \\\n",
       "0                     0.0                0.0  ...             0.0   \n",
       "1                     0.0                0.0  ...             0.0   \n",
       "2                     0.0                0.0  ...             0.0   \n",
       "3                     0.0                0.0  ...             1.0   \n",
       "4                     1.0                0.0  ...             0.0   \n",
       "...                   ...                ...  ...             ...   \n",
       "319790                0.0                0.0  ...             0.0   \n",
       "319791                0.0                0.0  ...             0.0   \n",
       "319792                0.0                1.0  ...             1.0   \n",
       "319793                0.0                0.0  ...             1.0   \n",
       "319794                0.0                0.0  ...             1.0   \n",
       "\n",
       "        GENHEALTH_POOR  GENHEALTH_VERY_GOOD  ASTHMA_NO  ASTHMA_YES  \\\n",
       "0                  0.0                  1.0        0.0         1.0   \n",
       "1                  0.0                  1.0        1.0         0.0   \n",
       "2                  0.0                  0.0        0.0         1.0   \n",
       "3                  0.0                  0.0        1.0         0.0   \n",
       "4                  0.0                  1.0        1.0         0.0   \n",
       "...                ...                  ...        ...         ...   \n",
       "319790             0.0                  0.0        0.0         1.0   \n",
       "319791             0.0                  1.0        0.0         1.0   \n",
       "319792             0.0                  0.0        1.0         0.0   \n",
       "319793             0.0                  0.0        1.0         0.0   \n",
       "319794             0.0                  0.0        1.0         0.0   \n",
       "\n",
       "        KIDNEYDISEASE_NO  KIDNEYDISEASE_YES  SKINCANCER_NO  SKINCANCER_YES  \\\n",
       "0                    1.0                0.0            0.0             1.0   \n",
       "1                    1.0                0.0            1.0             0.0   \n",
       "2                    1.0                0.0            1.0             0.0   \n",
       "3                    1.0                0.0            0.0             1.0   \n",
       "4                    1.0                0.0            1.0             0.0   \n",
       "...                  ...                ...            ...             ...   \n",
       "319790               1.0                0.0            1.0             0.0   \n",
       "319791               1.0                0.0            1.0             0.0   \n",
       "319792               1.0                0.0            1.0             0.0   \n",
       "319793               1.0                0.0            1.0             0.0   \n",
       "319794               1.0                0.0            1.0             0.0   \n",
       "\n",
       "        HEARTDISEASE  \n",
       "0                 No  \n",
       "1                 No  \n",
       "2                 No  \n",
       "3                 No  \n",
       "4                 No  \n",
       "...              ...  \n",
       "319790           Yes  \n",
       "319791            No  \n",
       "319792            No  \n",
       "319793            No  \n",
       "319794            No  \n",
       "\n",
       "[319795 rows x 49 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Combining Numeric vairiables, OHE categorical variables and the response variables into the final data frame to be used\n",
    "df_num = df[['BMI', 'PHYSICALHEALTH', 'MENTALHEALTH', 'SLEEPTIME']]\n",
    "df_responseVar = df['HEARTDISEASE']\n",
    "df_final = pd.concat([df_num, df_cat_ohe, df_responseVar], \n",
    "                           sort = False, axis = 1).reindex(df_num.index)\n",
    "df_final"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1679163b",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "ab4f721e",
   "metadata": {},
   "source": [
    "## Before Resampling, visualise the severe Imbalance in the categorical response variable - \"HeartDisease\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "05513967",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(27373, 49)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(292422, 49)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x2507b1ef6d0>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Clear imbalance of classes, \"No\" for \"HEARTDISEASE\" far more than \"Yes\" for \"HEARTDISEASE\"\n",
    "display(df_final[df_final.HEARTDISEASE == 'Yes'].shape)\n",
    "display(df_final[df_final.HEARTDISEASE == 'No'].shape)\n",
    "\n",
    "# visual representation of the imbalances\n",
    "sb.catplot(y = \"HEARTDISEASE\", data = df_final, kind = \"count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d98ee0f",
   "metadata": {},
   "source": [
    "## Evidence of poor results without resampling below (Due to severe imbalance)\n",
    "\n",
    "##### Machine Learning, creation of classification tree. Results: High false negative rates (Extremely low prediction accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2d9a785d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import essential models and functions from sklearn\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.tree import plot_tree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7b706260",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1728x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Extract Response and Predictors\n",
    "y = pd.DataFrame(df_final['HEARTDISEASE'])\n",
    "X = pd.DataFrame(df_final.drop('HEARTDISEASE', axis = 1))\n",
    "\n",
    "# Split the Dataset into Train and Test\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.3)\n",
    "\n",
    "# Decision Tree using Train Data\n",
    "dectree = DecisionTreeClassifier(max_depth = 4)\n",
    "dectree.fit(X_train, y_train)                    # train the decision tree model\n",
    "\n",
    "# Plot the trained Decision Tree\n",
    "f = plt.figure(figsize=(24,12))\n",
    "plot_tree(dectree, filled=True, rounded=True, \n",
    "          feature_names=X_train.columns, \n",
    "          class_names=[\"No\",\"Yes\"], fontsize = 10)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1a47a71c",
   "metadata": {},
   "outputs": [],
   "source": [
    "### Analysis of first decision tree classification model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8ebce856",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Data\n",
      "Accuracy  :\t 0.9153339646915875\n",
      "\n",
      "TPR Train :\t 0.013623978201634877\n",
      "TNR Train :\t 0.9993700310589338\n",
      "\n",
      "FPR Train :\t 0.0006299689410661614\n",
      "FNR Train :\t 0.9863760217983651\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Predict the Response corresponding to Predictors\n",
    "y_train_pred = dectree.predict(X_train)\n",
    "\n",
    "# Print the Classification Accuracy\n",
    "print(\"Train Data\")\n",
    "print(\"Accuracy  :\\t\", dectree.score(X_train, y_train))\n",
    "print()\n",
    "\n",
    "# Print the Accuracy Measures from the Confusion Matrix\n",
    "cmTrain = confusion_matrix(y_train, y_train_pred)\n",
    "tpTrain = cmTrain[1][1] # True Positives : Yes (1) predicted Yes (1)\n",
    "fpTrain = cmTrain[0][1] # False Positives : No (0) predicted Yes (1)\n",
    "tnTrain = cmTrain[0][0] # True Negatives : No (0) predicted No (0)\n",
    "fnTrain = cmTrain[1][0] # False Negatives : Yes (1) predicted No (0)\n",
    "\n",
    "print(\"TPR Train :\\t\", (tpTrain/(tpTrain + fnTrain)))\n",
    "print(\"TNR Train :\\t\", (tnTrain/(tnTrain + fpTrain)))\n",
    "print()\n",
    "\n",
    "print(\"FPR Train :\\t\", (fpTrain/(tnTrain + fpTrain)))\n",
    "print(\"FNR Train :\\t\", (fnTrain/(tpTrain + fnTrain)))\n",
    "\n",
    "# Plot the two-way Confusion Matrix\n",
    "sb.heatmap(confusion_matrix(y_train, y_train_pred), \n",
    "           annot = True, fmt=\".0f\", annot_kws={\"size\": 18})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a54c7d1c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test Data\n",
      "Accuracy  :\t 0.9141120920584955\n",
      "\n",
      "TPR Test :\t 0.012546748703100494\n",
      "TNR Test :\t 0.9993725042783799\n",
      "\n",
      "FPR Test :\t 0.0006274957216200798\n",
      "FNR Test :\t 0.9874532512968995\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_test_pred = dectree.predict(X_test)\n",
    "\n",
    "# Print the Classification Accuracy\n",
    "print(\"Test Data\")\n",
    "print(\"Accuracy  :\\t\", dectree.score(X_test, y_test))\n",
    "print()\n",
    "\n",
    "# Print the Accuracy Measures from the Confusion Matrix\n",
    "cmTest = confusion_matrix(y_test, y_test_pred)\n",
    "tpTest = cmTest[1][1] # True Positives : Yes (1) predicted Yes (1)\n",
    "fpTest = cmTest[0][1] # False Positives : No (0) predicted Yes (1)\n",
    "tnTest = cmTest[0][0] # True Negatives : No (0) predicted No (0)\n",
    "fnTest = cmTest[1][0] # False Negatives : Yes (1) predicted No (0)\n",
    "\n",
    "print(\"TPR Test :\\t\", (tpTest/(tpTest + fnTest)))\n",
    "print(\"TNR Test :\\t\", (tnTest/(tnTest + fpTest)))\n",
    "print()\n",
    "\n",
    "print(\"FPR Test :\\t\", (fpTest/(fpTest + tnTest)))\n",
    "print(\"FNR Test :\\t\", (fnTest/(fnTest + tpTest)))\n",
    "\n",
    "# Plot the two-way Confusion Matrix\n",
    "sb.heatmap(confusion_matrix(y_test, y_test_pred), \n",
    "           annot = True, fmt=\".0f\", annot_kws={\"size\": 18})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4cfcad1d",
   "metadata": {},
   "source": [
    "### Findings: \n",
    "\n",
    "#### Very bad model, insanely high false negative rate of 96.9% !\n",
    "#### This will result in catastrophic consequences if the chance of misdiagnosing someone actually with heart disease as someone without heart disease is so high. \n",
    "\n",
    "### Reason:\n",
    "\n",
    "#### Classification algorithms will tend to have a low prediction accuracy toward the minority class because they assume that there is a balance between the classes.\n",
    "\n",
    "#### Conclusion: Perform Resampling to balance the imbalance in classes of the response \"HeartDisease\" before machine learning for better prediction accuracy (Lower False Negative Rate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "29c727d5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "03dee573",
   "metadata": {},
   "source": [
    "# Resampling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "daf29e1f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Trying both upsampling and downsampling:\n",
    "\n",
    "# Import the essential function from sklearn\n",
    "from sklearn.utils import resample\n",
    "\n",
    "# extract the different classes\n",
    "hd_yes = df_final[df_final.HEARTDISEASE == 'Yes']\n",
    "hd_no = df_final[df_final.HEARTDISEASE == 'No']\n",
    " \n",
    "# Upsample the \"Yes\" samples to match the \"No\" samples\n",
    "hd_yes_up = resample(hd_yes, \n",
    "                        replace=True,                     # sample with replacement\n",
    "                        n_samples=hd_no.shape[0])    # to match number of \"No\"\n",
    "\n",
    "# Downsample the \"No\" samples to match the \"Up\" samples\n",
    "hd_no_down = resample(hd_no, \n",
    "                        replace=True,                     # sample with replacement\n",
    "                        n_samples=hd_yes.shape[0])    # to match number of \"Yes\"\n",
    " \n",
    "# Combine the two classes back after upsampling\n",
    "df_final_up = pd.concat([hd_no, hd_yes_up])\n",
    "\n",
    "# Combine the two classes back after downsampling\n",
    "df_final_down = pd.concat([hd_yes, hd_no_down])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70fea991",
   "metadata": {},
   "source": [
    "##### Downsampled dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "588a7ac0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 54746 entries, 5 to 194728\n",
      "Data columns (total 49 columns):\n",
      " #   Column                               Non-Null Count  Dtype  \n",
      "---  ------                               --------------  -----  \n",
      " 0   BMI                                  54746 non-null  float64\n",
      " 1   PHYSICALHEALTH                       54746 non-null  float64\n",
      " 2   MENTALHEALTH                         54746 non-null  float64\n",
      " 3   SLEEPTIME                            54746 non-null  float64\n",
      " 4   AGECATEGORY_18_24                    54746 non-null  float64\n",
      " 5   AGECATEGORY_25_29                    54746 non-null  float64\n",
      " 6   AGECATEGORY_30_34                    54746 non-null  float64\n",
      " 7   AGECATEGORY_35_39                    54746 non-null  float64\n",
      " 8   AGECATEGORY_40_44                    54746 non-null  float64\n",
      " 9   AGECATEGORY_45_49                    54746 non-null  float64\n",
      " 10  AGECATEGORY_50_54                    54746 non-null  float64\n",
      " 11  AGECATEGORY_55_59                    54746 non-null  float64\n",
      " 12  AGECATEGORY_60_64                    54746 non-null  float64\n",
      " 13  AGECATEGORY_65_69                    54746 non-null  float64\n",
      " 14  AGECATEGORY_70_74                    54746 non-null  float64\n",
      " 15  AGECATEGORY_75_79                    54746 non-null  float64\n",
      " 16  AGECATEGORY_80_OR_OLDER              54746 non-null  float64\n",
      " 17  RACE_AMERICAN_INDIAN/ALASKAN_NATIVE  54746 non-null  float64\n",
      " 18  RACE_ASIAN                           54746 non-null  float64\n",
      " 19  RACE_BLACK                           54746 non-null  float64\n",
      " 20  RACE_HISPANIC                        54746 non-null  float64\n",
      " 21  RACE_OTHER                           54746 non-null  float64\n",
      " 22  RACE_WHITE                           54746 non-null  float64\n",
      " 23  SEX_FEMALE                           54746 non-null  float64\n",
      " 24  SEX_MALE                             54746 non-null  float64\n",
      " 25  SMOKING_NO                           54746 non-null  float64\n",
      " 26  SMOKING_YES                          54746 non-null  float64\n",
      " 27  ALCOHOLDRINKING_NO                   54746 non-null  float64\n",
      " 28  ALCOHOLDRINKING_YES                  54746 non-null  float64\n",
      " 29  STROKE_NO                            54746 non-null  float64\n",
      " 30  STROKE_YES                           54746 non-null  float64\n",
      " 31  DIFFWALKING_NO                       54746 non-null  float64\n",
      " 32  DIFFWALKING_YES                      54746 non-null  float64\n",
      " 33  DIABETIC_NO                          54746 non-null  float64\n",
      " 34  DIABETIC_YES                         54746 non-null  float64\n",
      " 35  PHYSICALACTIVITY_NO                  54746 non-null  float64\n",
      " 36  PHYSICALACTIVITY_YES                 54746 non-null  float64\n",
      " 37  GENHEALTH_EXCELLENT                  54746 non-null  float64\n",
      " 38  GENHEALTH_FAIR                       54746 non-null  float64\n",
      " 39  GENHEALTH_GOOD                       54746 non-null  float64\n",
      " 40  GENHEALTH_POOR                       54746 non-null  float64\n",
      " 41  GENHEALTH_VERY_GOOD                  54746 non-null  float64\n",
      " 42  ASTHMA_NO                            54746 non-null  float64\n",
      " 43  ASTHMA_YES                           54746 non-null  float64\n",
      " 44  KIDNEYDISEASE_NO                     54746 non-null  float64\n",
      " 45  KIDNEYDISEASE_YES                    54746 non-null  float64\n",
      " 46  SKINCANCER_NO                        54746 non-null  float64\n",
      " 47  SKINCANCER_YES                       54746 non-null  float64\n",
      " 48  HEARTDISEASE                         54746 non-null  object \n",
      "dtypes: float64(48), object(1)\n",
      "memory usage: 20.9+ MB\n"
     ]
    }
   ],
   "source": [
    "# Final check on the downsampled dataframe to make sure everything is in place (OHE is still fine)\n",
    "df_final_down.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1b1da8be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Yes    27373\n",
       "No     27373\n",
       "Name: HEARTDISEASE, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x25006e219a0>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Check the ratio of the classes for the downsampled dataframe\n",
    "display(df_final_down['HEARTDISEASE'].value_counts())\n",
    "sb.catplot(y='HEARTDISEASE', data = df_final_down, kind = \"count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d3a36f9",
   "metadata": {},
   "source": [
    "##### Upsampled dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6bbd9c57",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 584844 entries, 0 to 257072\n",
      "Data columns (total 49 columns):\n",
      " #   Column                               Non-Null Count   Dtype  \n",
      "---  ------                               --------------   -----  \n",
      " 0   BMI                                  584844 non-null  float64\n",
      " 1   PHYSICALHEALTH                       584844 non-null  float64\n",
      " 2   MENTALHEALTH                         584844 non-null  float64\n",
      " 3   SLEEPTIME                            584844 non-null  float64\n",
      " 4   AGECATEGORY_18_24                    584844 non-null  float64\n",
      " 5   AGECATEGORY_25_29                    584844 non-null  float64\n",
      " 6   AGECATEGORY_30_34                    584844 non-null  float64\n",
      " 7   AGECATEGORY_35_39                    584844 non-null  float64\n",
      " 8   AGECATEGORY_40_44                    584844 non-null  float64\n",
      " 9   AGECATEGORY_45_49                    584844 non-null  float64\n",
      " 10  AGECATEGORY_50_54                    584844 non-null  float64\n",
      " 11  AGECATEGORY_55_59                    584844 non-null  float64\n",
      " 12  AGECATEGORY_60_64                    584844 non-null  float64\n",
      " 13  AGECATEGORY_65_69                    584844 non-null  float64\n",
      " 14  AGECATEGORY_70_74                    584844 non-null  float64\n",
      " 15  AGECATEGORY_75_79                    584844 non-null  float64\n",
      " 16  AGECATEGORY_80_OR_OLDER              584844 non-null  float64\n",
      " 17  RACE_AMERICAN_INDIAN/ALASKAN_NATIVE  584844 non-null  float64\n",
      " 18  RACE_ASIAN                           584844 non-null  float64\n",
      " 19  RACE_BLACK                           584844 non-null  float64\n",
      " 20  RACE_HISPANIC                        584844 non-null  float64\n",
      " 21  RACE_OTHER                           584844 non-null  float64\n",
      " 22  RACE_WHITE                           584844 non-null  float64\n",
      " 23  SEX_FEMALE                           584844 non-null  float64\n",
      " 24  SEX_MALE                             584844 non-null  float64\n",
      " 25  SMOKING_NO                           584844 non-null  float64\n",
      " 26  SMOKING_YES                          584844 non-null  float64\n",
      " 27  ALCOHOLDRINKING_NO                   584844 non-null  float64\n",
      " 28  ALCOHOLDRINKING_YES                  584844 non-null  float64\n",
      " 29  STROKE_NO                            584844 non-null  float64\n",
      " 30  STROKE_YES                           584844 non-null  float64\n",
      " 31  DIFFWALKING_NO                       584844 non-null  float64\n",
      " 32  DIFFWALKING_YES                      584844 non-null  float64\n",
      " 33  DIABETIC_NO                          584844 non-null  float64\n",
      " 34  DIABETIC_YES                         584844 non-null  float64\n",
      " 35  PHYSICALACTIVITY_NO                  584844 non-null  float64\n",
      " 36  PHYSICALACTIVITY_YES                 584844 non-null  float64\n",
      " 37  GENHEALTH_EXCELLENT                  584844 non-null  float64\n",
      " 38  GENHEALTH_FAIR                       584844 non-null  float64\n",
      " 39  GENHEALTH_GOOD                       584844 non-null  float64\n",
      " 40  GENHEALTH_POOR                       584844 non-null  float64\n",
      " 41  GENHEALTH_VERY_GOOD                  584844 non-null  float64\n",
      " 42  ASTHMA_NO                            584844 non-null  float64\n",
      " 43  ASTHMA_YES                           584844 non-null  float64\n",
      " 44  KIDNEYDISEASE_NO                     584844 non-null  float64\n",
      " 45  KIDNEYDISEASE_YES                    584844 non-null  float64\n",
      " 46  SKINCANCER_NO                        584844 non-null  float64\n",
      " 47  SKINCANCER_YES                       584844 non-null  float64\n",
      " 48  HEARTDISEASE                         584844 non-null  object \n",
      "dtypes: float64(48), object(1)\n",
      "memory usage: 223.1+ MB\n"
     ]
    }
   ],
   "source": [
    "# Final check on the upsampled dataframe to make sure everything is in place (OHE is still fine)\n",
    "df_final_up.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "3cdd1072",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Yes    292422\n",
       "No     292422\n",
       "Name: HEARTDISEASE, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x25006e62280>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Check the ratio of the classes for the upsampled dataframe\n",
    "display(df_final_up['HEARTDISEASE'].value_counts())\n",
    "sb.catplot(y='HEARTDISEASE', data = df_final_up, kind = \"count\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}