{

 "cells": [

  {

   "cell_type": "code",

   "execution_count": 6,

   "metadata": {},

   "outputs": [],

   "source": [

    "from sklearn.model_selection import train_test_split\n",

    "import pandas as pd"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 7,

   "metadata": {},

   "outputs": [],

   "source": [

    "# Load processed datasets\n",

    "original = pd.read_csv(\"../../data/processed/original.csv\")\n",

    "synthetic = pd.read_csv(\"../../data/processed/synthetic.csv\")\n",

    "\n",

    "# mix both original and synthetic sets\n",

    "data = pd.concat([original, synthetic], keys=[1, 2]).drop_duplicates().dropna()"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 8,

   "metadata": {},

   "outputs": [],

   "source": [

    "# Select relevant feature\n",

    "feature = data[['GENDER', 'AGE', 'SMOKING', 'YELLOW_FINGERS', 'FATIGUE', 'WHEEZING', 'COUGHING', 'SHORTNESS OF BREATH', 'SWALLOWING DIFFICULTY', 'CHEST PAIN', 'CHRONIC DISEASE']]\n",

    "label = data['LUNG_CANCER']\n",

    "\n",

    "data = pd.concat([feature, label], axis=1).drop_duplicates().dropna()"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 9,

   "metadata": {},

   "outputs": [],

   "source": [

    "feature = data.drop('LUNG_CANCER', axis='columns')\n",

    "label = data['LUNG_CANCER']"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 10,

   "metadata": {},

   "outputs": [

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "Training set: (353, 11)\n",

      "Testing set: (89, 11)\n"

     ]

    }

   ],

   "source": [

    "# Split train/test holdout sets\n",

    "X_train, X_test, y_train, y_test = train_test_split(feature, label, test_size=0.2, random_state=42, stratify=label)\n",

    "\n",

    "print(f\"Training set: {X_train.shape}\")\n",

    "print(f\"Testing set: {X_test.shape}\")\n",

    "\n",

    "train_data = pd.concat([X_train, y_train], axis=1)\n",

    "test_data = pd.concat([X_test , y_test], axis=1)\n",

    "\n",

    "train_data.to_csv('../../data/input/train.csv', index=False)\n",

    "test_data.to_csv('../../data/input/test.csv', index=False)\n"

   ]

  }

 ],

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