{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "0c41d51e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original distribution of the target data (T2DM):\n",
      "0.0    22618\n",
      "1.0     3680\n",
      "Name: T2DM, dtype: int64\n",
      "\n",
      "Distribution after RandomUnderSampling:\n",
      "0.0    3680\n",
      "1.0    3680\n",
      "Name: T2DM, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 4200x1800 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Optimal number of features: 18\n",
      "Selected features: ['Age', 'Hypertension', 'BMI', 'Central obesity', 'Sedentary time', 'Self-rated health', 'Daily sleep duration', 'Education', 'Dyslipidemia', 'Sleep quality', 'Drinking status', 'Annual income', 'PA', 'Residence', 'Smoking status', 'Chronic disease', 'Gender', 'Marital status']\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 3000x1800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from imblearn.under_sampling import RandomUnderSampler\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.feature_selection import RFE\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import roc_auc_score\n",
    "from sklearn.experimental import enable_iterative_imputer  # noqa\n",
    "from sklearn.impute import IterativeImputer\n",
    "\n",
    "# 提取的颜色\n",
    "left_color_hex = '#72b6a1'  # 绿色\n",
    "right_color_hex = '#e99675'  # 橙色\n",
    "\n",
    "# Set global font to Times New Roman and increase font sizes\n",
    "plt.rcParams['font.family'] = 'serif'\n",
    "plt.rcParams['font.serif'] = ['Times New Roman']\n",
    "plt.rcParams['font.size'] = 12\n",
    "plt.rcParams['axes.titlesize'] = 14\n",
    "plt.rcParams['axes.labelsize'] = 12\n",
    "plt.rcParams['xtick.labelsize'] = 10\n",
    "plt.rcParams['ytick.labelsize'] = 10\n",
    "plt.rcParams['legend.fontsize'] = 12\n",
    "\n",
    "# Load the dataset\n",
    "file_path = 'S4.Raw Data.xlsx'\n",
    "data = pd.read_excel(file_path)\n",
    "target = 'T2DM'\n",
    "\n",
    "# Handle NaN values using IterativeImputer\n",
    "imputer = IterativeImputer(random_state=42)\n",
    "data_imputed = pd.DataFrame(imputer.fit_transform(data), columns=data.columns)\n",
    "\n",
    "# Report original distribution of the target data\n",
    "print(\"Original distribution of the target data (T2DM):\")\n",
    "print(data_imputed[target].value_counts())\n",
    "\n",
    "# Plot original distribution of the target data\n",
    "plt.figure(figsize=(14, 6), dpi=300)  # Increase figure size and DPI for better clarity\n",
    "\n",
    "plt.subplot(1, 2, 1)\n",
    "sns.countplot(x=target, data=data_imputed, palette='Set2')\n",
    "plt.title('Original Distribution in Raw Dataset')\n",
    "plt.xlabel('T2DM')\n",
    "plt.ylabel('Counts')\n",
    "plt.grid(True, linestyle='--', alpha=0.6)\n",
    "\n",
    "# Annotate counts on the original distribution plot\n",
    "for p in plt.gca().patches:\n",
    "    plt.gca().annotate(f'{p.get_height()}', (p.get_x() + p.get_width() / 2, p.get_height()), \n",
    "                       ha='center', va='bottom', fontsize=10, color='black')\n",
    "\n",
    "# Exclude columns 'OGTT', 'FPG', 'T2DM_Report' from features\n",
    "exclude_columns = ['OGTT', 'FPG', 'T2DM_Report']\n",
    "X = data_imputed.drop(columns=[target] + exclude_columns)\n",
    "y = data_imputed[target]\n",
    "\n",
    "# Count the number of samples in each class\n",
    "class_counts = y.value_counts()\n",
    "minority_class_count = class_counts.min()\n",
    "\n",
    "# Define the sampling strategy to keep the minority class intact\n",
    "sampling_strategy = {class_counts.idxmin(): minority_class_count, class_counts.idxmax(): minority_class_count}\n",
    "\n",
    "rus = RandomUnderSampler(sampling_strategy=sampling_strategy, random_state=42)\n",
    "X_resampled, y_resampled = rus.fit_resample(X, y)\n",
    "\n",
    "# Report distribution after undersampling\n",
    "print(\"\\nDistribution after RandomUnderSampling:\")\n",
    "print(pd.Series(y_resampled).value_counts())\n",
    "\n",
    "# Create a DataFrame with the resampled data\n",
    "resampled_data = pd.DataFrame(X_resampled, columns=X.columns)\n",
    "resampled_data[target] = y_resampled\n",
    "\n",
    "# Plot the distribution of the target data after applying Random UnderSampler\n",
    "plt.subplot(1, 2, 2)\n",
    "sns.countplot(x=target, data=resampled_data, palette='Set2')\n",
    "plt.title('Distribution After RandomUnderSampling in Raw Dataset')\n",
    "plt.xlabel('T2DM')\n",
    "plt.ylabel('Counts')\n",
    "plt.grid(True, linestyle='--', alpha=0.6)\n",
    "\n",
    "# Annotate counts on the resampled distribution plot\n",
    "for p in plt.gca().patches:\n",
    "    plt.gca().annotate(f'{p.get_height()}', (p.get_x() + p.get_width() / 2, p.get_height()), \n",
    "                       ha='center', va='bottom', fontsize=10, color='black')\n",
    "\n",
    "# Add labels \"A\" and \"B\" to the plots\n",
    "plt.subplot(1, 2, 1)\n",
    "plt.text(-0.1, 1.05, 'A', transform=plt.gca().transAxes, fontsize=20, fontweight='bold')\n",
    "\n",
    "plt.subplot(1, 2, 2)\n",
    "plt.text(-0.1, 1.05, 'B', transform=plt.gca().transAxes, fontsize=20, fontweight='bold')\n",
    "\n",
    "# Show the plots\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# Split data into training and testing sets\n",
    "X_train, X_test, y_train, y_test = train_test_split(X_resampled, y_resampled, test_size=0.3, random_state=42)\n",
    "\n",
    "# Apply RF-RFE for feature selection\n",
    "rf = RandomForestClassifier(n_estimators=100, random_state=42)\n",
    "rfe = RFE(estimator=rf, n_features_to_select=1, step=1)\n",
    "rfe = rfe.fit(X_train, y_train)\n",
    "\n",
    "# Get feature rankings\n",
    "ranking = rfe.ranking_\n",
    "features = X.columns\n",
    "ranked_features = sorted(zip(ranking, features))\n",
    "\n",
    "# Determine the optimal number of features by maximizing AUC\n",
    "auc_scores = []\n",
    "for i in range(1, len(features) + 1):\n",
    "    selected_features = [f for rank, f in ranked_features[:i]]\n",
    "    rf.fit(X_train[selected_features], y_train)\n",
    "    y_pred = rf.predict_proba(X_test[selected_features])[:, 1]\n",
    "    auc = roc_auc_score(y_test, y_pred)\n",
    "    auc_scores.append(auc)\n",
    "\n",
    "optimal_num_features = auc_scores.index(max(auc_scores)) + 1\n",
    "selected_features = [f for rank, f in ranked_features[:optimal_num_features]]\n",
    "\n",
    "# Report the selected features\n",
    "print(\"\\nOptimal number of features:\", optimal_num_features)\n",
    "print(\"Selected features:\", selected_features)\n",
    "\n",
    "# Plot AUC scores vs. number of features\n",
    "plt.figure(figsize=(10, 6), dpi=300)\n",
    "plt.plot(range(1, len(features) + 1), auc_scores, marker='o', color=left_color_hex)\n",
    "plt.xlabel('Number of Features')\n",
    "plt.ylabel('AUC Score')\n",
    "plt.title('AUC Scores vs. Number of Features')\n",
    "plt.axvline(optimal_num_features, color='red', linestyle='--')\n",
    "plt.text(optimal_num_features - 3.2, max(auc_scores) + 0.01, f'Optimal Number: {optimal_num_features}', color='red', ha='left')\n",
    "plt.grid(True, linestyle='--', alpha=0.6)\n",
    "plt.xticks(range(1, len(features) + 1))  # Ensure x-axis has integer ticks\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "25c36014",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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