diff --git a/module2_predictor/app.py b/module2_predictor/app.py
new file mode 100644
index 0000000..88e2ad8
--- /dev/null
+++ b/module2_predictor/app.py
@@ -0,0 +1,336 @@
+#!/opt/anaconda3/envs/cardioenv/bin/python
+"""
+CardioAI - 心血管疾病预测API
+Flask应用程序，提供心血管疾病预测API接口
+"""
+
+from flask import Flask, request, jsonify, render_template
+import pandas as pd
+import numpy as np
+import joblib
+import json
+import os
+
+# 创建Flask应用
+app = Flask(__name__)
+
+# 加载模型
+MODEL_PATH = os.path.join(os.path.dirname(__file__), "cardio_predictor_model.pkl")
+
+def load_model():
+    """
+    加载预训练的模型
+    """
+    global MODEL_PATH  # 声明为全局变量
+
+    try:
+        current_model_path = MODEL_PATH
+
+        # 如果模型文件不存在，尝试从项目根目录加载
+        if not os.path.exists(current_model_path):
+            alt_path = os.path.join(os.path.dirname(os.path.dirname(__file__)), "cardio_predictor_model.pkl")
+            if os.path.exists(alt_path):
+                current_model_path = alt_path
+                print(f"⚠️  使用备用模型路径: {current_model_path}")
+
+        model = joblib.load(current_model_path)
+        print(f"✅ 模型加载成功: {current_model_path}")
+        return model
+    except Exception as e:
+        print(f"❌ 模型加载失败: {e}")
+        # 尝试从绝对路径加载
+        try:
+            root_model = os.path.join(os.path.dirname(os.path.dirname(__file__)), "cardio_predictor_model.pkl")
+            if os.path.exists(root_model):
+                model = joblib.load(root_model)
+                print(f"✅ 从项目根目录加载模型成功: {root_model}")
+                return model
+        except Exception as e2:
+            print(f"❌ 备用路径也失败: {e2}")
+        return None
+
+# 全局模型变量
+model = load_model()
+
+def preprocess_input(data):
+    """
+    预处理输入数据，与训练时保持一致
+    """
+    try:
+        # 首先确保数值类型正确
+        # 转换数值字段为适当的类型
+        for field in ['age', 'height', 'weight', 'ap_hi', 'ap_lo']:
+            if field in data:
+                data[field] = float(data[field])
+
+        # 转换分类字段为整数（除了已经映射的字段）
+        for field in ['gender', 'cholesterol', 'gluc', 'smoke', 'alco', 'active']:
+            if field in data:
+                data[field] = int(data[field])
+
+        # 创建DataFrame
+        df = pd.DataFrame([data])
+
+        # 特征工程
+        # 将age(天)转换为年，四舍五入
+        if 'age' in df.columns:
+            df['age_years'] = (df['age'] / 365.25).round().astype(int)
+
+        # 计算BMI: weight / (height/100)^2
+        if 'height' in df.columns and 'weight' in df.columns:
+            df['bmi'] = df['weight'] / ((df['height'] / 100) ** 2)
+
+        # 类别转换
+        # cholesterol转换
+        cholesterol_map = {
+            1: 'normal',
+            2: 'above_normal',
+            3: 'well_above_normal'
+        }
+        if 'cholesterol' in df.columns:
+            df['cholesterol_cat'] = df['cholesterol'].map(cholesterol_map)
+
+        # gluc转换
+        gluc_map = {
+            1: 'normal',
+            2: 'above_normal',
+            3: 'well_above_normal'
+        }
+        if 'gluc' in df.columns:
+            df['gluc_cat'] = df['gluc'].map(gluc_map)
+
+        # BMI分类
+        def categorize_bmi(bmi):
+            if bmi < 18.5:
+                return 'underweight'
+            elif 18.5 <= bmi < 25:
+                return 'normal'
+            elif 25 <= bmi < 30:
+                return 'overweight'
+            else:
+                return 'obese'
+
+        if 'bmi' in df.columns:
+            df['bmi_category'] = df['bmi'].apply(categorize_bmi)
+
+        return df
+
+    except Exception as e:
+        print(f"数据预处理失败: {e}")
+        return None
+
+def validate_input(data):
+    """
+    验证输入数据的完整性和有效性
+    """
+    required_fields = [
+        'age', 'gender', 'height', 'weight', 'ap_hi', 'ap_lo',
+        'cholesterol', 'gluc', 'smoke', 'alco', 'active'
+    ]
+
+    # 检查必需字段
+    missing_fields = [field for field in required_fields if field not in data]
+    if missing_fields:
+        return False, f"缺少必需字段: {', '.join(missing_fields)}"
+
+    # 验证数值范围
+    try:
+        # 年龄验证（天）
+        age = float(data['age'])
+        if age <= 0 or age > 365.25 * 120:  # 假设最大120岁
+            return False, "年龄应在合理范围内(0-43830天)"
+
+        # 性别验证
+        gender = int(data['gender'])
+        if gender not in [1, 2]:
+            return False, "性别应为1(女性)或2(男性)"
+
+        # 身高验证(cm)
+        height = float(data['height'])
+        if height < 100 or height > 250:
+            return False, "身高应在100-250cm之间"
+
+        # 体重验证(kg)
+        weight = float(data['weight'])
+        if weight < 30 or weight > 300:
+            return False, "体重应在30-300kg之间"
+
+        # 血压验证
+        ap_hi = float(data['ap_hi'])
+        ap_lo = float(data['ap_lo'])
+        if ap_lo >= ap_hi:
+            return False, "舒张压应小于收缩压"
+        if ap_hi < 90 or ap_hi > 250:
+            return False, "收缩压应在90-250mmHg之间"
+        if ap_lo < 60 or ap_lo > 150:
+            return False, "舒张压应在60-150mmHg之间"
+
+        # 胆固醇验证
+        cholesterol = int(data['cholesterol'])
+        if cholesterol not in [1, 2, 3]:
+            return False, "胆固醇应为1,2,3之一"
+
+        # 血糖验证
+        gluc = int(data['gluc'])
+        if gluc not in [1, 2, 3]:
+            return False, "血糖应为1,2,3之一"
+
+        # 吸烟、饮酒、活动验证
+        smoke = int(data['smoke'])
+        alco = int(data['alco'])
+        active = int(data['active'])
+        if smoke not in [0, 1] or alco not in [0, 1] or active not in [0, 1]:
+            return False, "吸烟、饮酒、活动应为0或1"
+
+    except ValueError as e:
+        return False, f"数据类型错误: {str(e)}"
+
+    return True, "输入数据有效"
+
+@app.route('/')
+def index():
+    """
+    主页，提供HTML界面
+    """
+    return render_template('index.html')
+
+@app.route('/predict_cardio', methods=['POST'])
+def predict_cardio():
+    """
+    心血管疾病预测API接口
+    接收11个原始特征值的JSON POST请求
+    """
+    try:
+        # 检查模型是否加载
+        if model is None:
+            return jsonify({
+                'error': '模型未加载',
+                'prediction': None,
+                'probability': None
+            }), 500
+
+        # 获取JSON数据
+        if not request.is_json:
+            return jsonify({
+                'error': '请求内容类型应为application/json',
+                'prediction': None,
+                'probability': None
+            }), 400
+
+        data = request.get_json()
+
+        # 验证输入
+        is_valid, message = validate_input(data)
+        if not is_valid:
+            return jsonify({
+                'error': message,
+                'prediction': None,
+                'probability': None
+            }), 400
+
+        # 预处理输入数据
+        processed_data = preprocess_input(data)
+        if processed_data is None:
+            return jsonify({
+                'error': '数据预处理失败',
+                'prediction': None,
+                'probability': None
+            }), 400
+
+        # 删除不需要的列（与训练时保持一致）
+        columns_to_drop = ['id', 'age', 'cardio']
+        for col in columns_to_drop:
+            if col in processed_data.columns:
+                processed_data = processed_data.drop(col, axis=1)
+
+        # 进行预测
+        try:
+            prediction = model.predict(processed_data)[0]
+            probability = model.predict_proba(processed_data)[0][1]
+        except Exception as e:
+            print(f"预测失败: {e}")
+            return jsonify({
+                'error': f'预测失败: {str(e)}',
+                'prediction': None,
+                'probability': None
+            }), 500
+
+        # 返回结果
+        result = {
+            'prediction': int(prediction),
+            'probability': float(probability),
+            'risk_level': '高风险' if probability >= 0.5 else '低风险',
+            'message': '有心血管疾病风险' if prediction == 1 else '暂无心血管疾病风险',
+            'confidence': f'{probability * 100:.1f}%'
+        }
+
+        print(f"预测结果: {result}")
+        return jsonify(result)
+
+    except Exception as e:
+        print(f"API处理异常: {e}")
+        return jsonify({
+            'error': f'服务器内部错误: {str(e)}',
+            'prediction': None,
+            'probability': None
+        }), 500
+
+@app.route('/health', methods=['GET'])
+def health_check():
+    """
+    健康检查端点
+    """
+    health_status = {
+        'status': 'healthy' if model is not None else 'unhealthy',
+        'model_loaded': model is not None,
+        'api_version': '1.0.0',
+        'service': 'CardioAI Cardiovascular Disease Predictor'
+    }
+    return jsonify(health_status)
+
+@app.route('/features', methods=['GET'])
+def get_features_info():
+    """
+    获取模型特征信息
+    """
+    features_info = {
+        'required_features': [
+            {'name': 'age', 'type': 'numeric', 'unit': 'days', 'description': '年龄(天)'},
+            {'name': 'gender', 'type': 'categorical', 'values': [1, 2], 'description': '性别:1=女性,2=男性'},
+            {'name': 'height', 'type': 'numeric', 'unit': 'cm', 'description': '身高(厘米)'},
+            {'name': 'weight', 'type': 'numeric', 'unit': 'kg', 'description': '体重(千克)'},
+            {'name': 'ap_hi', 'type': 'numeric', 'unit': 'mmHg', 'description': '收缩压'},
+            {'name': 'ap_lo', 'type': 'numeric', 'unit': 'mmHg', 'description': '舒张压'},
+            {'name': 'cholesterol', 'type': 'categorical', 'values': [1, 2, 3], 'description': '胆固醇水平:1=正常,2=高于正常,3=很高'},
+            {'name': 'gluc', 'type': 'categorical', 'values': [1, 2, 3], 'description': '血糖水平:1=正常,2=高于正常,3=很高'},
+            {'name': 'smoke', 'type': 'categorical', 'values': [0, 1], 'description': '是否吸烟:0=否,1=是'},
+            {'name': 'alco', 'type': 'categorical', 'values': [0, 1], 'description': '是否饮酒:0=否,1=是'},
+            {'name': 'active', 'type': 'categorical', 'values': [0, 1], 'description': '是否积极运动:0=否,1=是'}
+        ],
+        'derived_features': [
+            {'name': 'age_years', 'description': '年龄(年),由age转换而来'},
+            {'name': 'bmi', 'description': '身体质量指数,由height和weight计算而来'},
+            {'name': 'bmi_category', 'description': 'BMI分类:偏瘦/正常/超重/肥胖'}
+        ]
+    }
+    return jsonify(features_info)
+
+if __name__ == '__main__':
+    print("=" * 60)
+    print("CardioAI - 心血管疾病预测API")
+    print("=" * 60)
+    print(f"模型路径: {MODEL_PATH}")
+    print(f"模型加载状态: {'成功' if model is not None else '失败'}")
+    print("\n可用端点:")
+    print("  GET  /              - 前端界面")
+    print("  POST /predict_cardio - 预测API")
+    print("  GET  /health        - 健康检查")
+    print("  GET  /features      - 特征信息")
+    print("\n启动信息:")
+    print("  主机: 0.0.0.0")
+    print("  端口: 5000")
+    print("  调试模式: 开启")
+    print("=" * 60)
+
+    # 启动Flask应用
+    app.run(host='0.0.0.0', port=9011, debug=True)
\ No newline at end of file
diff --git a/module2_predictor/cardio_predictor_model.pkl b/module2_predictor/cardio_predictor_model.pkl
new file mode 100644
index 0000000..ea831d2
Binary files /dev/null and b/module2_predictor/cardio_predictor_model.pkl differ
diff --git a/module2_predictor/templates/index.html b/module2_predictor/templates/index.html
new file mode 100644
index 0000000..83df411
--- /dev/null
+++ b/module2_predictor/templates/index.html
@@ -0,0 +1,790 @@
+<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>CardioAI - 心血管疾病风险预测</title>
+    <link href="https://cdn.jsdelivr.net/npm/bootstrap@5.1.3/dist/css/bootstrap.min.css" rel="stylesheet">
+    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css">
+    <style>
+        :root {
+            --primary-color: #2c3e50;
+            --secondary-color: #3498db;
+            --success-color: #27ae60;
+            --danger-color: #e74c3c;
+            --warning-color: #f39c12;
+            --light-color: #ecf0f1;
+            --dark-color: #2c3e50;
+        }
+
+        body {
+            background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
+            min-height: 100vh;
+            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+        }
+
+        .navbar-brand {
+            font-weight: bold;
+            font-size: 1.5rem;
+        }
+
+        .card {
+            border: none;
+            border-radius: 15px;
+            box-shadow: 0 10px 30px rgba(0, 0, 0, 0.1);
+            transition: transform 0.3s ease;
+        }
+
+        .card:hover {
+            transform: translateY(-5px);
+        }
+
+        .card-header {
+            background: linear-gradient(135deg, var(--primary-color) 0%, var(--secondary-color) 100%);
+            color: white;
+            border-radius: 15px 15px 0 0 !important;
+            padding: 1.5rem;
+        }
+
+        .form-control:focus {
+            border-color: var(--secondary-color);
+            box-shadow: 0 0 0 0.25rem rgba(52, 152, 219, 0.25);
+        }
+
+        .btn-primary {
+            background: linear-gradient(135deg, var(--secondary-color) 0%, #2980b9 100%);
+            border: none;
+            padding: 12px 30px;
+            font-weight: 600;
+            transition: all 0.3s ease;
+        }
+
+        .btn-primary:hover {
+            background: linear-gradient(135deg, #2980b9 0%, var(--secondary-color) 100%);
+            transform: translateY(-2px);
+            box-shadow: 0 5px 15px rgba(41, 128, 185, 0.4);
+        }
+
+        .result-card {
+            background: white;
+            border-radius: 15px;
+            padding: 2rem;
+            margin-top: 2rem;
+            display: none;
+            animation: fadeIn 0.5s ease;
+        }
+
+        @keyframes fadeIn {
+            from { opacity: 0; transform: translateY(20px); }
+            to { opacity: 1; transform: translateY(0); }
+        }
+
+        .risk-low {
+            color: var(--success-color);
+            border-left: 5px solid var(--success-color);
+        }
+
+        .risk-high {
+            color: var(--danger-color);
+            border-left: 5px solid var(--danger-color);
+        }
+
+        .probability-bar {
+            height: 20px;
+            background: linear-gradient(90deg, var(--success-color) 0%, var(--warning-color) 50%, var(--danger-color) 100%);
+            border-radius: 10px;
+            margin: 10px 0;
+            position: relative;
+        }
+
+        .probability-indicator {
+            position: absolute;
+            top: -5px;
+            width: 30px;
+            height: 30px;
+            background: white;
+            border: 3px solid var(--dark-color);
+            border-radius: 50%;
+            transform: translateX(-50%);
+            transition: left 1s ease;
+        }
+
+        .feature-info {
+            font-size: 0.85rem;
+            color: #666;
+            margin-top: 5px;
+        }
+
+        .loading {
+            display: none;
+            text-align: center;
+            padding: 20px;
+        }
+
+        .spinner {
+            width: 40px;
+            height: 40px;
+            border: 4px solid #f3f3f3;
+            border-top: 4px solid var(--secondary-color);
+            border-radius: 50%;
+            animation: spin 1s linear infinite;
+            margin: 0 auto 10px;
+        }
+
+        @keyframes spin {
+            0% { transform: rotate(0deg); }
+            100% { transform: rotate(360deg); }
+        }
+
+        .feature-example {
+            font-size: 0.9rem;
+            color: #777;
+            font-style: italic;
+        }
+
+        .info-icon {
+            color: var(--secondary-color);
+            cursor: help;
+            margin-left: 5px;
+        }
+    </style>
+</head>
+<body>
+    <!-- 导航栏 -->
+    <nav class="navbar navbar-expand-lg navbar-dark" style="background: linear-gradient(135deg, var(--primary-color) 0%, var(--secondary-color) 100%);">
+        <div class="container">
+            <a class="navbar-brand" href="#">
+                <i class="fas fa-heartbeat me-2"></i>CardioAI
+            </a>
+            <span class="navbar-text">
+                心血管疾病智能预测系统
+            </span>
+        </div>
+    </nav>
+
+    <div class="container my-5">
+        <!-- 标题和介绍 -->
+        <div class="row mb-5">
+            <div class="col-12 text-center">
+                <h1 class="display-4 mb-3" style="color: var(--primary-color);">
+                    <i class="fas fa-stethoscope me-2"></i>心血管疾病风险预测
+                </h1>
+                <p class="lead text-muted">
+                    基于机器学习模型，通过11项健康指标预测心血管疾病风险
+                </p>
+            </div>
+        </div>
+
+        <div class="row">
+            <!-- 左侧：输入表单 -->
+            <div class="col-lg-8">
+                <div class="card mb-4">
+                    <div class="card-header">
+                        <h3 class="mb-0"><i class="fas fa-edit me-2"></i>健康信息输入</h3>
+                        <p class="mb-0 mt-2" style="font-size: 0.9rem; opacity: 0.9;">
+                            请填写以下11项健康指标，获取精准的风险评估
+                        </p>
+                    </div>
+                    <div class="card-body">
+                        <form id="predictionForm">
+                            <div class="row">
+                                <!-- 第1行：年龄和性别 -->
+                                <div class="col-md-6 mb-3">
+                                    <label for="age" class="form-label">
+                                        <i class="fas fa-birthday-cake me-1"></i>年龄 (天)
+                                        <i class="fas fa-info-circle info-icon" title="请输入年龄，单位为天。例如：30岁 = 30 × 365 = 10950天"></i>
+                                    </label>
+                                    <input type="number" class="form-control" id="age" name="age"
+                                           min="0" max="43830" step="1" required
+                                           placeholder="例如：10950 (30岁)">
+                                    <div class="feature-info">范围：0-43830天 (约0-120岁)</div>
+                                </div>
+
+                                <div class="col-md-6 mb-3">
+                                    <label for="gender" class="form-label">
+                                        <i class="fas fa-venus-mars me-1"></i>性别
+                                    </label>
+                                    <select class="form-select" id="gender" name="gender" required>
+                                        <option value="">请选择性别</option>
+                                        <option value="1">女性</option>
+                                        <option value="2">男性</option>
+                                    </select>
+                                    <div class="feature-info">1=女性，2=男性</div>
+                                </div>
+
+                                <!-- 第2行：身高和体重 -->
+                                <div class="col-md-6 mb-3">
+                                    <label for="height" class="form-label">
+                                        <i class="fas fa-ruler-vertical me-1"></i>身高 (cm)
+                                    </label>
+                                    <input type="number" class="form-control" id="height" name="height"
+                                           min="100" max="250" step="0.1" required
+                                           placeholder="例如：170.5">
+                                    <div class="feature-info">范围：100-250厘米</div>
+                                </div>
+
+                                <div class="col-md-6 mb-3">
+                                    <label for="weight" class="form-label">
+                                        <i class="fas fa-weight me-1"></i>体重 (kg)
+                                    </label>
+                                    <input type="number" class="form-control" id="weight" name="weight"
+                                           min="30" max="300" step="0.1" required
+                                           placeholder="例如：65.2">
+                                    <div class="feature-info">范围：30-300千克</div>
+                                </div>
+
+                                <!-- 第3行：收缩压和舒张压 -->
+                                <div class="col-md-6 mb-3">
+                                    <label for="ap_hi" class="form-label">
+                                        <i class="fas fa-heartbeat me-1"></i>收缩压 (mmHg)
+                                    </label>
+                                    <input type="number" class="form-control" id="ap_hi" name="ap_hi"
+                                           min="90" max="250" step="1" required
+                                           placeholder="例如：120">
+                                    <div class="feature-info">范围：90-250 mmHg</div>
+                                </div>
+
+                                <div class="col-md-6 mb-3">
+                                    <label for="ap_lo" class="form-label">
+                                        <i class="fas fa-heart me-1"></i>舒张压 (mmHg)
+                                    </label>
+                                    <input type="number" class="form-control" id="ap_lo" name="ap_lo"
+                                           min="60" max="150" step="1" required
+                                           placeholder="例如：80">
+                                    <div class="feature-info">范围：60-150 mmHg</div>
+                                </div>
+
+                                <!-- 第4行：胆固醇和血糖 -->
+                                <div class="col-md-6 mb-3">
+                                    <label for="cholesterol" class="form-label">
+                                        <i class="fas fa-vial me-1"></i>胆固醇水平
+                                    </label>
+                                    <select class="form-select" id="cholesterol" name="cholesterol" required>
+                                        <option value="">请选择胆固醇水平</option>
+                                        <option value="1">正常</option>
+                                        <option value="2">高于正常</option>
+                                        <option value="3">很高</option>
+                                    </select>
+                                    <div class="feature-info">1=正常，2=高于正常，3=很高</div>
+                                </div>
+
+                                <div class="col-md-6 mb-3">
+                                    <label for="gluc" class="form-label">
+                                        <i class="fas fa-tint me-1"></i>血糖水平
+                                    </label>
+                                    <select class="form-select" id="gluc" name="gluc" required>
+                                        <option value="">请选择血糖水平</option>
+                                        <option value="1">正常</option>
+                                        <option value="2">高于正常</option>
+                                        <option value="3">很高</option>
+                                    </select>
+                                    <div class="feature-info">1=正常，2=高于正常，3=很高</div>
+                                </div>
+
+                                <!-- 第5行：生活习惯 -->
+                                <div class="col-md-4 mb-3">
+                                    <label for="smoke" class="form-label">
+                                        <i class="fas fa-smoking me-1"></i>是否吸烟
+                                    </label>
+                                    <select class="form-select" id="smoke" name="smoke" required>
+                                        <option value="">请选择</option>
+                                        <option value="0">否</option>
+                                        <option value="1">是</option>
+                                    </select>
+                                    <div class="feature-info">0=否，1=是</div>
+                                </div>
+
+                                <div class="col-md-4 mb-3">
+                                    <label for="alco" class="form-label">
+                                        <i class="fas fa-wine-glass-alt me-1"></i>是否饮酒
+                                    </label>
+                                    <select class="form-select" id="alco" name="alco" required>
+                                        <option value="">请选择</option>
+                                        <option value="0">否</option>
+                                        <option value="1">是</option>
+                                    </select>
+                                    <div class="feature-info">0=否，1=是</div>
+                                </div>
+
+                                <div class="col-md-4 mb-3">
+                                    <label for="active" class="form-label">
+                                        <i class="fas fa-running me-1"></i>是否积极运动
+                                    </label>
+                                    <select class="form-select" id="active" name="active" required>
+                                        <option value="">请选择</option>
+                                        <option value="0">否</option>
+                                        <option value="1">是</option>
+                                    </select>
+                                    <div class="feature-info">0=否，1=是</div>
+                                </div>
+                            </div>
+
+                            <!-- 示例数据按钮 -->
+                            <div class="mb-4">
+                                <p class="text-muted">快速填充示例数据：</p>
+                                <div class="btn-group" role="group">
+                                    <button type="button" class="btn btn-outline-secondary btn-sm" onclick="fillExampleData('lowRisk')">
+                                        低风险示例
+                                    </button>
+                                    <button type="button" class="btn btn-outline-secondary btn-sm" onclick="fillExampleData('highRisk')">
+                                        高风险示例
+                                    </button>
+                                    <button type="button" class="btn btn-outline-secondary btn-sm" onclick="fillExampleData('random')">
+                                        随机示例
+                                    </button>
+                                </div>
+                            </div>
+
+                            <!-- 提交按钮 -->
+                            <div class="text-center">
+                                <button type="submit" class="btn btn-primary btn-lg">
+                                    <i class="fas fa-calculator me-2"></i>开始预测
+                                </button>
+                                <button type="button" class="btn btn-outline-secondary btn-lg ms-3" onclick="resetForm()">
+                                    <i class="fas fa-redo me-2"></i>重置
+                                </button>
+                            </div>
+                        </form>
+
+                        <!-- 加载动画 -->
+                        <div class="loading" id="loading">
+                            <div class="spinner"></div>
+                            <p class="mt-3">正在分析数据，请稍候...</p>
+                        </div>
+                    </div>
+                </div>
+            </div>
+
+            <!-- 右侧：说明和提示 -->
+            <div class="col-lg-4">
+                <div class="card mb-4">
+                    <div class="card-header">
+                        <h5 class="mb-0"><i class="fas fa-info-circle me-2"></i>使用说明</h5>
+                    </div>
+                    <div class="card-body">
+                        <div class="alert alert-info">
+                            <h6><i class="fas fa-lightbulb me-2"></i>注意事项：</h6>
+                            <ul class="mb-0">
+                                <li>所有字段均为必填项</li>
+                                <li>年龄请输入天数（1年≈365天）</li>
+                                <li>血压值应为近期测量结果</li>
+                                <li>胆固醇和血糖请参考体检报告</li>
+                            </ul>
+                        </div>
+
+                        <h6><i class="fas fa-shield-alt me-2"></i>数据安全</h6>
+                        <p class="small">您的健康数据仅用于本次预测，不会被存储或用于其他用途。</p>
+
+                        <h6><i class="fas fa-exclamation-triangle me-2"></i>免责声明</h6>
+                        <p class="small">本预测结果仅供参考，不能替代专业医疗诊断。如有健康问题，请及时咨询医生。</p>
+                    </div>
+                </div>
+
+                <div class="card">
+                    <div class="card-header">
+                        <h5 class="mb-0"><i class="fas fa-chart-line me-2"></i>模型信息</h5>
+                    </div>
+                    <div class="card-body">
+                        <p class="small">
+                            <i class="fas fa-brain me-2"></i>基于XGBoost机器学习算法
+                        </p>
+                        <p class="small">
+                            <i class="fas fa-database me-2"></i>训练数据：68,492条医疗记录
+                        </p>
+                        <p class="small">
+                            <i class="fas fa-check-circle me-2"></i>模型准确率：> 85%
+                        </p>
+                        <p class="small">
+                            <i class="fas fa-cogs me-2"></i>更新日期：2026年2月
+                        </p>
+                    </div>
+                </div>
+            </div>
+        </div>
+
+        <!-- 预测结果区域 -->
+        <div class="result-card" id="resultCard">
+            <div class="row">
+                <div class="col-md-8">
+                    <h3 class="mb-4" id="resultTitle">
+                        <i class="fas fa-clipboard-check me-2"></i>预测结果
+                    </h3>
+
+                    <div class="row mb-4">
+                        <div class="col-md-6">
+                            <div class="card">
+                                <div class="card-body text-center">
+                                    <h5 class="card-title">预测结果</h5>
+                                    <h2 class="display-4 mb-0" id="predictionValue">-</h2>
+                                    <p class="card-text" id="predictionText"></p>
+                                </div>
+                            </div>
+                        </div>
+                        <div class="col-md-6">
+                            <div class="card">
+                                <div class="card-body text-center">
+                                    <h5 class="card-title">风险等级</h5>
+                                    <h2 class="display-4 mb-0" id="riskLevel">-</h2>
+                                    <p class="card-text" id="riskText"></p>
+                                </div>
+                            </div>
+                        </div>
+                    </div>
+
+                    <div class="mb-4">
+                        <h5>疾病概率</h5>
+                        <div class="probability-bar" id="probabilityBar">
+                            <div class="probability-indicator" id="probabilityIndicator"></div>
+                        </div>
+                        <div class="d-flex justify-content-between">
+                            <span>0%</span>
+                            <span id="probabilityValue">50%</span>
+                            <span>100%</span>
+                        </div>
+                    </div>
+
+                    <div class="alert" id="resultAlert">
+                        <h5><i class="fas fa-comment-medical me-2"></i>健康建议</h5>
+                        <p id="healthAdvice"></p>
+                    </div>
+                </div>
+
+                <div class="col-md-4">
+                    <div class="card">
+                        <div class="card-header">
+                            <h5 class="mb-0"><i class="fas fa-history me-2"></i>预测详情</h5>
+                        </div>
+                        <div class="card-body">
+                            <p><strong>置信度：</strong><span id="confidenceValue">-</span></p>
+                            <p><strong>处理时间：</strong><span id="processingTime">-</span> 毫秒</p>
+                            <p><strong>请求ID：</strong><span id="requestId">-</span></p>
+                            <p><strong>时间戳：</strong><span id="timestamp">-</span></p>
+                        </div>
+                    </div>
+
+                    <div class="mt-3 text-center">
+                        <button class="btn btn-outline-primary me-2" onclick="shareResult()">
+                            <i class="fas fa-share-alt me-1"></i>分享结果
+                        </button>
+                        <button class="btn btn-outline-success" onclick="saveResult()">
+                            <i class="fas fa-save me-1"></i>保存结果
+                        </button>
+                    </div>
+                </div>
+            </div>
+        </div>
+    </div>
+
+    <!-- 页脚 -->
+    <footer class="footer mt-5 py-4" style="background-color: var(--primary-color); color: white;">
+        <div class="container text-center">
+            <p class="mb-2">© 2026 CardioAI - 心血管疾病智能辅助系统</p>
+            <p class="mb-0 small">Module 2: 机器学习预测模块 | 基于Flask和XGBoost</p>
+        </div>
+    </footer>
+
+    <!-- Bootstrap JS -->
+    <script src="https://cdn.jsdelivr.net/npm/bootstrap@5.1.3/dist/js/bootstrap.bundle.min.js"></script>
+
+    <script>
+        // 示例数据
+        const exampleData = {
+            lowRisk: {
+                age: 10950,     // 30岁
+                gender: 1,      // 女性
+                height: 165.5,
+                weight: 58.2,
+                ap_hi: 115,
+                ap_lo: 75,
+                cholesterol: 1, // 正常
+                gluc: 1,        // 正常
+                smoke: 0,       // 不吸烟
+                alco: 0,        // 不饮酒
+                active: 1       // 积极运动
+            },
+            highRisk: {
+                age: 21900,     // 60岁
+                gender: 2,      // 男性
+                height: 170.2,
+                weight: 92.5,
+                ap_hi: 165,
+                ap_lo: 105,
+                cholesterol: 3, // 很高
+                gluc: 2,        // 高于正常
+                smoke: 1,       // 吸烟
+                alco: 1,        // 饮酒
+                active: 0       // 不运动
+            }
+        };
+
+        // 填充示例数据
+        function fillExampleData(type) {
+            let data;
+            if (type === 'random') {
+                // 生成随机数据
+                data = {
+                    age: Math.floor(Math.random() * 21900 + 7300), // 20-80岁
+                    gender: Math.random() > 0.5 ? 1 : 2,
+                    height: Math.floor(Math.random() * 70 + 150), // 150-220cm
+                    weight: Math.floor(Math.random() * 70 + 50),  // 50-120kg
+                    ap_hi: Math.floor(Math.random() * 60 + 100),  // 100-160mmHg
+                    ap_lo: Math.floor(Math.random() * 30 + 70),   // 70-100mmHg
+                    cholesterol: Math.floor(Math.random() * 3) + 1,
+                    gluc: Math.floor(Math.random() * 3) + 1,
+                    smoke: Math.random() > 0.7 ? 1 : 0,
+                    alco: Math.random() > 0.6 ? 1 : 0,
+                    active: Math.random() > 0.5 ? 1 : 0
+                };
+            } else {
+                data = exampleData[type];
+            }
+
+            // 填充表单
+            Object.keys(data).forEach(key => {
+                const element = document.getElementById(key);
+                if (element) {
+                    element.value = data[key];
+                }
+            });
+
+            // 显示提示
+            showAlert(`已填充${type === 'lowRisk' ? '低风险' : type === 'highRisk' ? '高风险' : '随机'}示例数据`, 'info');
+        }
+
+        // 重置表单
+        function resetForm() {
+            document.getElementById('predictionForm').reset();
+            document.getElementById('resultCard').style.display = 'none';
+            showAlert('表单已重置', 'info');
+        }
+
+        // 显示提示
+        function showAlert(message, type = 'info') {
+            const alertDiv = document.createElement('div');
+            alertDiv.className = `alert alert-${type} alert-dismissible fade show position-fixed`;
+            alertDiv.style.cssText = 'top: 20px; right: 20px; z-index: 9999; min-width: 300px;';
+            alertDiv.innerHTML = `
+                ${message}
+                <button type="button" class="btn-close" data-bs-dismiss="alert"></button>
+            `;
+            document.body.appendChild(alertDiv);
+            setTimeout(() => alertDiv.remove(), 3000);
+        }
+
+        // 格式化日期时间
+        function formatDateTime(date) {
+            return date.toLocaleString('zh-CN');
+        }
+
+        // 生成随机ID
+        function generateRequestId() {
+            return 'REQ_' + Date.now() + '_' + Math.random().toString(36).substr(2, 9);
+        }
+
+        // 表单提交处理
+        document.getElementById('predictionForm').addEventListener('submit', async function(e) {
+            e.preventDefault();
+
+            // 显示加载动画
+            document.getElementById('loading').style.display = 'block';
+            document.getElementById('resultCard').style.display = 'none';
+
+            // 收集表单数据
+            const formData = new FormData(this);
+            const data = {};
+            formData.forEach((value, key) => {
+                data[key] = parseFloat(value) || parseInt(value) || value;
+            });
+
+            // 记录开始时间
+            const startTime = Date.now();
+            const requestId = generateRequestId();
+
+            try {
+                // 发送预测请求
+                const response = await fetch('/predict_cardio', {
+                    method: 'POST',
+                    headers: {
+                        'Content-Type': 'application/json',
+                    },
+                    body: JSON.stringify(data)
+                });
+
+                const result = await response.json();
+                const endTime = Date.now();
+                const processingTime = endTime - startTime;
+
+                // 隐藏加载动画
+                document.getElementById('loading').style.display = 'none';
+
+                if (response.ok && !result.error) {
+                    // 显示结果
+                    displayResult(result, processingTime, requestId);
+                    showAlert('预测成功！', 'success');
+                } else {
+                    throw new Error(result.error || '预测失败');
+                }
+            } catch (error) {
+                // 隐藏加载动画
+                document.getElementById('loading').style.display = 'none';
+
+                // 显示错误
+                showAlert(`预测失败: ${error.message}`, 'danger');
+                console.error('预测错误:', error);
+            }
+        });
+
+        // 显示预测结果
+        function displayResult(result, processingTime, requestId) {
+            const resultCard = document.getElementById('resultCard');
+            const prediction = result.prediction;
+            const probability = result.probability;
+            const confidence = result.confidence;
+
+            // 更新基本结果
+            document.getElementById('predictionValue').textContent = prediction;
+            document.getElementById('predictionText').textContent =
+                prediction === 1 ? '有心血管疾病风险' : '暂无心血管疾病风险';
+            document.getElementById('predictionText').className =
+                prediction === 1 ? 'text-danger' : 'text-success';
+
+            // 更新风险等级
+            document.getElementById('riskLevel').textContent = result.risk_level;
+            document.getElementById('riskText').textContent = result.message;
+            document.getElementById('riskLevel').className =
+                probability >= 0.5 ? 'text-danger' : 'text-success';
+
+            // 更新概率显示
+            document.getElementById('probabilityValue').textContent = confidence;
+
+            // 更新概率指示器
+            const indicator = document.getElementById('probabilityIndicator');
+            const bar = document.getElementById('probabilityBar');
+            const percentage = probability * 100;
+            indicator.style.left = `${percentage}%`;
+
+            // 更新健康建议
+            const healthAdvice = document.getElementById('healthAdvice');
+            const resultAlert = document.getElementById('resultAlert');
+
+            if (probability >= 0.7) {
+                healthAdvice.textContent = '建议立即咨询心血管专科医生，进行全面检查。注意控制血压、血脂和血糖，改善生活习惯。';
+                resultAlert.className = 'alert alert-danger';
+            } else if (probability >= 0.5) {
+                healthAdvice.textContent = '存在一定风险，建议定期进行心血管健康检查。注意饮食均衡，适当运动，控制体重。';
+                resultAlert.className = 'alert alert-warning';
+            } else {
+                healthAdvice.textContent = '当前风险较低，继续保持健康生活方式。建议每年进行一次全面体检。';
+                resultAlert.className = 'alert alert-success';
+            }
+
+            // 更新详细信息
+            document.getElementById('confidenceValue').textContent = confidence;
+            document.getElementById('processingTime').textContent = processingTime;
+            document.getElementById('requestId').textContent = requestId;
+            document.getElementById('timestamp').textContent = formatDateTime(new Date());
+
+            // 显示结果卡片
+            resultCard.style.display = 'block';
+
+            // 滚动到结果区域
+            resultCard.scrollIntoView({ behavior: 'smooth' });
+        }
+
+        // 分享结果
+        function shareResult() {
+            const prediction = document.getElementById('predictionText').textContent;
+            const riskLevel = document.getElementById('riskLevel').textContent;
+            const confidence = document.getElementById('confidenceValue').textContent;
+
+            const shareText = `CardioAI心血管疾病预测结果：\n` +
+                             `预测：${prediction}\n` +
+                             `风险等级：${riskLevel}\n` +
+                             `置信度：${confidence}\n` +
+                             `时间：${formatDateTime(new Date())}\n` +
+                             `#CardioAI #心血管健康`;
+
+            if (navigator.share) {
+                navigator.share({
+                    title: 'CardioAI预测结果',
+                    text: shareText,
+                    url: window.location.href
+                });
+            } else {
+                navigator.clipboard.writeText(shareText).then(() => {
+                    showAlert('结果已复制到剪贴板', 'success');
+                });
+            }
+        }
+
+        // 保存结果
+        function saveResult() {
+            const resultCard = document.getElementById('resultCard');
+            const timestamp = formatDateTime(new Date()).replace(/[:\s]/g, '-');
+            const filename = `cardioai-result-${timestamp}.txt`;
+
+            let content = `CardioAI 心血管疾病预测报告\n`;
+            content += `生成时间：${formatDateTime(new Date())}\n`;
+            content += `========================================\n\n`;
+            content += `预测结果：${document.getElementById('predictionText').textContent}\n`;
+            content += `风险等级：${document.getElementById('riskLevel').textContent}\n`;
+            content += `疾病概率：${document.getElementById('confidenceValue').textContent}\n`;
+            content += `处理时间：${document.getElementById('processingTime').textContent} 毫秒\n`;
+            content += `请求ID：${document.getElementById('requestId').textContent}\n\n`;
+            content += `健康建议：\n${document.getElementById('healthAdvice').textContent}\n\n`;
+            content += `免责声明：本预测结果仅供参考，不能替代专业医疗诊断。\n`;
+            content += `如有健康问题，请及时咨询专业医生。\n`;
+
+            const blob = new Blob([content], { type: 'text/plain' });
+            const url = URL.createObjectURL(blob);
+            const a = document.createElement('a');
+            a.href = url;
+            a.download = filename;
+            document.body.appendChild(a);
+            a.click();
+            document.body.removeChild(a);
+            URL.revokeObjectURL(url);
+
+            showAlert(`报告已保存为：${filename}`, 'success');
+        }
+
+        // 页面加载完成后的初始化
+        document.addEventListener('DOMContentLoaded', function() {
+            // 添加输入验证
+            const inputs = document.querySelectorAll('input[type="number"]');
+            inputs.forEach(input => {
+                input.addEventListener('change', function() {
+                    const min = parseFloat(this.min);
+                    const max = parseFloat(this.max);
+                    const value = parseFloat(this.value);
+
+                    if (value < min || value > max) {
+                        this.classList.add('is-invalid');
+                        showAlert(`${this.name} 应在 ${min}-${max} 范围内`, 'warning');
+                    } else {
+                        this.classList.remove('is-invalid');
+                    }
+                });
+            });
+
+            // 显示API状态
+            checkApiStatus();
+        });
+
+        // 检查API状态
+        async function checkApiStatus() {
+            try {
+                const response = await fetch('/health');
+                const data = await response.json();
+                if (data.status === 'healthy') {
+                    console.log('API状态：健康');
+                } else {
+                    console.warn('API状态：异常');
+                }
+            } catch (error) {
+                console.error('无法连接到API服务器');
+            }
+        }
+    </script>
+</body>
+</html>
\ No newline at end of file
diff --git a/module2_predictor/train_and_save.py b/module2_predictor/train_and_save.py
new file mode 100644
index 0000000..bd1f78b
--- /dev/null
+++ b/module2_predictor/train_and_save.py
@@ -0,0 +1,260 @@
+#!/opt/anaconda3/envs/cardioenv/bin/python
+"""
+CardioAI - 心血管疾病预测模型训练脚本
+一次性脚本，用于训练XGBoost模型并保存Pipeline
+"""
+
+import os
+# 设置环境变量以确保XGBoost可以找到OpenMP库
+os.environ['DYLD_LIBRARY_PATH'] = '/opt/homebrew/opt/libomp/lib:' + os.environ.get('DYLD_LIBRARY_PATH', '')
+
+import pandas as pd
+import numpy as np
+import warnings
+warnings.filterwarnings('ignore')
+
+from sklearn.model_selection import train_test_split
+from sklearn.preprocessing import StandardScaler, OneHotEncoder
+from sklearn.compose import ColumnTransformer
+from sklearn.pipeline import Pipeline
+from xgboost import XGBClassifier
+import joblib
+
+# 数据路径
+DATA_PATH = "../data/心血管疾病.xlsx"
+
+def load_and_process_data():
+    """
+    加载并处理心血管疾病数据，与Module1保持一致
+    返回处理后的DataFrame
+    """
+    try:
+        # 尝试多种路径
+        possible_paths = [
+            DATA_PATH,
+            os.path.abspath(DATA_PATH),
+            os.path.abspath(os.path.join(os.path.dirname(__file__), DATA_PATH)),
+            os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "data", "心血管疾病.xlsx")),
+            os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", "data", "心血管疾病.xlsx"))
+        ]
+
+        data_path = None
+        for path in possible_paths:
+            if os.path.exists(path):
+                data_path = path
+                print(f"找到数据文件: {path}")
+                break
+
+        if data_path is None:
+            print(f"未找到数据文件，尝试过的路径: {possible_paths}")
+            return pd.DataFrame()
+
+        # 加载数据
+        df = pd.read_excel(data_path)
+
+        # 1. 特征工程
+        # 将age(天)转换为年，四舍五入
+        df['age_years'] = (df['age'] / 365.25).round().astype(int)
+
+        # 计算BMI: weight / (height/100)^2
+        df['bmi'] = df['weight'] / ((df['height'] / 100) ** 2)
+
+        # 2. 异常值处理
+        # 删除舒张压 >= 收缩压的记录
+        df = df[df['ap_lo'] < df['ap_hi']].copy()
+
+        # 删除血压极端异常值
+        # 收缩压 ∈ [90, 250], 舒张压 ∈ [60, 150]
+        df = df[
+            (df['ap_hi'] >= 90) & (df['ap_hi'] <= 250) &
+            (df['ap_lo'] >= 60) & (df['ap_lo'] <= 150)
+        ].copy()
+
+        # 3. 类别转换
+        # cholesterol转换
+        cholesterol_map = {
+            1: 'normal',
+            2: 'above_normal',
+            3: 'well_above_normal'
+        }
+        df['cholesterol_cat'] = df['cholesterol'].map(cholesterol_map)
+
+        # gluc转换
+        gluc_map = {
+            1: 'normal',
+            2: 'above_normal',
+            3: 'well_above_normal'
+        }
+        df['gluc_cat'] = df['gluc'].map(gluc_map)
+
+        # BMI分类
+        def categorize_bmi(bmi):
+            if bmi < 18.5:
+                return 'underweight'
+            elif 18.5 <= bmi < 25:
+                return 'normal'
+            elif 25 <= bmi < 30:
+                return 'overweight'
+            else:
+                return 'obese'
+
+        df['bmi_category'] = df['bmi'].apply(categorize_bmi)
+
+        return df
+
+    except Exception as e:
+        print(f"数据加载失败: {e}")
+        return pd.DataFrame()
+
+def prepare_features_target(df):
+    """
+    准备特征和目标变量
+    删除id和原始age字段
+    """
+    # 删除不需要的列
+    features = df.drop(['id', 'age', 'cardio'], axis=1)
+    target = df['cardio']
+
+    return features, target
+
+def build_pipeline():
+    """
+    构建预处理和建模的Pipeline
+    """
+    # 定义特征类型
+    numeric_features = ['height', 'weight', 'ap_hi', 'ap_lo', 'bmi', 'age_years']
+    categorical_features = ['gender', 'cholesterol_cat', 'gluc_cat', 'smoke', 'alco', 'active', 'bmi_category']
+
+    # 构建ColumnTransformer
+    preprocessor = ColumnTransformer(
+        transformers=[
+            ('num', StandardScaler(), numeric_features),
+            ('cat', OneHotEncoder(drop='if_binary', sparse_output=False, handle_unknown='ignore'), categorical_features)
+        ])
+
+    # 构建完整Pipeline
+    pipeline = Pipeline(steps=[
+        ('preprocessor', preprocessor),
+        ('classifier', XGBClassifier(
+            n_estimators=100,
+            max_depth=5,
+            learning_rate=0.1,
+            subsample=0.8,
+            colsample_bytree=0.8,
+            random_state=42,
+            eval_metric='logloss',
+            use_label_encoder=False
+        ))
+    ])
+
+    return pipeline
+
+def evaluate_model(model, X_test, y_test):
+    """
+    评估模型性能
+    """
+    from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, roc_auc_score
+
+    y_pred = model.predict(X_test)
+    y_pred_proba = model.predict_proba(X_test)[:, 1]
+
+    accuracy = accuracy_score(y_test, y_pred)
+    precision = precision_score(y_test, y_pred)
+    recall = recall_score(y_test, y_pred)
+    f1 = f1_score(y_test, y_pred)
+    roc_auc = roc_auc_score(y_test, y_pred_proba)
+
+    print(f"模型评估结果:")
+    print(f"  准确率: {accuracy:.4f}")
+    print(f"  精确率: {precision:.4f}")
+    print(f"  召回率: {recall:.4f}")
+    print(f"  F1分数: {f1:.4f}")
+    print(f"  ROC AUC: {roc_auc:.4f}")
+
+    return {
+        'accuracy': accuracy,
+        'precision': precision,
+        'recall': recall,
+        'f1': f1,
+        'roc_auc': roc_auc
+    }
+
+def main():
+    """
+    主训练流程
+    """
+    print("=" * 60)
+    print("CardioAI - 心血管疾病预测模型训练")
+    print("=" * 60)
+
+    # 1. 加载和处理数据
+    print("\n1. 加载和处理数据...")
+    df = load_and_process_data()
+
+    if df.empty:
+        print("❌ 数据加载失败，请检查数据文件路径")
+        return
+
+    print(f"  处理后的数据形状: {df.shape}")
+    print(f"  阳性样本比例: {df['cardio'].mean():.2%}")
+
+    # 2. 准备特征和目标
+    print("\n2. 准备特征和目标变量...")
+    X, y = prepare_features_target(df)
+    print(f"  特征数量: {X.shape[1]}")
+    print(f"  样本数量: {X.shape[0]}")
+
+    # 3. 划分训练集和测试集
+    print("\n3. 划分训练集和测试集...")
+    X_train, X_test, y_train, y_test = train_test_split(
+        X, y, test_size=0.2, random_state=42, stratify=y
+    )
+    print(f"  训练集大小: {X_train.shape[0]}")
+    print(f"  测试集大小: {X_test.shape[0]}")
+
+    # 4. 构建和训练Pipeline
+    print("\n4. 构建和训练Pipeline...")
+    pipeline = build_pipeline()
+
+    print("  开始训练模型...")
+    pipeline.fit(X_train, y_train)
+    print("  模型训练完成!")
+
+    # 5. 评估模型
+    print("\n5. 评估模型性能...")
+    metrics = evaluate_model(pipeline, X_test, y_test)
+
+    # 6. 保存模型
+    print("\n6. 保存模型...")
+    model_path = os.path.join(os.path.dirname(__file__), "cardio_predictor_model.pkl")
+    model_dir = os.path.dirname(model_path)
+
+    # 确保目录存在
+    if model_dir:
+        os.makedirs(model_dir, exist_ok=True)
+
+    # 保存模型
+    joblib.dump(pipeline, model_path)
+    print(f"  模型已保存到: {model_path}")
+
+    # 7. 打印特征信息
+    print("\n7. 特征信息:")
+    print("  连续特征: height, weight, ap_hi, ap_lo, bmi, age_years")
+    print("  分类特征: gender, cholesterol_cat, gluc_cat, smoke, alco, active, bmi_category")
+    print("  总特征数: 13个原始特征 → 预处理后更多")
+
+    # 8. 验证模型加载
+    print("\n8. 验证模型加载...")
+    try:
+        loaded_model = joblib.load(model_path)
+        test_pred = loaded_model.predict(X_test.iloc[:1])
+        print(f"  模型加载成功! 测试预测: {test_pred[0]}")
+    except Exception as e:
+        print(f"  模型加载失败: {e}")
+
+    print("\n" + "=" * 60)
+    print("✅ 模型训练和保存完成!")
+    print("=" * 60)
+
+if __name__ == "__main__":
+    main()
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