feat(training): 新增 TabM 模型支持及数据质量优化

- 添加 TabMModel、TabPFNModel 深度学习模型实现
- 新增 DataQualityAnalyzer 进行训练前数据质量诊断
- 改进数据处理器 NaN/null 双重处理，增强数据鲁棒性
- 支持 train_skip_days 参数跳过训练初期数据不足期
- Pipeline 自动清理标签为 NaN 的样本

src/experiment/regression.py

@@ -38,6 +38,7 @@ from src.experiment.common import (
     get_model_save_path,
     save_model_with_factors,
     TOP_N,
+    TRAIN_SKIP_DAYS,
 )
 
 # 训练类型标识
@@ -51,55 +52,55 @@ TRAINING_TYPE = "regression"
 
 # 排除的因子列表
 EXCLUDED_FACTORS = [
-    'GTJA_alpha036',
-    'GTJA_alpha032',
-    'GTJA_alpha010',
-    'GTJA_alpha005',
-    'CP',
-    'BP',
-    'debt_to_equity',
-    'current_ratio',
-    'GTJA_alpha002',
-    'GTJA_alpha027',
-    'GTJA_alpha064',
-    'GTJA_alpha062',
-    'GTJA_alpha043',
-    'GTJA_alpha044',
-    'GTJA_alpha120',
-    'GTJA_alpha117',
-    'GTJA_alpha103',
-    'GTJA_alpha104',
-    'GTJA_alpha105',
-    'GTJA_alpha073',
-    'GTJA_alpha077',
-    'GTJA_alpha085',
-    'GTJA_alpha090',
-    'GTJA_alpha087',
-    'GTJA_alpha083',
-    'GTJA_alpha092',
-    'GTJA_alpha133',
-    'GTJA_alpha131',
-    'GTJA_alpha126',
-    'GTJA_alpha124',
-    'GTJA_alpha162',
-    'GTJA_alpha164',
-    'GTJA_alpha157',
-    'GTJA_alpha177',
-    'price_to_avg_cost',
-    'cost_skewness',
-    'GTJA_alpha191',
-    'GTJA_alpha180',
-    'history_position',
-    'bottom_profit',
-    'mean_median_dev',
-    'smart_money_accumulation',
-'GTJA_alpha013',
-'GTJA_alpha099',
-'GTJA_alpha107',
-'GTJA_alpha119',
-'GTJA_alpha141',
-'GTJA_alpha130',
-'GTJA_alpha173',
+    "GTJA_alpha036",
+    "GTJA_alpha032",
+    "GTJA_alpha010",
+    "GTJA_alpha005",
+    "CP",
+    "BP",
+    "debt_to_equity",
+    "current_ratio",
+    "GTJA_alpha002",
+    "GTJA_alpha027",
+    "GTJA_alpha064",
+    "GTJA_alpha062",
+    "GTJA_alpha043",
+    "GTJA_alpha044",
+    "GTJA_alpha120",
+    "GTJA_alpha117",
+    "GTJA_alpha103",
+    "GTJA_alpha104",
+    "GTJA_alpha105",
+    "GTJA_alpha073",
+    "GTJA_alpha077",
+    "GTJA_alpha085",
+    "GTJA_alpha090",
+    "GTJA_alpha087",
+    "GTJA_alpha083",
+    "GTJA_alpha092",
+    "GTJA_alpha133",
+    "GTJA_alpha131",
+    "GTJA_alpha126",
+    "GTJA_alpha124",
+    "GTJA_alpha162",
+    "GTJA_alpha164",
+    "GTJA_alpha157",
+    "GTJA_alpha177",
+    "price_to_avg_cost",
+    "cost_skewness",
+    "GTJA_alpha191",
+    "GTJA_alpha180",
+    "history_position",
+    "bottom_profit",
+    "mean_median_dev",
+    "smart_money_accumulation",
+    "GTJA_alpha013",
+    "GTJA_alpha099",
+    "GTJA_alpha107",
+    "GTJA_alpha119",
+    "GTJA_alpha141",
+    "GTJA_alpha130",
+    "GTJA_alpha173",
 ]
 
 # 模型参数配置
@@ -184,6 +185,7 @@ def main():
         filters=[STFilter(data_router=engine.router)],
         stock_pool_filter_func=stock_pool_filter,
         stock_pool_required_columns=STOCK_FILTER_REQUIRED_COLUMNS,
+        train_skip_days=TRAIN_SKIP_DAYS,
     )
 
     # 4. 创建 RegressionTask