feat(experiment): 新增因子排除机制并优化模型训练参数

- 添加 EXCLUDED_FACTORS 列表支持批量排除效果不佳的因子
- 修复 LightGBM 树结构冲突，调整正则化和采样策略防过拟合
- 调整数据处理器配置，关闭模型自动保存

src/experiment/learn_to_rank.py

@@ -41,6 +41,7 @@ from src.training.config import TrainingConfig
 from src.experiment.common import (
     SELECTED_FACTORS,
     FACTOR_DEFINITIONS,
+    EXCLUDED_FACTORS,
     get_label_factor,
     register_factors,
     prepare_data,
@@ -260,7 +261,7 @@ engine = FactorEngine()
 # 2. 使用 metadata 定义因子
 print("\n[2] 定义因子（从 metadata 注册）")
 feature_cols = register_factors(
-    engine, SELECTED_FACTORS, FACTOR_DEFINITIONS, LABEL_FACTOR
+    engine, SELECTED_FACTORS, FACTOR_DEFINITIONS, LABEL_FACTOR, EXCLUDED_FACTORS
 )
 
 # 3. 准备数据