Step3 插值算法 OOM 修复 + 多进程加速 + 全链路累积改动（14 文件）

src/core/steps/modeling_step.py

@@ -135,7 +135,7 @@ class ModelingStep:
         split_methods: Optional[List[str]] = None,
         cv_folds: int = 5,
         training_csv_path: Optional[str] = None,
-        output_dir: Union[str, Path] = "./7_Supervised_Model_Training",
+        output_dir: Union[str, Path] = "./8_Supervised_Model_Training",
         callback: Optional[Callable] = None,
         _report_generator=None,
     ) -> str:
@@ -251,7 +251,7 @@ class ModelingStep:
         if output_dir is not None:
             non_empirical_dir = Path(output_dir)
         else:
-            non_empirical_dir = Path.cwd() / "8_Regression_Modeling"
+            non_empirical_dir = Path.cwd() / "8_Non_Empirical_Regression"
         non_empirical_dir.mkdir(parents=True, exist_ok=True)
 
         if preprocessing_methods is None:
@@ -430,7 +430,7 @@ def _apply_preprocessing_internal(
 
     save_path = None
     if preprocess_method == "SS":
-        models_dir = output_dir.parent.parent / "7_Supervised_Model_Training"
+        models_dir = output_dir.parent.parent / "8_Supervised_Model_Training"
         models_dir.mkdir(parents=True, exist_ok=True)
         save_path = str(models_dir / "scaler_params.pkl")
         print(f"SS预处理: scaler模型将保存到 {save_path}")