feature(Config): added transformation parameters to Config, removed expanding_window (it's ON now)

transformations/retrieve.py

@@ -0,0 +1,42 @@
+from .rfe import RFETransformation
+from .pca import PCATransformation
+from .sklearn import SKLearnTransformation
+from typing import Literal, Optional
+from models.model_map import default_feature_selector_classification
+from sklearn.preprocessing import MinMaxScaler, Normalizer, StandardScaler
+
+ScalerTypes = Literal["normalize", "minmax", "standardize"]
+
+
+def get_rfe(n_feature_to_select: int) -> Optional[RFETransformation]:
+    if n_feature_to_select > 0:
+        return RFETransformation(
+            n_feature_to_select=n_feature_to_select,
+            model=default_feature_selector_classification,
+        )
+    else:
+        return None
+
+
+def get_pca(
+    ratio_components_to_keep: float, sliding_window_size: int
+) -> Optional[PCATransformation]:
+
+    if ratio_components_to_keep > 0:
+        return PCATransformation(
+            ratio_components_to_keep=ratio_components_to_keep,
+            sliding_window_size=sliding_window_size,
+        )
+    else:
+        return None
+
+
+def get_scaler(type: ScalerTypes) -> SKLearnTransformation:
+    if type == "normalize":
+        return SKLearnTransformation(Normalizer())
+    elif type == "minmax":
+        return SKLearnTransformation(MinMaxScaler(feature_range=(-1, 1)))
+    elif type == "standardize":
+        return SKLearnTransformation(StandardScaler())
+    else:
+        raise Exception("Scaler type not supported")