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feat(Transformations): added Transformations abstraction & handling in walk_forward_train() & inference() (#161)

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* feat(Transformations): added Transformations abstraction & handling in walk_forward_train() & inference()

* fix(WalkForward): use Dataframes to call Transformation.fit_transform()

* feat(WalkForward): restored option for models to recieve unscaled data

* fix(Transformations): output DataFrame as expected

* fix(Tests): missing new property
This commit is contained in:
Mark Aron Szulyovszky
2022-01-12 23:22:55 +01:00
committed by GitHub
parent 3084f5e271
commit 1856fcad22
16 changed files with 144 additions and 85 deletions
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feature_selection/feature_selection.py
+1 -1
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@@ -25,7 +25,7 @@ def select_features(X: pd.DataFrame, y: pd.Series, model: Model, n_features_to_s
# 2. Recursive feature selection
cv = TimeSeriesSplit(n_splits=5)
scaler = get_scaler(scaling)
X_scaled = scaler.fit_transform(X)
X_scaled = scaler.fit_transform(X, y)
feat_selector_model = model.model
if hasattr(feat_selector_model, 'feature_importances_') == False and hasattr(feat_selector_model, 'coef_') == False: