feat(Transformations): replaced feature selection pre-processing step with online version (with cache) (#170)

* feat(Transformations): removed feature-selection pre-processing step completely

* fix(Core): removed unnecessary `original_X`

* fix(Transformations): use the X_expanding_window to transform subsequent data

* fix(RFE): should check for model correctly

* fix(Config): only re-train the model every 40 timestamp

* fix(MetaLabeling): pass in the correct X to meta-labeling step

* fix(Transformation): PCA should at least keep as many features as sliding_window_size

* feat(Transformations): cache transformations across the same asset

* fix(Tests): missing preloaded_transformations arg

* chore(Config): got rid of unnecessary 'classification_models' and 'regression_models' dictionary keys

tests/test_evaluation.py

@@ -77,14 +77,15 @@ def test_evaluation():
         expanding_window=False,
         window_size=window_length,
         retrain_every=10,
-        transformations=[])
+        transformations=[],
+        preloaded_transformations=None)
     predictions, _ = walk_forward_inference(
         model_name='test',
         model_over_time=model_over_time,
         transformations_over_time=transformations_over_time,
         X=X,
         expanding_window=False,
-        window_size=window_length
+        window_size=window_length,
     )
     
     # verify if predictions are the same as y

tests/test_walk_forward.py

@@ -75,7 +75,9 @@ def test_walk_forward_train_test():
         expanding_window=False,
         window_size=window_length,
         retrain_every=10,
-        transformations=[])
+        transformations=[],
+        preloaded_transformations=None
+    )
     predictions, _ = walk_forward_inference(
         model_name='test',
         model_over_time=model_over_time,