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
This commit is contained in:
Mark Aron Szulyovszky
2022-01-17 11:43:51 +01:00
committed by GitHub
parent 31dc847be1
commit 6b26643ece
27 changed files with 240 additions and 278 deletions
+3 -3
View File
@@ -21,10 +21,10 @@ def __preprocess_feature_extractors_config(data_dict: dict) -> dict:
return data_dict
def __preprocess_model_config(model_config:dict, method:str) -> dict:
model_map, _, _, _, _ = get_model_map(model_config)
model_config['primary_models'] = [(model_name, model_map[method + '_models'][model_name]) for model_name in model_config['primary_models']]
model_map = get_model_map(model_config)
model_config['primary_models'] = [(model_name, model_map['primary_models'][model_name]) for model_name in model_config['primary_models']]
if len(model_config['meta_labeling_models']) > 0:
model_config['meta_labeling_models'] = [(model_name, model_map[method + '_models'][model_name]) for model_name in model_config['meta_labeling_models']]
model_config['meta_labeling_models'] = [(model_name, model_map['primary_models'][model_name]) for model_name in model_config['meta_labeling_models']]
if model_config['ensemble_model'] is not None:
model_config['ensemble_model'] = (model_config['ensemble_model'], model_map['ensemble_models'][model_config['ensemble_model']])