* feat(FeatureExtraction): added fractionally differentiated returns to remove lagged returns
* fix(Sweep): config
* fix(Sweep): name
* fix(Sweep): grid
* feat(Config): separated sliding_window_size_level1 & sliding_window_size_level2
* feat(Dependencies): added ray, now using it to parallel process feature extraction
* fix(Dependencies): added pip explicitly
* fix(Dependencies): removed ray from root
* fix(Models): average model was probably not taking the right timestamp to average
* feat(Config): separated expanding_window_level1 & expanding_window_level2
* fix(Config): set n_features_to_select to the optimal 30
* feat(Selection): added prototype feature selection python script
* feat(Utils): added some helpers for the future from Advances in Financial ML book
* feat(Selection): added RFECV
* feat(Selection): added configurable feature selection step into pipeline
* feat(Config): added level_1 & level_2 default config, PCA before feature selection process starts
* feat(Selection): added backup feature selector models if current one can't output feature importance, removed unnecessary array for level-2 models
* fix(Training): deal with zero first value coming out of static models
* feat(Sweep): added feature selection sweep
* fix(Sweep): config problem
* fix(Sweep): config
* chore(Utils): removed unnecessary purged k-fold crossval class
* feat(Config): added dimensionality_reduction as a separate flag
* fix(Sweep): config updated
* fix(Sweep): sweep name
* chore(Config): updated level_2 config to the best performing configuation
* fix(Reporting): use weighted average (with no_of_samples as weights) and only report level-1 OR level-2 model performance
* chore(Config): updated sweep config
* fix(Reporting): missing import
* fix(Evaluation): get_first_valid_return_index can deal with zero valid indexes
* fix(Training): increase threshold for skipping assets
* fix(DataLoader): target asset should be always the first column
* feat: Added ensemble models to sweep and configured naming convention.
* fix: Default value was misconfigured.
* feat(Sweep): separated level-1 and level-2 sweep configs, skip assets with too few samples to train on, simplified model mapping
* fix(Sweep): syntax error
* chore(Sweep): set sweep names accordingly
* fix(Sweep): set sliding window
* fix(Sweep): adjusted sweep config
* fix(Sweep): removed invalid feature extractor preset
Co-authored-by: Mark Aron Szulyovszky <mark.szulyovszky@gmail.com>
Mark Aron Szulyovszky