2 Commits

Author	SHA1	Message	Date
Mark Aron Szulyovszky	c611481eb6	refactor(WalkForward): separate train / test functions to help with inference later (#158) ... * refactor(WalkForward): separate train / test functions (draft) to potentially help with inference later * fix(Training): use the new separate train / test functions * feat(Training): return and pass in scalers that are necessary for inference * fix(Project): runtime errors * fix(WalkForward): use the correct `train_from` value * fix(Tests): for new walk_forward functions() * refactor(WalkForward): rename `walk_forward_test()` to `walk_forward_inference()`	2022-01-12 14:42:16 +01:00
Mark Aron Szulyovszky	1cd0119589	feat(DataLoader): caching MVP, added ability to use standard scaling for exogenous data, scaling is now also done before feature selection (#105) ... * fix(FeatureExtractor): apply log to transform some series to normality * feat(DataLoader): add ability of not returning returns when they're not needed (exogenous data), applied log to certain features * feat(FeatureExtractors): added standard scaling for exogenous data * feat(FeatureSelection): scale data with the passed in scaler before doing feature-selection * fix(Config): sweep config * feat(Models): output probability, store it * feat(Core): added caching to select_features() and load_data() * fix(Dependencies): added diskcache * fix(Training): error when creating results DF * feat(Models): added xgboost, fixed tests * refactor(Cache): moved hashing to a separate function, created wrapper functions to separate business logic and caching * fix(Tests): new syntax * fix(Model): XGboost can't handle -1 class, so we'll use the deprecated label_encoder fornow * fix(Model): XGBoost config * feat(Cache): add run_clear_cache script * fix(Pipeline) accidentally re-instatiating all_predictions for each asset	2022-01-04 11:44:35 +01:00