2 Commits

Author	SHA1	Message	Date
Mark Aron Szulyovszky	b1c04afb13	refactor(Naming): use new convention, added Ensemble model parameter back, support multiple Meta-Labeling models (#132) ... * refactor(Naming): use `primary_models` & `meta_labeling_models` * refactor(Naming): using primary * meta_labeling across config and in pipeline * feat(Pipeline): added back Ensemble models * fix(Pipeline): compiler error * fix(Config): typo * chore(Pipeline): removed unused averaging step * revert the changes in discretizing * chore(Pipeline): remove sharpe improvement logging * fix(Pipeline): ensemble predictions should be a pd.Series instead of a DataFrame * fix(Pipeline): discard unnecessary ensemble_probabilities * fix(Pipeline): fixes regarding various meta-labeling ensemble bugs * fix(Reporting): use the new naming convention * fix(Reporting): use the right variable * feat(Sweep): new sweep for ensemble models * fix(Sweep): config reference * fix(Config): simplified dev config * fix(Models): use the faster LR model * fix(Models): use LGBM in the meta-labeling model for speed * fix(Selection): always use the first model for feature selection, commented out caching from select_features() as it's close to redundant in terms of speed	2022-01-09 17:21:06 +01:00
Daniel Szemerey	78a7fe028e	feat(Inference): Models are collected and structured. (#120) ... * feat: Added collection of models into a dictionary. * feat: Models are now saved in a structured way into a dictionary. * Rename run_model_test.py to run_model_dev.py * fix(Pipeline): missing variable statement Co-authored-by: Mark Aron Szulyovszky <mark.szulyovszky@gmail.com>	2022-01-07 15:33:50 +01:00