3 Commits

Include renames

Author	SHA1	Message	Date
3 people	1eaba0c221	fix(Evaluate): ignore empty data at evaluation time, add backtesting metrics (sharpe, etc), fixed crash when predicting 0.0 (#23) ... * fix(Evaluate): ignore empty data at evaluation time, so we don't inflate the model's performance * refactor(Pipeline): pass in data_loader arguments to the pipeline * feat(Evaluation): added sharpe, sortino, etc * fix: Took out the method to fill NaN numbers with 0s. This way in evaluation we can ignore NaN values. * fix: Fix of the fix added fillna back. Either we root out NaN lines in the very beginning or we stick with the method you created. Co-authored-by: Daniel Szemerey <szemy2@gmail.com>	2021-12-15 21:11:12 +01:00
Mark Aron SzulyovszkyandGitHub	6440ced32c	feat(Tests): added basic unit tests for walk_forward_train_test() (#22) ... * feat(Tests): added basic unit tests for walk_forward_train_test() * fix(Tests): inherit from BaseEstimator, fix index problems in walk_forward_train_test * fix(WalkForward): predictions were mistakenly removed, oops * fix(WalkForward): mistakenly re-assiging model	2021-12-15 17:54:03 +01:00
Mark Aron Szulyovszky	64721330a3	feat(Pipeline): save results, train on all assets	2021-12-14 22:59:44 +01:00