5 Commits

Author	SHA1	Message	Date
Mark Aron Szulyovszky	4fc1070f45	fix(DataLoader): sort the dataframe when fetching data (#239)	2022-03-15 14:12:05 +01:00
Mark Aron Szulyovszky	75157c6285	feat(Labeling): purge overlapping events, sort dataframe at loading time (#226) ... * feat(Labeling): purge overlapping events, sort dataframe at loading time * fix(Linter): ran * refactor(Labeling): moved purge_overlapping_events one abstraction level higher * fix(Data): renamed class * fix(Data): corrected parameter name * fix(Config): parameters * fix(Data): fixed path * fix(Data): uncommented required code * feat(EventFilters): use vol based CUSUM * fix(Config): only retrain every 2000 samples * fix(Config): filter out even more events * fix(Inference): added remove_overlapping_events * refactor(Types): simplified type hierarchy	2022-03-02 00:26:33 +01:00
Mark Aron Szulyovszky	c9f8ed1304	feat(Data): added script to download data from binance (#224) ... * feat(Data): added script to download data from binance * feat(Data): saving unified parquet file/loading * fix(Config): tweak the cusum filter's threshold * fix(Dependencies): added binance_historical_data	2022-02-20 12:30:53 +01:00
Mark Aron Szulyovszky	8dd2d88740	chore(Linter): reformatted code with black (#211) ... * chore(Linter): reformatted code with black * Create black.yaml	2022-02-17 19:22:17 +01:00
Mark Aron Szulyovszky	9d47ee942d	feat(Project): use SKLearn models directly, removed custom ensembling, use 5 minute data, batch inference, numba cusum filter (#192) ... * feat(Project): use 5 minute data, running training in parallel, sped up cusum filter by 10x with numba * fix(WalkForward): inference mini-batch parallelization * fix(WalkForward): don't use the parallel version of any of the functions * feat(CI): download the data required * fix(Project): 5min_crypto folder added * fix(Evaluate): make sure we have numerical stability in returns * feat(Models): use SKLearn models directly to enable composability * feat(Inference): batched inference now working, added forecasting_horizon * fix(Inference): works again * fix(Inference) * chore(Models): remove unused Ensemble model * fix(Labeller): don't just forward shift returns, also take the sum of the data happened until then * Update test.yml	2022-02-17 16:36:35 +01:00