4 Commits

Author	SHA1	Message	Date
Mark Aron Szulyovszky	5b7bcbb5e9	fix(DataLoader): sort the data before merging (this corrupted the pipeline completely)	2022-03-12 22:22:10 +01:00
Mark Aron Szulyovszky	b656f790f5	feat(Data): resample exogenous/other datasource when their frequency is different (#234) ... * feat(Data): resample exogenous/other datasource when their frequency is different * fix(Linter): ran * fix(Data): resampling done properly	2022-03-10 20:00:06 +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