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0395715fa15670f2d6b9be9da425cd875c5809ef
* fix(Config): set remove_overlapping_events=True * fix(Config): only use level_1 features * feat(Config): added get_minimal_config
feat(Project): use SKLearn models directly, removed custom ensembling, use 5 minute data, batch inference, numba cusum filter (#192)
Financial time series prediction
And end-to-end pipeline to train predictive Machine Learning models on financial (non-stationary, regime changing) time series. Includes feature selection and meta labelling.
Description
Languages
Python
85%
Jupyter Notebook
15%