This package contains the implementation of the Machine Learning algorithm Cyclic Boosting, which is described in Cyclic Boosting - an explainable supervised machine learning algorithm and Demand Forecasting of Individual Probability Density Functions with Machine Learning.
The documentation of this package can be found here.
It can be used in a scikit-learn-like fashion. You need to combine a binner (e.g., BinNumberTransformer) with an estimator (find all estimators in the init). A usage example can be found in the integration tests. A more detailed example, including additional helper functionality, can be found here.