Cyclic Boosting is a Python library implementing the family of machine learning algorithms of the same name, which is described in Cyclic Boosting - an explainable supervised machine learning algorithm and Demand Forecasting of Individual Probability Density Functions with Machine Learning. It contains efficient, off-the-shelf, general-purpose supervised machine learning methods for both regression and classification tasks.
Cyclic Boosting can be used for many different use-cases, here are just some examples
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