mlrl.boosting.learners module

Author: Michael Rapp (michael.rapp.ml@gmail.com)

Provides scikit-learn implementations of boosting algorithms.

class mlrl.boosting.learners.BoomerClassifier(*args: Any, **kwargs: Any)

Bases: ProbabilisticClassificationRuleLearner

A scikit-learn implementation of “BOOMER”, an algorithm for learning gradient boosted multi-output rules, that can be used in classification problems.

class mlrl.boosting.learners.BoomerRegressor(*args: Any, **kwargs: Any)

Bases: RegressionRuleLearner

A scikit-learn implementation of “BOOMER”, an algorithm for learning gradient boosted multi-output rules, that can be used in regression problems.