AdaBoostRegressor

AdaBoostRegressor

A model type for constructing a AdaBoost ensemble regression, based on MLJScikitLearnInterface.jl, and implementing the MLJ model interface.

From MLJ, the type can be imported using

AdaBoostRegressor = @load AdaBoostRegressor pkg=MLJScikitLearnInterface

Do model = AdaBoostRegressor() to construct an instance with default hyper-parameters. Provide keyword arguments to override hyper-parameter defaults, as in AdaBoostRegressor(estimator=...).

An AdaBoost regressor is a meta-estimator that begins by fitting a regressor on the original dataset and then fits additional copies of the regressor on the same dataset but where the weights of instances are adjusted according to the error of the current prediction. As such, subsequent regressors focus more on difficult cases.

This class implements the algorithm known as AdaBoost.R2.