adaboostAggregator: Aggregator for the Adaboost.M1 algorithm

In boostr: A modular framework to bag or boost any estimation procedure.

Description

Implements a (parallelized) version of the aggregator described in the Adaboost.M1 algorithm.

Usage

adaboostAggregator(estimators, alpha, ..., .parallelPredict = FALSE)

Arguments

estimators	a list of estimators which must produce output in the same response-space. This is usually the output of some reweighter function.
...	this does nothing – meant to swallow auxillary output from reweighter function.
.parallelPredict	a boolean indicating if prediction should be carried out in parallel.
alpha	a vector (or list) of length equal to the length of estimators. Each entry of alpha acts as a prediction weight for the corresponding estimator.

Value

a function whose sole argument is newdata and whose output is the aggregated predictions of the boosted ensemble, estimators.

For internal bookkeeping, this function is inherits from the 'aggregator' class.

See Also

Other adaboost: adaboostReweighter

Other aggregators: arcfsAggregator; arcx4Aggregator, vanillaAggregator, weightedAggregator; boost, boost.function, boost.list

boostr documentation built on May 2, 2019, 1:42 p.m.