arcfsAggregator: Aggregator for the arc-fs algorithm.

Description Usage Arguments Details Value Note See Also

View source: R/arcfsAggregator.R


A (parallelized) implementation of the aggregator described in the arc-fs algorithm.


arcfsAggregator(estimators, beta, ..., .parallelPredict = FALSE,
  .parallelTally = FALSE, .rngSeed = 1234)



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.


a boolean indicating if prediction should be carried out in parallel.


a vector of scalar weights associated to each estimator in estimators


a boolean indicating if vote tallying should be performed in parallel. Unless you have more than 1,000 votes / observation, you probably won't see much performance gain by parallelizing this step.


the RNG seed sent to predictClassFromWeightedVote in the case of a tie.


By default, this function will perform its predictions in sequence across the estimators in estimators. To predict in parallel, change .parallelPredict to TRUE.


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.


In accord with the arc-fs algorithm, there is the assumption that the estimators in estimators are classifiers. More aptly, their output is either of factor or character-type.

See Also

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

Other arc-fs: arcfsReweighter

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