Fuse learner with simple downsampling (subsampling).

Creates a learner object, which can be used like any other learner object. It will only be trained on a subset of the original data to save computational time.

makeDownsampleWrapper(learner, dw.perc = 1, dw.stratify = FALSE)

Arguments

learner	(Learner | character(1)) The learner. If you pass a string the learner will be created via makeLearner.
dw.perc	(numeric(1)) See downsample. Default is 1.
dw.stratify	(logical(1)) See downsample. Default is FALSE.

Value

Learner.

See also

Other downsample: downsample()

Other wrapper: makeBaggingWrapper(), makeClassificationViaRegressionWrapper(), makeConstantClassWrapper(), makeCostSensClassifWrapper(), makeCostSensRegrWrapper(), makeDummyFeaturesWrapper(), makeExtractFDAFeatsWrapper(), makeFeatSelWrapper(), makeFilterWrapper(), makeImputeWrapper(), makeMulticlassWrapper(), makeMultilabelBinaryRelevanceWrapper(), makeMultilabelClassifierChainsWrapper(), makeMultilabelDBRWrapper(), makeMultilabelNestedStackingWrapper(), makeMultilabelStackingWrapper(), makeOverBaggingWrapper(), makePreprocWrapperCaret(), makePreprocWrapper(), makeRemoveConstantFeaturesWrapper(), makeSMOTEWrapper(), makeTuneWrapper(), makeUndersampleWrapper(), makeWeightedClassesWrapper()