makeDownsampleWrapper: Fuse learner with simple downsampling (subsampling).

In riebetob/mlr: Machine Learning in R

Description

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.

Usage

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

riebetob/mlr documentation built on May 20, 2019, 5:58 p.m.