makePreprocWrapperCaret: Fuse learner with preprocessing.

In riebetob/mlr: Machine Learning in R

Description

Fuses a learner with preprocessing methods provided by preProcess. Before training the preprocessing will be performed and the preprocessing model will be stored. Before prediction the preprocessing model will transform the test data according to the trained model.

After being wrapped the learner will support missing values although this will only be the case if ppc.knnImpute, ppc.bagImpute or ppc.medianImpute is set to TRUE.

Usage

makePreprocWrapperCaret(learner, ...)

Arguments

learner	[Learner | character(1)] The learner. If you pass a string the learner will be created via makeLearner.
...	[any] See preProcess for parameters not listed above. If you use them you might want to define them in the add.par.set so that they can be tuned.

Value

[Learner].

See Also

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

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