R: Fuse learner with simple downsampling (subsampling).

makeDownsampleWrapper {mlr} | R Documentation

## Fuse learner with simple downsampling (subsampling).

### 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()`

[Package mlr version 2.17.1 Index]