View source: R/OverUndersampleWrapper.R
makeUndersampleWrapper | R Documentation |
Creates a learner object, which can be used like any other learner object. Internally uses oversample or undersample before every model fit.
Note that observation weights do not influence the sampling and are simply passed down to the next learner.
makeUndersampleWrapper(learner, usw.rate = 1, usw.cl = NULL)
makeOversampleWrapper(learner, osw.rate = 1, osw.cl = NULL)
learner |
(Learner | |
usw.rate |
( |
usw.cl |
( |
osw.rate |
( |
osw.cl |
( |
Learner.
Other imbalancy:
makeOverBaggingWrapper()
,
oversample()
,
smote()
Other wrapper:
makeBaggingWrapper()
,
makeClassificationViaRegressionWrapper()
,
makeConstantClassWrapper()
,
makeCostSensClassifWrapper()
,
makeCostSensRegrWrapper()
,
makeDownsampleWrapper()
,
makeDummyFeaturesWrapper()
,
makeExtractFDAFeatsWrapper()
,
makeFeatSelWrapper()
,
makeFilterWrapper()
,
makeImputeWrapper()
,
makeMulticlassWrapper()
,
makeMultilabelBinaryRelevanceWrapper()
,
makeMultilabelClassifierChainsWrapper()
,
makeMultilabelDBRWrapper()
,
makeMultilabelNestedStackingWrapper()
,
makeMultilabelStackingWrapper()
,
makeOverBaggingWrapper()
,
makePreprocWrapper()
,
makePreprocWrapperCaret()
,
makeRemoveConstantFeaturesWrapper()
,
makeSMOTEWrapper()
,
makeTuneWrapper()
,
makeWeightedClassesWrapper()
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