Creates a wrapper, which can be used like any other learner object. Models can easily be accessed via getLearnerModel.
For each class in the task, an individual regression model is fitted for the costs of that class. During prediction, the class with the lowest predicted costs is selected.
makeCostSensRegrWrapper(learner)Learner.
(Learner | character(1))
The regression learner.
If you pass a string the learner will be created via makeLearner.
Other costsens:
makeCostSensClassifWrapper(),
makeCostSensTask(),
makeCostSensWeightedPairsWrapper()
Other wrapper:
makeBaggingWrapper(),
makeClassificationViaRegressionWrapper(),
makeConstantClassWrapper(),
makeCostSensClassifWrapper(),
makeDownsampleWrapper(),
makeDummyFeaturesWrapper(),
makeExtractFDAFeatsWrapper(),
makeFeatSelWrapper(),
makeFilterWrapper(),
makeImputeWrapper(),
makeMulticlassWrapper(),
makeMultilabelBinaryRelevanceWrapper(),
makeMultilabelClassifierChainsWrapper(),
makeMultilabelDBRWrapper(),
makeMultilabelNestedStackingWrapper(),
makeMultilabelStackingWrapper(),
makeOverBaggingWrapper(),
makePreprocWrapperCaret(),
makePreprocWrapper(),
makeRemoveConstantFeaturesWrapper(),
makeSMOTEWrapper(),
makeTuneWrapper(),
makeUndersampleWrapper(),
makeWeightedClassesWrapper()