removeConstantFeatures.makeRemoveConstantFeaturesWrapper(learner, perc = 0,
dont.rm = character(0L), na.ignore = FALSE,
tol = .Machine$double.eps^0.5)Learner | character(1)]
The learner.
If you pass a string the learner will be created via makeLearner.numeric(1)]
The percentage of a feature values in [0, 1) that must differ from the mode value.
Default is 0, which means only constant features with exactly one observed level are removed.character]
Names of the columns which must not be deleted.
Default is no columns.logical(1)]
Should NAs be ignored in the percentage calculation?
(Or should they be treated as a single, extra level in the percentage calculation?)
Note that if the feature has only missing values, it is always removed.
Default is FALSE.numeric(1)]
Numerical tolerance to treat two numbers as equal.
Variables stored as double will get rounded accordingly before computing the mode.
Default is sqrt(.Maschine$double.eps).Learner].makeBaggingWrapper,
makeConstantClassWrapper,
makeCostSensClassifWrapper,
makeCostSensRegrWrapper,
makeDownsampleWrapper,
makeFeatSelWrapper,
makeFilterWrapper,
makeImputeWrapper,
makeMulticlassWrapper,
makeMultilabelBinaryRelevanceWrapper,
makeMultilabelClassifierChainsWrapper,
makeMultilabelDBRWrapper,
makeMultilabelNestedStackingWrapper,
makeMultilabelStackingWrapper,
makeOverBaggingWrapper,
makePreprocWrapperCaret,
makePreprocWrapper,
makeSMOTEWrapper,
makeTuneWrapper,
makeUndersampleWrapper,
makeWeightedClassesWrapper