makePreprocWrapper(learner, train, predict, par.set = makeParamSet(), par.vals = list())Learner | character(1)]
The learner.
If you pass a string the learner will be created via makeLearner.function(data, target, args)]
Function to preprocess the data before training.
target is a string and denotes the target variable in data.
args is a list of further arguments and parameters to influence the
preprocessing.
Must return a list(data, control), where data is the preprocessed
data and control stores all information necessary to do the preprocessing
before predictions.function(data, target, args, control)]
Function to preprocess the data before prediction.
target is a string and denotes the target variable in data.
args are the args that were passed to train.
control is the object you returned in train.
Must return the processed data.ParamSet]
Parameter set of LearnerParam objects to describe the
parameters in args.
Default is empty set.list]
Named list of default values for params in args respectively par.set.
Default is empty list.Learner].
makeBaggingWrapper,
makeConstantClassWrapper,
makeCostSensClassifWrapper,
makeCostSensRegrWrapper,
makeDownsampleWrapper,
makeFeatSelWrapper,
makeFilterWrapper,
makeImputeWrapper,
makeMulticlassWrapper,
makeMultilabelBinaryRelevanceWrapper,
makeMultilabelClassifierChainsWrapper,
makeMultilabelDBRWrapper,
makeMultilabelNestedStackingWrapper,
makeMultilabelStackingWrapper,
makeOverBaggingWrapper,
makePreprocWrapperCaret,
makeRemoveConstantFeaturesWrapper,
makeSMOTEWrapper,
makeTuneWrapper,
makeUndersampleWrapper,
makeWeightedClassesWrapper