impute before training the learner and reimpute
before predicting.makeImputeWrapper(learner, classes = list(), cols = list(),
dummy.cols = character(0L), dummy.type = "factor",
impute.new.levels = TRUE, recode.factor.levels = TRUE)Learner].imputations,
imputeConstant, imputeHist,
imputeLearner, imputeMax,
imputeMean, imputeMedian,
imputeMin, imputeMode,
imputeNormal, imputeUniform;
impute; makeImputeMethod;
reimputeOther wrapper: CostSensClassifModel,
CostSensClassifWrapper,
makeCostSensClassifWrapper;
CostSensRegrModel,
CostSensRegrWrapper,
makeCostSensRegrWrapper;
makeBaggingWrapper;
makeDownsampleWrapper;
makeFeatSelWrapper;
makeFilterWrapper;
makeMulticlassWrapper;
makeOverBaggingWrapper;
makeOversampleWrapper,
makeUndersampleWrapper;
makePreprocWrapper;
makeSMOTEWrapper;
makeTuneWrapper;
makeWeightedClassesWrapper