makeExtractFDAFeatsWrapper: Fuse learner with an extractFDAFeatures method.

In riebetob/mlr: Machine Learning in R

Description

Fuses a base learner with an extractFDAFeatures method. Creates a learner object, which can be used like any other learner object. Internally uses extractFDAFeatures before training the learner and reextractFDAFeatures before predicting.

Usage

makeExtractFDAFeatsWrapper(learner, feat.methods = list())

Arguments

learner	[Learner | character(1)] The learner. If you pass a string the learner will be created via makeLearner.
feat.methods	[named list] List of functional features along with the desired methods for each functional feature. “all” applies the extratFDAFeatures method to each functional feature. Names of feat.methods must match column names of functional features. Available feature extraction methods are available under family fda_featextractor. Default is list() which does nothing.

Value

[Learner].

See Also

Other fda: extractFDAFeatures, makeExtractFDAFeatMethod

Other wrapper: makeBaggingWrapper, makeClassificationViaRegressionWrapper, makeConstantClassWrapper, makeCostSensClassifWrapper, makeCostSensRegrWrapper, makeDownsampleWrapper, makeDummyFeaturesWrapper, makeFeatSelWrapper, makeFilterWrapper, makeImputeWrapper, makeMulticlassWrapper, makeMultilabelBinaryRelevanceWrapper, makeMultilabelClassifierChainsWrapper, makeMultilabelDBRWrapper, makeMultilabelNestedStackingWrapper, makeMultilabelStackingWrapper, makeOverBaggingWrapper, makePreprocWrapperCaret, makePreprocWrapper, makeRemoveConstantFeaturesWrapper, makeSMOTEWrapper, makeTuneWrapper, makeUndersampleWrapper, makeWeightedClassesWrapper

riebetob/mlr documentation built on May 20, 2019, 5:58 p.m.