mlr (version 1.1-18)

makeFilterWrapper: Fuse learner with filter method.

Description

Fuses a base learner with a filter method. Creates a learner object, which can be used like any other learner object. Internally Uses filterFeatures before every model fit.

Usage

makeFilterWrapper(learner,
    fw.method = "random.forest.importance", fw.perc = 1)

Value

[Learner].

Details

Look at package FSelector for details on the filter algorithms.

After training, the selected features can be retrieved with getTuneResult.

Examples

task = makeClassifTask(data=iris, target="Species")
lrn = makeLearner("classif.lda")
inner = makeResampleDesc("Holdout")
outer = makeResampleDesc("CV", iters = 2)
lrn = makeFilterWrapper(lrn, fw.perc=0.5)
mod = train(lrn, task)
print(getFilteredFeatures(mod))
r = resample(lrn, task, outer, extract = function(model) {
getFilteredFeatures(model)
})
print(r$extract)