R: Get the resampling indices from a tuning or feature selection...

getResamplingIndices {mlr} | R Documentation

## Get the resampling indices from a tuning or feature selection wrapper..

### Description

After you resampled a tuning or feature selection wrapper (see makeTuneWrapper) with `resample(..., extract = getTuneResult)` or `resample(..., extract = getFeatSelResult)` this helper returns a `list` with the resampling indices used for the respective method.

### Usage

    getResamplingIndices(object, inner = FALSE)

### Arguments

`object` | (ResampleResult) The result of resampling of a tuning or feature selection wrapper.
`inner` | (logical) If `TRUE`, returns the inner indices of a nested resampling setting.

### Value

(list). One list for each outer resampling fold.

### See Also

Other tune: `TuneControl`, `getNestedTuneResultsOptPathDf()`, `getNestedTuneResultsX()`, `getTuneResult()`, `makeModelMultiplexerParamSet()`, `makeModelMultiplexer()`, `makeTuneControlCMAES()`, `makeTuneControlDesign()`, `makeTuneControlGenSA()`, `makeTuneControlGrid()`, `makeTuneControlIrace()`, `makeTuneControlMBO()`, `makeTuneControlRandom()`, `makeTuneWrapper()`, `tuneParams()`, `tuneThreshold()`

### Examples

    task = makeClassifTask(data = iris, target = "Species")
    lrn = makeLearner("classif.rpart")
    # stupid mini grid
    ps = makeParamSet(
      makeDiscreteParam("cp", values = c(0.05, 0.1)),
      makeDiscreteParam("minsplit", values = c(10, 20))
    )
    ctrl = makeTuneControlGrid()
    inner = makeResampleDesc("Holdout")
    outer = makeResampleDesc("CV", iters = 2)
    lrn = makeTuneWrapper(lrn, resampling = inner, par.set = ps, control = ctrl)
    # nested resampling for evaluation
    # we also extract tuned hyper pars in each iteration and by that the resampling indices
    r = resample(lrn, task, outer, extract = getTuneResult)
    # get tuning indices
    getResamplingIndices(r, inner = TRUE)

[Package mlr version 2.19.0 Index]