mlr_resamplings_ncv {mlr3inferr}R Documentation

Nested Cross-Validation

Description

This implements the Nested CV resampling procedure by Bates et al. (2024).

Parameters

Super class

mlr3::Resampling -> ResamplingNestedCV

Active bindings

iters

(integer(1))
The total number of resampling iterations.

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage
ResamplingNestedCV$new()

Method unflatten()

Convert a resampling iteration to a more useful representation. For outer resampling iterations, inner is NA.

Usage
ResamplingNestedCV$unflatten(iter)
Arguments
iter

(integer(1))
The iteration.

Returns

list(rep, outer, inner)


Method clone()

The objects of this class are cloneable with this method.

Usage
ResamplingNestedCV$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

References

Bates, Stephen, Hastie, Trevor, Tibshirani, Robert (2024). “Cross-validation: what does it estimate and how well does it do it?” Journal of the American Statistical Association, 119(546), 1434–1445.

Examples

ncv = rsmp("nested_cv", folds = 3, repeats = 10L)
ncv
rr = resample(tsk("mtcars"), lrn("regr.featureless"), ncv)

[Package mlr3inferr version 0.1.0 Index]