mlr_measures_ci_ncv function

Nested CV CI

Confidence Intervals based on ResamplingNestedCV, including bias-correction. This inference method can only be applied to decomposable losses.

Parameters

Those from MeasureAbstractCi, as well as:

• bias :: logical(1)

  Whether to do bias correction. This is initialized to TRUE. If FALSE, the outer iterations are used for the point estimate and no bias correction is applied.

Examples

ci_ncv = msr("ci.ncv", "classif.acc")
ci_ncv

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.

Super classes

mlr3::Measure -> mlr3inferr::MeasureAbstractCi -> MeasureCiNestedCV

Methods

Public methods

• list("MeasureCiNestedCV$new()")

• list("MeasureCiNestedCV$clone()")

Method new()

Creates a new instance of this R6 class.

Usage

MeasureCiNestedCV$new(measure)

Arguments

• measure: (Measure or character(1))

   A measure of ID of a measure.
  

Method clone()

The objects of this class are cloneable with this method.

Usage

MeasureCiNestedCV$clone(deep = FALSE)

Arguments

• deep: Whether to make a deep clone.