Splits data repeats (default: 10) times using a folds-fold (default: 10) cross-validation.

The iteration counter translates to repeats blocks of folds cross-validations, i.e., the first folds iterations belong to a single cross-validation.

Iteration numbers can be translated into folds or repeats with provided methods.

Dictionary

This Resampling can be instantiated via the dictionary mlr_resamplings or with the associated sugar function rsmp():

mlr_resamplings$get("holdout")
rsmp("holdout")

Parameters

References

Bischl B, Mersmann O, Trautmann H, Weihs C (2012). “Resampling Methods for Meta-Model Validation with Recommendations for Evolutionary Computation.” Evolutionary Computation, 20(2), 249--275. doi: 10.1162/evco_a_00069 .

See also

Super class

mlr3::Resampling -> ResamplingRepeatedCV

Active bindings

iters

(integer(1))
Returns the number of resampling iterations, depending on the values stored in the param_set.

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage

ResamplingRepeatedCV$new()


Method folds()

Translates iteration numbers to fold numbers.

Usage

ResamplingRepeatedCV$folds(iters)

Arguments

iters

(integer())
Iteration number.

Returns

integer() of fold numbers.


Method repeats()

Translates iteration numbers to repetition numbers.

Usage

ResamplingRepeatedCV$repeats(iters)

Arguments

iters

(integer())
Iteration number.

Returns

integer() of repetition numbers.


Method clone()

The objects of this class are cloneable with this method.

Usage

ResamplingRepeatedCV$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

# Create a task with 10 observations task = tsk("iris") task$filter(1:10) # Instantiate Resampling rrcv = rsmp("repeated_cv", repeats = 2, folds = 3) rrcv$instantiate(task) rrcv$iters
#> [1] 6
rrcv$folds(1:6)
#> [1] 1 2 1 2 1 2
rrcv$repeats(1:6)
#> [1] 1 1 1 2 2 2
# Individual sets: rrcv$train_set(1)
#> [1] 2 3 8 4 5 7
rrcv$test_set(1)
#> [1] 1 6 9 10
intersect(rrcv$train_set(1), rrcv$test_set(1))
#> integer(0)
# Internal storage: rrcv$instance # table
#> row_id rep fold #> 1: 1 1 1 #> 2: 2 1 2 #> 3: 3 1 2 #> 4: 4 1 3 #> 5: 5 1 3 #> 6: 6 1 1 #> 7: 7 1 3 #> 8: 8 1 2 #> 9: 9 1 1 #> 10: 10 1 1 #> 11: 1 2 1 #> 12: 2 2 3 #> 13: 3 2 1 #> 14: 4 2 3 #> 15: 5 2 1 #> 16: 6 2 2 #> 17: 7 2 3 #> 18: 8 2 1 #> 19: 9 2 2 #> 20: 10 2 2