Uses all observations as training and as test set.

Dictionary

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

mlr_resamplings$get("insample")
rsmp("insample")

See also

Super class

mlr3::Resampling -> ResamplingInsample

Public fields

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

ResamplingInsample$new()


Method clone()

The objects of this class are cloneable with this method.

Usage

ResamplingInsample$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

# Create a task with 10 observations task = tsk("iris") task$filter(1:10) # Instantiate Resampling rins = rsmp("insample") rins$instantiate(task) rins$train_set(1)
#> [1] 1 2 3 4 5 6 7 8 9 10
rins$test_set(1)
#> [1] 1 2 3 4 5 6 7 8 9 10
# Internal storage: rins$instance # just row ids
#> [1] 1 2 3 4 5 6 7 8 9 10