mlr_resamplings_insample: Insample Resampling

mlr_resamplings_insampleR Documentation

Insample Resampling

Description

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")

Super class

mlr3::Resampling -> ResamplingInsample

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
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.

See Also

Other Resampling: Resampling, mlr_resamplings, mlr_resamplings_bootstrap, mlr_resamplings_custom, mlr_resamplings_custom_cv, mlr_resamplings_cv, mlr_resamplings_holdout, mlr_resamplings_loo, mlr_resamplings_repeated_cv, mlr_resamplings_subsampling

Examples

# Create a task with 10 observations
task = tsk("penguins")
task$filter(1:10)

# Instantiate Resampling
insample = rsmp("insample")
insample$instantiate(task)

# Train set equal to test set:
setequal(insample$train_set(1), insample$test_set(1))

# Internal storage:
insample$instance # just row ids

mlr3 documentation built on Oct. 18, 2024, 5:11 p.m.