Splits data into a training set and a test set. Parameter ratio determines the ratio of observation going into the training set (default: 2/3).

Format

R6::R6Class inheriting from Resampling.

Construction

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

Fields

See Resampling.

Methods

See Resampling.

Parameters

  • ratio :: numeric(1)
    Ratio of observations to put into the training set.

See also

Dictionary of Resamplings: mlr_resamplings

as.data.table(mlr_resamplings) for a complete table of all (also dynamically created) Resampling implementations.

Examples

# Create a task with 10 observations task = tsk("iris") task$filter(1:10) # Instantiate Resampling rho = rsmp("holdout", ratio = 0.5) rho$instantiate(task) # Individual sets: rho$train_set(1)
#> [1] 4 9 6 7 2
rho$test_set(1)
#> [1] 1 3 5 8 10
intersect(rho$train_set(1), rho$test_set(1))
#> integer(0)
# Internal storage: rho$instance # simple list
#> $train #> [1] 4 9 6 7 2 #> #> $test #> [1] 1 3 5 8 10 #>