ResamplingHoldout: Holdout Resampling
In mllg/mlr3: Machine Learning in R - Next Generation

Description Format Construction Fields Methods Parameters See Also Examples

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).

R6::R6Class inheriting from Resampling.

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

See Resampling.

stratify :: logical(1) | character()
Enables stratification. See Resampling.
ratio :: numeric(1)
Ratio of observations to put into the training set.

Dictionary of Resamplings: mlr_resamplings

# 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$train_set(1)
rho$test_set(1)
intersect(rho$train_set(1), rho$test_set(1))

# Internal storage:
rho$instance # simple list