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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.
ResamplingHoldout$new() mlr_resamplings$get("holdout") rsmp("holdout")
See Resampling.
See Resampling.
ratio
:: numeric(1)
Ratio of observations to put into the training set.
Dictionary of Resamplings: mlr_resamplings
as.data.table(mlr_resamplings)
for a complete table of all (also dynamically created) Resampling implementations.
# NOT RUN {
# 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
# }
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