tune_nested {mlr3tuning} | R Documentation |
Function for Nested Resampling
Description
Function to conduct nested resampling.
Usage
tune_nested(
tuner,
task,
learner,
inner_resampling,
outer_resampling,
measure = NULL,
term_evals = NULL,
term_time = NULL,
terminator = NULL,
search_space = NULL,
store_tuning_instance = TRUE,
store_benchmark_result = TRUE,
store_models = FALSE,
check_values = FALSE,
callbacks = NULL
)
Arguments
tuner |
(Tuner) |
task |
(mlr3::Task) |
learner |
(mlr3::Learner) |
inner_resampling |
(mlr3::Resampling) |
outer_resampling |
mlr3::Resampling) |
measure |
(mlr3::Measure) |
term_evals |
( |
term_time |
( |
terminator |
(bbotk::Terminator) |
search_space |
(paradox::ParamSet) |
store_tuning_instance |
( |
store_benchmark_result |
( |
store_models |
( |
check_values |
( |
callbacks |
(list of mlr3misc::Callback) |
Value
Examples
# Nested resampling on Palmer Penguins data set
rr = tune_nested(
tuner = tnr("random_search", batch_size = 2),
task = tsk("penguins"),
learner = lrn("classif.rpart", cp = to_tune(1e-04, 1e-1, logscale = TRUE)),
inner_resampling = rsmp ("holdout"),
outer_resampling = rsmp("cv", folds = 2),
measure = msr("classif.ce"),
term_evals = 2)
# Performance scores estimated on the outer resampling
rr$score()
# Unbiased performance of the final model trained on the full data set
rr$aggregate()