makeMlr3Surrogate {mlrintermbo} | R Documentation |
Create Surrogate Learner
Description
Creates the default mlrMBO surrogate learners as an mlr3::Learner
.
This imitates the behaviour of mlrCPO when no learner
argument is given to mbo()
/ initSMBO()
.
Usage
makeMlr3Surrogate(
is.numeric = TRUE,
is.noisy = TRUE,
has.dependencies = !is.numeric
)
Arguments
is.numeric |
(logical(1) )
Whether only numeric parameters are present. If so, a LearnerRegrKM (DiceKriging package)
is constructed. Otherwise a LearnerRegrRanger (random forest from the ranger package) is constructed.
Default is TRUE .
|
is.noisy |
(logical(1) )
Whether to use nugget estimation. Only considered when is.numeric is TRUE . Default is TRUE .
|
has.dependencies |
(logical(1) )
Whether to anticipate missing values in the surrogate model design. This adds out-of-range imputation to the model.
If more elaborate imputation is desired, it may be desirable to set this to FALSE and instead perform custom imputation
using mlr3pipelines.
Default is !numeric .
|
Examples
# DiceKriging Learner:
makeMlr3Surrogate()
# mlr3pipelines Graph: imputation %>>% 'ranger' (randomForest):
makeMlr3Surrogate(is.numeric = FALSE)
# just the 'ranger' Learner:
makeMlr3Surrogate(is.numeric = FALSE, has.dependencies = FALSE)
[Package
mlrintermbo version 0.5.1-1
Index]