This function allows to construct a SurrogateLearner or SurrogateLearnerCollection in the spirit
of mlr_sugar
from mlr3.
If the archive
references more than one target variable or cols_y
contains more than one
target variable but only a single learner
is specified, this learner is replicated as many
times as needed to build the SurrogateLearnerCollection.
Arguments
- learner
(mlr3::LearnerRegr | List of mlr3::LearnerRegr)
mlr3::LearnerRegr that is to be used within the SurrogateLearner or a list of mlr3::LearnerRegr that are to be used within the SurrogateLearnerCollection.- archive
(
NULL
| bbotk::Archive)
bbotk::Archive of the bbotk::OptimInstance used. Can also beNULL
.- cols_x
(
NULL
|character()
)
Column ids in the bbotk::Archive that should be used as features. Can also beNULL
in which case this is automatically inferred based on the archive.- cols_y
(
NULL
|character()
)
Column id(s) in the bbotk::Archive that should be used as a target. If a list of mlr3::LearnerRegr is provided as thelearner
argument andcols_y
is specified as well, as many column names as learners must be provided. Can also beNULL
in which case this is automatically inferred based on the archive.- ...
(named
list()
)
Named arguments passed to the constructor, to be set as parameters in the paradox::ParamSet.
Examples
library(mlr3)
srlrn(lrn("regr.featureless"), catch_errors = FALSE)
#> <SurrogateLearner>: LearnerRegrFeatureless
#> * Parameters: assert_insample_perf=FALSE, catch_errors=FALSE
srlrn(list(lrn("regr.featureless"), lrn("regr.featureless")))
#> <SurrogateLearnerCollection>: (LearnerRegrFeatureless | LearnerRegrFeatureless)
#> * Parameters: assert_insample_perf=FALSE, catch_errors=TRUE