Convenience Constructor for Pool-Based Active Learning Optimizers
Source:R/optimizer_pool_al.R
optimizer_pool_al.RdCreates an OptimizerAL with appropriate components for a specific active learning method.
Usage
optimizer_pool_al(
method = c("gsx", "gsy", "igs", "qbc", "random", "ideal"),
learner = NULL,
delta = 1,
n_init = NULL,
init_method = NULL,
k_qbc = 5L,
batch_size = 1L,
n_candidates = NULL,
distance = NULL
)Arguments
- method
(
character(1))
One of"gsx","gsy","igs","qbc","random","ideal".- learner
(mlr3::LearnerRegr |
NULL)
Regression learner. Required for"gsy","igs","qbc","ideal".- delta
(
numeric(1))
Exploration weight for IDEAL (default 1).- n_init
(
integer(1)|NULL)
Number of initial samples.NULLuses OptimizerAL's default initialization policy.- init_method
(
character(1)|NULL)
Optional initialization override:"gsx","random", or"kmeans".NULLkeeps the method-specific default ("kmeans"for IDEAL,"gsx"for GSx/GSy/iGS,"random"for random/QBC).- k_qbc
(
integer(1))
Number of QBC committee members (default 5).- batch_size
(
integer(1))
Points per iteration (default 1).- n_candidates
(
NULL|integer(1))
Optional number of candidate points to subsample uniformly before scoring.NULLkeeps exhaustive pool scoring and does not enable continuous-space use.- distance
(
character(1)| ALDistance |NULL)
Distance used by every distance-based component (the GSx / iGS / IDEAL acquisition functions and the"gsx"/"kmeans"initializations).NULL(default) keeps the papers' method-specific scalings (standardization; per-dimension affine for IDEAL), which support numeric search spaces only. For mixed-type pools pass"gower"(a mlr_al_distances key) or an ALDistance object. A"kmeans"initialization combined with a non-geometry distance (such as Gower) uses the medoid-based SpaceSamplerKMedoids instead, its mixed-type analogue. Note that on mixed-type pools the surrogatelearnermust supportcharacterfeatures (e.g.lrn("regr.ranger")), since archives store paradox::ParamSet factor parameters as character columns.
Value
A configured OptimizerAL.