Subclass that implements CMA-ES calling adagio::pureCMAES()
from package adagio.
Dictionary
This Tuner can be instantiated via the dictionary
mlr_tuners or with the associated sugar function tnr():
mlr_tuners$get("cmaes") tnr("cmaes")
Logging
All Tuners use a logger (as implemented in lgr) from package
bbotk.
Use lgr::get_logger("bbotk") to access and control the logger.
Parameters
parsigma
For the meaning of the control parameters, see adagio::pureCMAES(). Note
that we have removed all control parameters which refer to the termination of
the algorithm and where our terminators allow to obtain the same behavior.
See also
Package mlr3hyperband for hyperband tuning.
Other Tuner:
mlr_tuners_design_points,
mlr_tuners_gensa,
mlr_tuners_grid_search,
mlr_tuners_nloptr,
mlr_tuners_random_search
Super classes
mlr3tuning::Tuner -> mlr3tuning::TunerFromOptimizer -> TunerCmaes
Methods
Public methods
Method new()
Creates a new instance of this R6 class.
Usage
TunerCmaes$new()
Method clone()
The objects of this class are cloneable with this method.
Usage
TunerCmaes$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
Examples
library(mlr3) library(paradox) library(data.table) search_space = ParamSet$new(list( ParamDbl$new("cp", lower = 0.001, upper = 0.1) )) terminator = trm("evals", n_evals = 10) instance = TuningInstanceSingleCrit$new( task = tsk("iris"), learner = lrn("classif.rpart"), resampling = rsmp("holdout"), measure = msr("classif.ce"), search_space = search_space, terminator = terminator ) tt = tnr("cmaes", par = 0.1) # modifies the instance by reference tt$optimize(instance)#> cp learner_param_vals x_domain classif.ce #> 1: 0.1 <list[2]> <list[1]> 0.1# returns best configuration and best performance instance$result#> cp learner_param_vals x_domain classif.ce #> 1: 0.1 <list[2]> <list[1]> 0.1# allows access of data.table of full path of all evaluations instance$archive#> <ArchiveTuning> #> cp classif.ce uhash x_domain #> 1: 0.10000000 0.1 a951bac6-b79d-425a-bf79-559c3c2e86c7 <list[1]> #> 2: 0.10000000 0.1 03090464-e946-4120-b3d3-597f2401bf27 <list[1]> #> 3: 0.10000000 0.1 cb675f29-f017-44a8-8afb-dcf57662cfed <list[1]> #> 4: 0.10000000 0.1 fd18ee5a-9786-4508-b719-32afb08a5b91 <list[1]> #> 5: 0.10000000 0.1 a292e098-bd79-41e4-b8e6-ad1fb730e752 <list[1]> #> 6: 0.09357766 0.1 cd729d0c-c246-43b3-8bc5-ec3633153fee <list[1]> #> 7: 0.08681602 0.1 9b514f37-967e-4c76-8d0c-314016a86735 <list[1]> #> 8: 0.10000000 0.1 357ddb0a-a312-4190-ab7d-b1c699aead48 <list[1]> #> 9: 0.08461986 0.1 e4a75c84-4460-4abe-a962-37c8a6d15ece <list[1]> #> 10: 0.10000000 0.1 a5469673-8642-4ced-926e-fa5c9dc3c0b0 <list[1]> #> timestamp batch_nr #> 1: 2020-12-10 04:36:37 1 #> 2: 2020-12-10 04:36:38 2 #> 3: 2020-12-10 04:36:38 3 #> 4: 2020-12-10 04:36:38 4 #> 5: 2020-12-10 04:36:38 5 #> 6: 2020-12-10 04:36:38 6 #> 7: 2020-12-10 04:36:38 7 #> 8: 2020-12-10 04:36:38 8 #> 9: 2020-12-10 04:36:38 9 #> 10: 2020-12-10 04:36:38 10