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

sigma

numeric(1)

start_values

character(1)
Create random start values or based on center of search space? In the latter case, it is the center of the parameters before a trafo is applied.

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.

Progress Bars

$optimize() supports progress bars via the package progressr combined with a Terminator. Simply wrap the function in progressr::with_progress() to enable them. We recommend to use package progress as backend; enable with progressr::handlers("progress").

See also

Super classes

mlr3tuning::Tuner -> mlr3tuning::TunerFromOptimizer -> TunerCmaes

Methods

Public methods

Inherited 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

deep

Whether 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$new( task = tsk("iris"), learner = lrn("classif.rpart"), resampling = rsmp("holdout"), measure = msr("classif.ce"), search_space = search_space, terminator = terminator ) tt = tnr("cmaes") # modifies the instance by reference tt$optimize(instance)
#> Error in B %*% diag(D^-1): non-conformable arguments
# returns best configuration and best performance instance$result
#> NULL
# allows access of data.table of full path of all evaluations instance$archive
#> <ArchiveTuning> #> cp classif.ce timestamp batch_nr #> 1: 0.050 0.08 2021-03-15 04:41:45 1 #> 2: 0.100 0.08 2021-03-15 04:41:45 2 #> 3: 0.100 0.08 2021-03-15 04:41:45 3 #> 4: 0.100 0.08 2021-03-15 04:41:45 4 #> 5: 0.001 0.08 2021-03-15 04:41:45 5 #> 6: 0.094 0.08 2021-03-15 04:41:45 6 #> 7: 0.100 0.08 2021-03-15 04:41:45 7 #> 8: 0.100 0.08 2021-03-15 04:41:45 8