mlr3tuning (version 0.5.0)

mlr_tuners_gensa: TunerGenSA

Description

Subclass for generalized simulated annealing tuning calling GenSA::GenSA() from package GenSA.

Arguments

Dictionary

This Tuner can be instantiated via the dictionary mlr_tuners or with the associated sugar function tnr():

mlr_tuners$get("gensa")
tnr("gensa")

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

smooth

logical(1)

temperature

numeric(1)

acceptance.param

numeric(1)

verbose

logical(1)

trace.mat

logical(1)

For the meaning of the control parameters, see GenSA::GenSA(). 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.

Methods

Public methods

Method new()

Creates a new instance of this R6 class.

Usage

TunerGenSA$new()

Method clone()

The objects of this class are cloneable with this method.

Usage

TunerGenSA$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

Package mlr3hyperband for hyperband tuning.

Other Tuner: mlr_tuners_cmaes, mlr_tuners_design_points, mlr_tuners_grid_search, mlr_tuners_nloptr, mlr_tuners_random_search

Examples

Run this code
# NOT RUN {
library(mlr3)
library(paradox)
search_space = ParamSet$new(list(
  ParamDbl$new("cp", lower = 0.001, upper = 0.1)
))
terminator = trm("evals", n_evals = 3)
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("gensa")

# modifies the instance by reference
tt$optimize(instance)

# returns best configuration and best performance
instance$result

# allows access of data.table of full path of all evaluations
instance$archive
# }

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