mlr_acqfunctions_sd {mlr3mbo}R Documentation

Acquisition Function Standard Deviation

Description

Posterior Standard Deviation.

Dictionary

This AcqFunction can be instantiated via the dictionary mlr_acqfunctions or with the associated sugar function acqf():

mlr_acqfunctions$get("sd")
acqf("sd")

Super classes

bbotk::Objective -> mlr3mbo::AcqFunction -> AcqFunctionSD

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage
AcqFunctionSD$new(surrogate = NULL)
Arguments
surrogate

(NULL | SurrogateLearner).


Method clone()

The objects of this class are cloneable with this method.

Usage
AcqFunctionSD$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

See Also

Other Acquisition Function: AcqFunction, mlr_acqfunctions, mlr_acqfunctions_aei, mlr_acqfunctions_cb, mlr_acqfunctions_ehvi, mlr_acqfunctions_ehvigh, mlr_acqfunctions_ei, mlr_acqfunctions_eips, mlr_acqfunctions_mean, mlr_acqfunctions_pi, mlr_acqfunctions_smsego

Examples

if (requireNamespace("mlr3learners") &
    requireNamespace("DiceKriging") &
    requireNamespace("rgenoud")) {
  library(bbotk)
  library(paradox)
  library(mlr3learners)
  library(data.table)

  fun = function(xs) {
    list(y = xs$x ^ 2)
  }
  domain = ps(x = p_dbl(lower = -10, upper = 10))
  codomain = ps(y = p_dbl(tags = "minimize"))
  objective = ObjectiveRFun$new(fun = fun, domain = domain, codomain = codomain)

  instance = OptimInstanceBatchSingleCrit$new(
    objective = objective,
    terminator = trm("evals", n_evals = 5))

  instance$eval_batch(data.table(x = c(-6, -5, 3, 9)))

  learner = default_gp()

  surrogate = srlrn(learner, archive = instance$archive)

  acq_function = acqf("sd", surrogate = surrogate)

  acq_function$surrogate$update()
  acq_function$update()
  acq_function$eval_dt(data.table(x = c(-1, 0, 1)))
}

[Package mlr3mbo version 0.2.4 Index]