mlr_result_assigners_surrogate {mlr3mbo}

Result Assigner Based on a Surrogate Mean Prediction

Description

Result assigner that chooses the final point(s) based on a surrogate mean prediction of all evaluated points in the bbotk::Archive. This is especially useful in the case of noisy objective functions.

In the case of operating on an bbotk::OptimInstanceBatchMultiCrit the SurrogateLearnerCollection must use as many learners as there are objective functions.

Super class

mlr3mbo::ResultAssigner -> ResultAssignerSurrogate

Active bindings

surrogate

(Surrogate | NULL)
The surrogate.

packages

(character())
Set of required packages. A warning is signaled if at least one of the packages is not installed, but loaded (not attached) later on-demand via requireNamespace().

Methods

Public methods

• ResultAssignerSurrogate$new()

• ResultAssignerSurrogate$assign_result()

• ResultAssignerSurrogate$clone()

Inherited methods

• mlr3mbo::ResultAssigner$format()
• mlr3mbo::ResultAssigner$print()

Method new()

Creates a new instance of this R6 class.

Usage

ResultAssignerSurrogate$new(surrogate = NULL)

Arguments

surrogate

(Surrogate | NULL)
The surrogate that is used to predict the mean of all evaluated points.

Method assign_result()

Assigns the result, i.e., the final point(s) to the instance. If ⁠$surrogate⁠ is NULL, default_surrogate(instance) is used and also assigned to ⁠$surrogate⁠.

Usage

ResultAssignerSurrogate$assign_result(instance)

Arguments

instance

(bbotk::OptimInstanceBatchSingleCrit | bbotk::OptimInstanceBatchMultiCrit)
The bbotk::OptimInstance the final result should be assigned to.

Method clone()

The objects of this class are cloneable with this method.

Usage

ResultAssignerSurrogate$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

Other Result Assigner: ResultAssigner, mlr_result_assigners, mlr_result_assigners_archive

Examples

result_assigner = ras("surrogate")