Result Assigner Based on a Surrogate Mean Prediction
Source:R/ResultAssignerSurrogate.R
mlr_result_assigners_surrogate.RdResult 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 or bbotk::OptimInstanceAsyncMultiCrit the SurrogateLearnerCollection must use as many learners as there are objective functions.
See also
Other Result Assigner:
ResultAssigner,
mlr_result_assigners,
mlr_result_assigners_archive
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 viarequireNamespace().
Methods
Inherited methods
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.
Arguments
instance(bbotk::OptimInstanceBatchSingleCrit | bbotk::OptimInstanceBatchMultiCrit |bbotk::OptimInstanceAsyncSingleCrit | bbotk::OptimInstanceAsyncMultiCrit)
The bbotk::OptimInstance the final result should be assigned to.
Examples
result_assigner = ras("surrogate")