| mlr_result_assigners_surrogate | R Documentation |
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 or bbotk::OptimInstanceAsyncMultiCrit the SurrogateLearnerCollection must use as many learners as there are objective functions.
mlr3mbo::ResultAssigner -> ResultAssignerSurrogate
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().
new()Creates a new instance of this R6 class.
ResultAssignerSurrogate$new(surrogate = NULL)
surrogate(Surrogate | NULL)
The surrogate that is used to predict the mean of all evaluated points.
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 $surrogate.
ResultAssignerSurrogate$assign_result(instance)
instance(bbotk::OptimInstanceBatchSingleCrit | bbotk::OptimInstanceBatchMultiCrit |bbotk::OptimInstanceAsyncSingleCrit | bbotk::OptimInstanceAsyncMultiCrit)
The bbotk::OptimInstance the final result should be assigned to.
clone()The objects of this class are cloneable with this method.
ResultAssignerSurrogate$clone(deep = FALSE)
deepWhether to make a deep clone.
Other Result Assigner:
ResultAssigner,
mlr_result_assigners,
mlr_result_assigners_archive
result_assigner = ras("surrogate")
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