Stores the objective function that estimates the performance of hyperparameter configurations. This class is usually constructed internally by the TuningInstanceSingleCrit / TuningInstanceMultiCrit.
bbotk::Objective -> ObjectiveTuning
task(mlr3::Task).
learnerresamplingmeasures(list of mlr3::Measure).
store_models(logical(1)).
store_benchmark_result(logical(1)).
archivenew()Creates a new instance of this R6 class.
ObjectiveTuning$new( task, learner, resampling, measures, check_values = TRUE, store_benchmark_result = TRUE, store_models = FALSE )
task(mlr3::Task) Task to operate on.
learnerresampling(mlr3::Resampling) Uninstantiated resamplings are instantiated during construction so that all configurations are evaluated on the same data splits.
measures(list of mlr3::Measure)
Measures to optimize.
If NULL, mlr3's default measure is used.
check_values(logical(1))
Should parameters before the evaluation and the results be checked for
validity?
store_benchmark_result(logical(1))
Store benchmark result in archive?
store_models(logical(1))
Store models in benchmark result?
clone()The objects of this class are cloneable with this method.
ObjectiveTuning$clone(deep = FALSE)
deepWhether to make a deep clone.