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