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Stores the objective function that estimates the performance of feature subsets. This class is usually constructed internally by the FSelectInstanceBatchSingleCrit / FSelectInstanceBatchMultiCrit.

Super classes

bbotk::Objective -> mlr3fselect::ObjectiveFSelect -> ObjectiveFSelectBatch

Public fields

Methods

Inherited methods


Method new()

Creates a new instance of this R6 class.

Usage

ObjectiveFSelectBatch$new(
  task,
  learner,
  resampling,
  measures,
  check_values = TRUE,
  store_benchmark_result = TRUE,
  store_models = FALSE,
  archive = NULL,
  callbacks = NULL
)

Arguments

task

(mlr3::Task)
Task to operate on.

learner

(mlr3::Learner)
Learner to optimize the feature subset for.

resampling

(mlr3::Resampling)
Resampling that is used to evaluated the performance of the feature subsets. Uninstantiated resamplings are instantiated during construction so that all feature subsets are evaluated on the same data splits. Already instantiated resamplings are kept unchanged.

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?

archive

(ArchiveBatchFSelect)
Reference to the archive of FSelectInstanceBatchSingleCrit | FSelectInstanceBatchMultiCrit. If NULL (default), benchmark result and models cannot be stored.

callbacks

(list of CallbackBatchFSelect)
List of callbacks.


Method clone()

The objects of this class are cloneable with this method.

Usage

ObjectiveFSelectBatch$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.