Create Feature Selection Callback

Specialized bbotk::CallbackBatch for feature selection. Callbacks allow customizing the behavior of processes in mlr3fselect. The callback_batch_fselect() function creates a CallbackBatchFSelect. Predefined callbacks are stored in the dictionary mlr_callbacks and can be retrieved with clbk(). For more information on callbacks see callback_batch_fselect().

Super classes

mlr3misc::Callback -> bbotk::CallbackBatch -> CallbackBatchFSelect

Public fields

on_eval_after_design

(function())
Stage called after design is created. Called in ObjectiveFSelectBatch$eval_many().

on_eval_after_benchmark

(function())
Stage called after feature sets are evaluated. Called in ObjectiveFSelectBatch$eval_many().

on_eval_before_archive

(function())
Stage called before performance values are written to the archive. Called in ObjectiveFSelectBatch$eval_many().

on_auto_fselector_before_final_model

(function())
Stage called before the final model is trained. Called in AutoFSelector$train(). This stage is called after the optimization has finished and the final model is trained with the best feature set found.

on_auto_fselector_after_final_model

(function())
Stage called after the final model is trained. Called in AutoFSelector$train(). This stage is called after the final model is trained with the best feature set found.

Methods

Public methods

• CallbackBatchFSelect$clone()

Inherited methods

• mlr3misc::Callback$call()
• mlr3misc::Callback$format()
• mlr3misc::Callback$help()
• mlr3misc::Callback$initialize()
• mlr3misc::Callback$print()

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Method clone()

The objects of this class are cloneable with this method.

Usage

CallbackBatchFSelect$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

# Write archive to disk
callback_batch_fselect("mlr3fselect.backup",
  on_optimization_end = function(callback, context) {
    saveRDS(context$instance$archive, "archive.rds")
  }
)
#> <CallbackBatchFSelect:mlr3fselect.backup>
#> * Active Stages: on_optimization_end