CallbackBatchFSelect | R Documentation |
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()
.
mlr3misc::Callback
-> bbotk::CallbackBatch
-> CallbackBatchFSelect
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$train()
.
This stage is called after the final model is trained with the best feature set found.
clone()
The objects of this class are cloneable with this method.
CallbackBatchFSelect$clone(deep = FALSE)
deep
Whether to make a deep clone.
# Write archive to disk
callback_batch_fselect("mlr3fselect.backup",
on_optimization_end = function(callback, context) {
saveRDS(context$instance$archive, "archive.rds")
}
)
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