CallbackBatchFSelect {mlr3fselect} | R Documentation |
Create Feature Selection Callback
Description
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 inObjectiveFSelectBatch$eval_many()
.on_eval_after_benchmark
(
function()
)
Stage called after feature sets are evaluated. Called inObjectiveFSelectBatch$eval_many()
.on_eval_before_archive
(
function()
)
Stage called before performance values are written to the archive. Called inObjectiveFSelectBatch$eval_many()
.on_auto_fselector_before_final_model
(
function()
)
Stage called before the final model is trained. Called inAutoFSelector$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 inAutoFSelector$train()
. This stage is called after the final model is trained with the best feature set found.
Methods
Public methods
Inherited methods
Method clone()
The objects of this class are cloneable with this method.
Usage
CallbackBatchFSelect$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")
}
)