Releases: mlr-org/mlr3fselect
Releases · mlr-org/mlr3fselect
mlr3fselect 1.1.0
mlr3fselect 1.0.0
- feat: Add ensemble feature selection function
ensemble_fselect()
. - BREAKING CHANGE: The
FSelector
class isFSelectorBatch
now. - BREAKING CHANGE: THe
FSelectInstanceSingleCrit
andFSelectInstanceMultiCrit
classes areFSelectInstanceBatchSingleCrit
andFSelectInstanceBatchMultiCrit
now. - BREAKING CHANGE: The
CallbackFSelect
class isCallbackBatchFSelect
now. - BREAKING CHANGE: The
ContextEval
class isContextBatchFSelect
now.
mlr3fselect 0.12.0
- feat: Add number of features to
instance$result
. - feat: Add
ties_method
options"least_features"
and"random"
toArchiveFSelect$best()
. - refactor: Optimize runtime of
ArchiveFSelect$best()
method. - feat: Add importance scores to result of
FSelectorRFE
. - feat: Add number of features to
as.data.table.ArchiveFSelect()
. - feat: Features can be always included with the
always_include
column role. - fix: Add
$phash()
method toAutoFSelector
. - fix: Include
FSelector
in hash ofAutoFSelector
. - refactor: Change default batch size of
FSelectorRandomSearch
to 10. - feat: Add
batch_size
parameter toFSelectorExhaustiveSearch
to reduce memory consumption. - compatibility: Work with new paradox version 1.0.0
mlr3fselect 0.11.0
- BREAKING CHANGE: The
method
parameter offselect()
,fselect_nested()
andauto_fselector()
is renamed tofselector
.
OnlyFSelector
objects are accepted now.
Arguments to the fselector cannot be passed with...
anymore. - BREAKING CHANGE: The
fselect
parameter ofFSelector
is moved to the first position to achieve consistency with the other functions. - docs: Update resources sections.
- docs: Add list of default measures.
mlr3fselect 0.10.0
- feat: Add callback
mlr3fselect.svm_rfe
to run recursive feature elimination on linear support vector machines. - refactor: The importance scores in
FSelectorRFE
are now aggregated by rank instead of averaging them. - feat: Add
FSelectorRFECV
optimizer to run recursive feature elimination with cross-validation. - refactor:
FSelectorRFE
works withoutstore_models = TRUE
now. - feat: The
as.data.table.ArchiveFSelect()
function additionally returns a character vector of selected features for each row. - refactor: Add
callbacks
argument tofsi()
function.
mlr3fselect 0.9.1
- refactor: Remove internal use of
mlr3pipelines
. - fix: Feature selection with measures that require the importance or oob error works now.
mlr3fselect 0.9.0
- fix: Add
genalg
to required packages ofFSelectorGeneticSearch
. - feat: Add new callback that backups the benchmark result to disk after each batch.
- feat: Create custom callbacks with the
callback_fselect()
function.
mlr3fselect 0.8.1
- fix: Add
genalg
to required packages ofFSelectorGeneticSearch
.
mlr3fselect 0.8.0
- refactor:
FSelectorRFE
throws an error if the learner does not support the$importance()
method. - refactor: The
AutoFSelector
stores the instance and benchmark result ifstore_models = TRUE
. - refactor: The
AutoFSelector
stores the instance ifstore_benchmark_result = TRUE
. - feat: Add missing parameters from
AutoFSelector
toauto_fselect()
. - feat: Add
fsi()
function to create aFSelectInstanceSingleCrit
orFSelectInstanceMultiCrit
. - refactor: Remove
unnest
option fromas.data.table.ArchiveFSelect()
function.
mlr3fselect 0.7.2
- docs: Re-generate rd files with valid html.