Changelog
Source:NEWS.md
mlr3fselect 1.2.0
CRAN release: 2024-10-25
- feat: Add internal tuning callback
mlr3fselect.internal_tuning
. - fix: Register mlr3fselect in the
mlr_reflections$loaded_packages
field.
mlr3fselect 1.1.0
CRAN release: 2024-09-09
- compatibility: mlr3 0.21.0
- fix: Delete intermediate
BenchmarkResult
inObjectiveFSelectBatch
after optimization. - fix: Reloading mlr3fselect does not duplicate column roles anymore.
- perf: Remove
x_domain
column from archive.
mlr3fselect 1.0.0
CRAN release: 2024-06-29
- feat: Add ensemble feature selection function
ensemble_fselect()
. - BREAKING CHANGE: The
FSelector
class isFSelectorBatch
now. - BREAKING CHANGE: THe
FSelectInstanceSingleCrit
andFSelectInstanceMultiCrit
classes areFSelectInstanceBatchSingleCrit
andFSelectInstanceBatchMultiCrit
now. - BREAKING CHANGE: The
CallbackFSelect
class isCallbackBatchFSelect
now. - BREAKING CHANGE: The
ContextEval
class isContextBatchFSelect
now.
mlr3fselect 0.12.0
CRAN release: 2024-03-09
- feat: Add number of features to
instance$result
. - feat: Add
ties_method
options"least_features"
and"random"
toArchiveBatchFSelect$best()
. - refactor: Optimize runtime of
ArchiveBatchFSelect$best()
method. - feat: Add importance scores to result of
FSelectorRFE
. - feat: Add number of features to
as.data.table.ArchiveBatchFSelect()
. - feat: Features can be always included with the
always_include
column role. - fix: Add
$phash()
method toAutoFSelector
. - fix: Include
FSelector
in hash ofAutoFSelector
. - refactor: Change default batch size of
FSelectorBatchRandomSearch
to 10. - feat: Add
batch_size
parameter toFSelectorBatchExhaustiveSearch
to reduce memory consumption. - compatibility: Work with new paradox version 1.0.0
mlr3fselect 0.11.0
CRAN release: 2023-03-02
- BREAKING CHANGE: The
method
parameter offselect()
,fselect_nested()
andauto_fselector()
is renamed tofselector
. OnlyFSelector
objects are accepted now. Arguments to the fselector cannot be passed with...
anymore. - BREAKING CHANGE: The
fselect
parameter ofFSelector
is moved to the first position to achieve consistency with the other functions. - docs: Update resources sections.
- docs: Add list of default measures.
mlr3fselect 0.10.0
CRAN release: 2023-02-21
- feat: Add callback
mlr3fselect.svm_rfe
to run recursive feature elimination on linear support vector machines. - refactor: The importance scores in
FSelectorRFE
are now aggregated by rank instead of averaging them. - feat: Add
FSelectorRFECV
optimizer to run recursive feature elimination with cross-validation. - refactor:
FSelectorRFE
works withoutstore_models = TRUE
now. - feat: The
as.data.table.ArchiveBatchFSelect()
function additionally returns a character vector of selected features for each row. - refactor: Add
callbacks
argument tofsi()
function.
mlr3fselect 0.9.1
CRAN release: 2023-01-26
- refactor: Remove internal use of
mlr3pipelines
. - fix: Feature selection with measures that require the importance or oob error works now.
mlr3fselect 0.9.0
CRAN release: 2022-12-21
- fix: Add
genalg
to required packages ofFSelectorBatchGeneticSearch
. - feat: Add new callback that backups the benchmark result to disk after each batch.
- feat: Create custom callbacks with the
callback_batch_fselect()
function.
mlr3fselect 0.8.0
CRAN release: 2022-11-16
- refactor:
FSelectorRFE
throws an error if the learner does not support the$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 aFSelectInstanceBatchSingleCrit
orFSelectInstanceBatchMultiCrit
. - refactor: Remove
unnest
option fromas.data.table.ArchiveBatchFSelect()
function.
mlr3fselect 0.7.0
CRAN release: 2022-04-08
- feat: Allow to pass
FSelector
objects asmethod
infselect()
andauto_fselector()
. - feat: Added
$label
toFSelector
s. - docs: New examples with
fselect()
function. - feat:
$help()
method which opens manual page of aFSelector
. - feat: Added a
as.data.table.DictionaryFSelector
function. - feat: Added
min_features
parameter toFSelectorBatchSequential
.
mlr3fselect 0.6.1
CRAN release: 2022-01-20
- Add
store_models
flag tofselect()
. - Remove
store_x_domain
flag.
mlr3fselect 0.6.0
CRAN release: 2021-09-13
- Adds
AutoFSelector$base_learner()
method to extract the base learner from nested learner objects. - Adds
fselect()
,auto_fselector()
andfselect_nested()
sugar functions. - Adds
extract_inner_fselect_results()
andextract_inner_fselect_archives()
helper function to extract inner feature selection results and archives.
mlr3fselect 0.5.0
CRAN release: 2021-01-24
-
FSelectorRFE
stores importance values of each evaluated feature set in archive. -
ArchiveBatchFSelect$data
is a public field now.
mlr3fselect 0.4.0
CRAN release: 2020-10-22
- Compact in-memory representation of R6 objects to save space when saving mlr3 objects via saveRDS(), serialize() etc.
-
FSelectorRFE
supports fraction of features to retain in each iteration (feature_fraction
), number of features to remove in each iteration (feature_number
) and vector of number of features to retain in each iteration (subset_sizes
). -
AutoFSelect
is renamed toAutoFSelector
. - To retrieve the inner feature selection results in nested resampling,
as.data.table(rr)$learner[[1]]$fselect_result
must be used now. - Option to control
store_benchmark_result
,store_models
andcheck_values
inAutoFSelector
.store_fselect_instance
must be set as a parameter during initialization. - Adds
FSelectorBatchGeneticSearch
. - Fixes
check_values
flag inFSelectInstanceBatchSingleCrit
andFSelectInstanceBatchMultiCrit
. - Removed dependency on orphaned package
bibtex
. -
PipeOpSelect
is internally used for task subsetting.
mlr3fselect 0.3.0
CRAN release: 2020-09-22
-
Archive
isArchiveBatchFSelect
now which stores the benchmark result in$benchmark_result
. This change removed the resample results from the archive but they can be still accessed via the benchmark result.