Changes in version 1.6.0 (2026-05-21) - refactor: Remove rush backward compatibility. - docs: Add hEFS reference. - compatibility: fastVoteR 0.0.3 - feat: Add $rm_zero_features() method in EnsembleFSResult to remove result rows where no features were selected. Changes in version 1.5.1 (2026-03-18) - compatibility: rush 1.0.0 Changes in version 1.5.0 (2025-11-27) - fix: Add always_included column role to all registered tasks. - perf: Add fast aggregation for ResampleResult and BenchmarkResult objects to speed up objective function evaluation. Changes in version 1.4.0 (2025-07-31) - feat: Introduce asynchronous optimization with the FSelectorAsync and FSelectInstanceAsync* classes. - feat: Add max_nfeatures argument in the pareto_front() and knee_points() methods of an EnsembleFSResult(). - feat: Classes are now printed with the cli package. Changes in version 1.3.0 (2025-01-16) - refactor: Use fastVoteR for feature ranking in EnsembleFSResult() objects - feat: Add embedded ensemble feature selection embedded_ensemble_fselect() - refactor/perf: ensemble_fselect() and EnsembleFSResult() - feat: Add c.EnsembleFSResult(...) and EnsembleFSResult$combine(...) methods Changes in version 1.2.1 (2024-11-07) - compatibility: mlr3 0.22.0 Changes in version 1.2.0 (2024-10-25) - feat: Add internal tuning callback mlr3fselect.internal_tuning. - fix: Register mlr3fselect in the mlr_reflections$loaded_packages field. Changes in version 1.1.1 (2024-10-15) - compatibility: bbotk 1.1.1 Changes in version 1.1.0 (2024-09-09) - compatibility: mlr3 0.21.0 - fix: Delete intermediate BenchmarkResult in ObjectiveFSelectBatch after optimization. - fix: Reloading mlr3fselect does not duplicate column roles anymore. - perf: Remove x_domain column from archive. Changes in version 1.0.0 (2024-06-29) - feat: Add ensemble feature selection function ensemble_fselect(). - BREAKING CHANGE: The FSelector class is FSelectorBatch now. - BREAKING CHANGE: THe FSelectInstanceSingleCrit and FSelectInstanceMultiCrit classes are FSelectInstanceBatchSingleCrit and FSelectInstanceBatchMultiCrit now. - BREAKING CHANGE: The CallbackFSelect class is CallbackBatchFSelect now. - BREAKING CHANGE: The ContextEval class is ContextBatchFSelect now. Changes in version 0.12.0 (2024-03-09) - feat: Add number of features to instance$result. - feat: Add ties_method options "least_features" and "random" to ArchiveBatchFSelect$best(). - refactor: Optimize runtime of ArchiveBatchFSelect$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 to AutoFSelector. - fix: Include FSelector in hash of AutoFSelector. - refactor: Change default batch size of FSelectorBatchRandomSearch to 10. - feat: Add batch_size parameter to FSelectorBatchExhaustiveSearch to reduce memory consumption. - compatibility: Work with new paradox version 1.0.0 Changes in version 0.11.0 (2023-03-02) - BREAKING CHANGE: The method parameter of fselect(), fselect_nested() and auto_fselector() is renamed to fselector. Only FSelector objects are accepted now. Arguments to the fselector cannot be passed with ... anymore. - BREAKING CHANGE: The fselect parameter of FSelector is moved to the first position to achieve consistency with the other functions. - docs: Update resources sections. - docs: Add list of default measures. Changes in version 0.10.0 (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 without store_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 to fsi() function. Changes in version 0.9.1 (2023-01-26) - refactor: Remove internal use of mlr3pipelines. - fix: Feature selection with measures that require the importance or oob error works now. Changes in version 0.9.0 (2022-12-21) - fix: Add genalg to required packages of FSelectorBatchGeneticSearch. - feat: Add new callback that backups the benchmark result to disk after each batch. - feat: Create custom callbacks with the callback_batch_fselect() function. Changes in version 0.8.0 (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 if store_models = TRUE. - refactor: The AutoFSelector stores the instance if store_benchmark_result = TRUE. - feat: Add missing parameters from AutoFSelector to auto_fselect(). - feat: Add fsi() function to create a FSelectInstanceBatchSingleCrit or FSelectInstanceBatchMultiCrit. - refactor: Remove unnest option from as.data.table.ArchiveBatchFSelect() function. Changes in version 0.7.2 (2022-08-25) - docs: Re-generate rd files with valid html. Changes in version 0.7.1 (2022-05-03) - feat: FSelector objects have the field $id now. Changes in version 0.7.0 (2022-04-08) - feat: Allow to pass FSelector objects as method in fselect() and auto_fselector(). - feat: Added $label to FSelectors. - docs: New examples with fselect() function. - feat: $help() method which opens manual page of a FSelector. - feat: Added a as.data.table.DictionaryFSelector function. - feat: Added min_features parameter to FSelectorBatchSequential. Changes in version 0.6.1 (2022-01-20) - Add store_models flag to fselect(). - Remove store_x_domain flag. Changes in version 0.6.0 (2021-09-13) - Adds AutoFSelector$base_learner() method to extract the base learner from nested learner objects. - Adds fselect(), auto_fselector() and fselect_nested() sugar functions. - Adds extract_inner_fselect_results() and extract_inner_fselect_archives() helper function to extract inner feature selection results and archives. Changes in version 0.5.1 (2021-03-09) - Remove x_domain column from archive. Changes in version 0.5.0 (2021-01-24) - FSelectorRFE stores importance values of each evaluated feature set in archive. - ArchiveBatchFSelect$data is a public field now. Changes in version 0.4.1 (2020-10-30) - Fix bug in AutoFSelector$predict() Changes in version 0.4.0 (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 to AutoFSelector. - 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 and check_values in AutoFSelector. store_fselect_instance must be set as a parameter during initialization. - Adds FSelectorBatchGeneticSearch. - Fixes check_values flag in FSelectInstanceBatchSingleCrit and FSelectInstanceBatchMultiCrit. - Removed dependency on orphaned package bibtex. - PipeOpSelect is internally used for task subsetting. Changes in version 0.3.0 (2020-09-22) - Archive is ArchiveBatchFSelect 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. Changes in version 0.2.1 (2020-09-10) - Warning message if external package for feature selection is not installed. Changes in version 0.2.0 (2020-08-23) - Initial CRAN release.