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mlr3fselect  

Feature Selection for 'mlr3'
View on CRAN: Click here


Download and install mlr3fselect package within the R console
Install from CRAN:
install.packages("mlr3fselect")

Install from Github:
library("remotes")
install_github("cran/mlr3fselect")

Install by package version:
library("remotes")
install_version("mlr3fselect", "1.7.0")



Attach the package and use:
library("mlr3fselect")
Maintained by
Marc Becker
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-08-23
Latest Update: 2025-07-31
Description:
Feature selection package of the 'mlr3' ecosystem. It selects the optimal feature set for any 'mlr3' learner. The package works with several optimization algorithms e.g. Random Search, Recursive Feature Elimination, and Genetic Search. Moreover, it can automatically optimize learners and estimate the performance of optimized feature sets with nested resampling.
How to cite:
Marc Becker (2020). mlr3fselect: Feature Selection for 'mlr3'. R package version 1.7.0, https://cran.r-project.org/web/packages/mlr3fselect. Accessed 06 Oct. 2026.
Previous versions and publish date:
(2026-08-23 11:00), 0.2.0 (2020-08-23 12:40), 0.2.1 (2020-09-10 11:20), 0.3.0 (2020-09-22 17:30), 0.4.0 (2020-10-22 23:20), 0.4.1 (2020-10-30 06:20), 0.5.0 (2021-01-24 15:50), 0.5.1 (2021-03-09 12:00), 0.6.0 (2021-09-13 21:10), 0.6.1 (2022-01-20 17:02), 0.7.0 (2022-04-08 09:12), 0.7.1 (2022-05-03 15:40), 0.7.2 (2022-08-25 12:40), 0.8.0 (2022-11-16 13:10), 0.8.1 (2022-11-27 15:50), 0.9.0 (2022-12-21 15:00), 0.9.1 (2023-01-26 19:20), 0.10.0 (2023-02-21 12:40), 0.11.0 (2023-03-02 12:40), 0.12.0 (2024-03-09 12:30), 1.0.0 (2024-06-29 17:00), 1.1.0 (2024-09-09 21:00), 1.1.1 (2024-10-15 18:40), 1.2.0 (2024-10-25 20:10), 1.2.1 (2024-11-07 22:10), 1.3.0 (2025-01-16 10:40), 1.4.0 (2025-07-31 18:30), 1.5.0 (2025-11-27 11:40), 1.5.1 (2026-03-18 10:00), 1.6.0 (2026-05-21 23:50)
Other packages that cited mlr3fselect R package
View mlr3fselect citation profile
Other R packages that mlr3fselect depends, imports, suggests or enhances
Complete documentation for mlr3fselect
Functions, R codes and Examples using the mlr3fselect R package
Some associated functions: ArchiveFSelect . AutoFSelector . CallbackFSelect . ContextEval . FSelectInstanceMultiCrit . FSelectInstanceSingleCrit . FSelector . FSelectorFromOptimizer . ObjectiveFSelect . auto_fselector . callback_fselect . extract_inner_fselect_archives . extract_inner_fselect_results . fs . fselect . fselect_nested . fsi . mlr3fselect-package . mlr3fselect.backup . mlr3fselect.svm_rfe . mlr_fselectors . mlr_fselectors_design_points . mlr_fselectors_exhaustive_search . mlr_fselectors_genetic_search . mlr_fselectors_random_search . mlr_fselectors_rfe . mlr_fselectors_rfecv . mlr_fselectors_sequential . mlr_fselectors_shadow_variable_search . reexports . 
Some associated R codes: ArchiveFSelect.R . AutoFSelector.R . CallbackFSelect.R . ContextEval.R . FSelectInstanceMultiCrit.R . FSelectInstanceSingleCrit.R . FSelector.R . FSelectorDesignPoints.R . FSelectorExhaustiveSearch.R . FSelectorFromOptimizer.R . FSelectorGeneticSearch.R . FSelectorRFE.R . FSelectorRFECV.R . FSelectorRandomSearch.R . FSelectorSequential.R . FSelectorShadowVariableSearch.R . ObjectiveFSelect.R . assertions.R . auto_fselector.R . bibentries.R . extract_inner_fselect_archives.R . extract_inner_fselect_results.R . fselect.R . fselect_nested.R . helper.R . mlr_callbacks.R . mlr_fselectors.R . reexports.R . sugar.R . zzz.R .  Full mlr3fselect package functions and examples
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