mlr3filters: Filter Based Feature Selection for 'mlr3'

Extends 'mlr3' with filter methods for feature selection. Besides standalone filter methods built-in methods of any machine-learning algorithm are supported. Partial scoring of multivariate filter methods is supported.

Version: 0.8.0
Depends: R (≥ 3.1.0)
Imports: backports, checkmate, data.table, mlr3 (≥ 0.12.0), mlr3misc, paradox, R6
Suggests: Boruta, care, caret, carSurv, FSelectorRcpp, knitr, lgr, mlr3learners, mlr3measures, mlr3pipelines, praznik, rpart, survival, testthat (≥ 3.0.0), withr
Published: 2024-04-10
DOI: 10.32614/CRAN.package.mlr3filters
Author: Patrick Schratz ORCID iD [aut], Michel Lang ORCID iD [cre, aut], Bernd Bischl ORCID iD [aut], Martin Binder [aut], John Zobolas ORCID iD [aut]
Maintainer: Michel Lang <michellang at>
License: LGPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: mlr3filters results


Reference manual: mlr3filters.pdf


Package source: mlr3filters_0.8.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): mlr3filters_0.8.0.tgz, r-oldrel (arm64): mlr3filters_0.8.0.tgz, r-release (x86_64): mlr3filters_0.8.0.tgz, r-oldrel (x86_64): mlr3filters_0.8.0.tgz
Old sources: mlr3filters archive

Reverse dependencies:

Reverse imports: mlr3verse, sense
Reverse suggests: mlr3pipelines, mlr3spatiotempcv, mlr3viz


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