filtro: Feature Selection Using Supervised Filter-Based Methods

Tidy tools to apply filter-based supervised feature selection methods. These methods score and rank feature relevance using metrics such as p-values, correlation, and importance scores (Kuhn and Johnson (2019) <doi:10.1201/9781315108230>).

Version: 0.1.0
Depends: R (≥ 4.1)
Imports: purrr, rlang (≥ 1.1.0), stats, tibble
Suggests: aorsf, dplyr, FSelectorRcpp, modeldata, partykit, ranger, testthat (≥ 3.0.0), titanic
Published: 2025-07-18
DOI: 10.32614/CRAN.package.filtro
Author: Frances Lin [aut, cre], Max Kuhn [aut], Emil Hvitfeldt [aut], Posit Software, PBC ROR ID [cph, fnd]
Maintainer: Frances Lin <franceslinyc at gmail.com>
BugReports: https://github.com/tidymodels/filtro/issues
License: MIT + file LICENSE
URL: https://github.com/tidymodels/filtro
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: filtro results

Documentation:

Reference manual: filtro.html , filtro.pdf

Downloads:

Package source: filtro_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: filtro_0.1.0.zip, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): filtro_0.1.0.tgz, r-oldrel (x86_64): filtro_0.1.0.tgz

Linking:

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