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:	0.2.0
Depends:	R (≥ 4.1)
Imports:	cli, desirability2 (≥ 0.1.0), dplyr, generics, pROC, purrr, rlang (≥ 1.1.0), S7, stats, tibble, tidyr, vctrs
Suggests:	aorsf, FSelectorRcpp, knitr, modeldata, partykit, quarto, ranger, rmarkdown, testthat (≥ 3.0.0), titanic
Published:	2025-08-26
DOI:	10.32614/CRAN.package.filtro
Author:	Frances Lin [aut, cre], Max Kuhn [aut], Emil Hvitfeldt [aut], Posit Software, PBC [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, https://filtro.tidymodels.org/
NeedsCompilation:	no
Materials:	README, NEWS
CRAN checks:	filtro results

Documentation:

Reference manual:	filtro.html , filtro.pdf
Vignettes:	Introduction to filtro (source, R code) Scoring via random forests (source, R code)

Downloads:

Package source:	filtro_0.2.0.tar.gz
Windows binaries:	r-devel: filtro_0.1.0.zip, r-release: filtro_0.1.0.zip, r-oldrel: filtro_0.1.0.zip
macOS binaries:	r-release (arm64): filtro_0.1.0.tgz, r-oldrel (arm64): filtro_0.1.0.tgz, r-release (x86_64): filtro_0.1.0.tgz, r-oldrel (x86_64): filtro_0.1.0.tgz
Old sources:	filtro archive

Linking:

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