Package: featR Title: A Unified Toolkit for Feature Selection Version: 0.1.0 Authors@R: person("Justin", "Chase", email = "jchase.msu@gmail.com", role = c("aut", "cre", "cph")) Description: Filter, wrapper, and embedded feature-selection methods behind a consistent set of functions that share one calling convention and one return type: correlation and chi-squared filters, information gain, LASSO and elastic net, Bayesian model comparison, Boruta, recursive feature elimination, random forest importance, multivariate adaptive regression splines, support vector machine recursive feature elimination, stepwise selection, and principal component / singular value decomposition helpers. The implemented methods follow Tibshirani (1996) , Zou and Hastie (2005) , Friedman (1991) , Breiman (2001) , Guyon, Weston, Barnhill and Vapnik (2002) , Kursa and Rudnicki (2010) , and Vehtari, Gelman and Gabry (2017) . Heavy modeling engines are optional and only required by the functions that use them. License: MIT + file LICENSE Encoding: UTF-8 Language: en-US Roxygen: list(markdown = TRUE) Config/roxygen2/version: 8.1.0 Depends: R (>= 4.1.0) Imports: data.table, parallel, stats, utils, withr Suggests: bigstatsr, Boruta, brms, caret, doParallel, e1071, earth, foreach, furrr, future, ggplot2, glmnet, kernlab, knitr, loo, MASS, Matrix, MLmetrics, pbapply, polycor, pROC, PRROC, randomForest, rmarkdown, RSpectra, testthat (>= 3.0.0) VignetteBuilder: knitr Config/testthat/edition: 3 URL: https://github.com/elkronos/featR, https://elkronos.github.io/featR/ BugReports: https://github.com/elkronos/featR/issues Repository: https://elkronos.r-universe.dev Date/Publication: 2026-09-27 03:56:43 UTC RemoteUrl: https://github.com/elkronos/featr RemoteRef: HEAD RemoteSha: f744cfd738b1f1431cca3342aa903e26aa6ae280 NeedsCompilation: no Packaged: 2026-09-27 08:27:20 UTC; root Author: Justin Chase [aut, cre, cph] Maintainer: Justin Chase