Package: VSURF
Type: Package
Title: Variable Selection Using Random Forests
Version: 1.2.1
Date: 2025-10-21
Depends: R (>= 4.2.0)
Authors@R: c(person("Robin", "Genuer", email = "Robin.Genuer@u-bordeaux.fr", role = c("aut", "cre")),
             person("Jean-Michel", "Poggi", role = "aut"),
             person("Christine", "Tuleau-Malot", role = "aut"))
Description: Three steps variable selection procedure based on random forests.
    Initially developed to handle high dimensional data (for which number of
    variables largely exceeds number of observations), the package is very
    versatile and can treat most dimensions of data, for regression and
    supervised classification problems. First step is dedicated to eliminate
    irrelevant variables from the dataset. Second step aims to select all
    variables related to the response for interpretation purpose. Third step
    refines the selection by eliminating redundancy in the set of variables
    selected by the second step, for prediction purpose.
    Genuer, R. Poggi, J.-M. and Tuleau-Malot, C. (2015)
    <https://journal.r-project.org/articles/RJ-2015-018/>.
License: GPL (>= 2)
LazyData: true
URL: https://github.com/robingenuer/VSURF
BugReports: https://github.com/robingenuer/VSURF/issues
Imports: doParallel, foreach, parallel, randomForest, rpart
Suggests: testthat, ranger, Rborist
RoxygenNote: 7.3.3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2025-10-21 12:04:04 UTC; rg
Author: Robin Genuer [aut, cre],
  Jean-Michel Poggi [aut],
  Christine Tuleau-Malot [aut]
Maintainer: Robin Genuer <Robin.Genuer@u-bordeaux.fr>
Repository: CRAN
Date/Publication: 2025-10-21 16:10:28 UTC
Built: R 4.6.0; ; 2026-04-25 11:11:30 UTC; unix
