forestControl: Approximate False Positive Rate Control in Selection Frequency for Random Forest

Approximate false positive rate control in selection frequency for random forest using the methods described by Ender Konukoglu and Melanie Ganz (2014) <doi:10.48550/arXiv.1410.2838>. Methods for calculating the selection frequency threshold at false positive rates and selection frequency false positive rate feature selection.

Version:	0.2.2
Imports:	Rcpp, purrr, tibble, magrittr, dplyr
LinkingTo:	Rcpp
Suggests:	testthat, randomForest, ranger, parsnip, knitr, rmarkdown
Published:	2022-02-09
DOI:	10.32614/CRAN.package.forestControl
Author:	Tom Wilson [aut, cre], Jasen Finch [aut]
Maintainer:	Tom Wilson <tpw2 at aber.ac.uk>
BugReports:	https://github.com/aberHRML/forestControl/issues
License:	MIT + file LICENSE
URL:	https://github.com/aberHRML/forestControl
NeedsCompilation:	yes
Citation:	forestControl citation info
Materials:	NEWS
CRAN checks:	forestControl results

Documentation:

Reference manual:	forestControl.pdf
Vignettes:	Getting_started

Downloads:

Package source:	forestControl_0.2.2.tar.gz
Windows binaries:	r-devel: forestControl_0.2.2.zip, r-release: forestControl_0.2.2.zip, r-oldrel: forestControl_0.2.2.zip
macOS binaries:	r-release (arm64): forestControl_0.2.2.tgz, r-oldrel (arm64): forestControl_0.2.2.tgz, r-release (x86_64): forestControl_0.2.2.tgz, r-oldrel (x86_64): forestControl_0.2.2.tgz
Old sources:	forestControl archive

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