binomialRF: Binomial Random Forest Feature Selection

The 'binomialRF' is a new feature selection technique for decision trees that aims at providing an alternative approach to identify significant feature subsets using binomial distributional assumptions (Rachid Zaim, S., et al. (2019)) <doi:10.1101/681973>. Treating each splitting variable selection as a set of exchangeable correlated Bernoulli trials, 'binomialRF' then tests whether a feature is selected more often than by random chance.

Version: 0.1.0
Imports: randomForest, data.table, stats, rlist
Suggests: foreach, knitr, rmarkdown, correlbinom
Published: 2020-03-26
Author: Samir Rachid Zaim [aut, cre]
Maintainer: Samir Rachid Zaim <samirrachidzaim at math.arizona.edu>
License: GPL-2
URL: https://www.biorxiv.org/content/10.1101/681973v1.abstract
NeedsCompilation: no
Materials: README NEWS
CRAN checks: binomialRF results

Documentation:

Reference manual: binomialRF.pdf
Vignettes: "binomialRF Feature Selection Vignette"

Downloads:

Package source: binomialRF_0.1.0.tar.gz
Windows binaries: r-devel: binomialRF_0.1.0.zip, r-release: binomialRF_0.1.0.zip, r-oldrel: binomialRF_0.1.0.zip
macOS binaries: r-release (arm64): binomialRF_0.1.0.tgz, r-oldrel (arm64): binomialRF_0.1.0.tgz, r-release (x86_64): binomialRF_0.1.0.tgz, r-oldrel (x86_64): binomialRF_0.1.0.tgz
Old sources: binomialRF archive

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