fuzzyforest: Fuzzy Forests

Fuzzy forests, a new algorithm based on random forests, is designed to reduce the bias seen in random forest feature selection caused by the presence of correlated features. Fuzzy forests uses recursive feature elimination random forests to select features from separate blocks of correlated features where the correlation within each block of features is high and the correlation between blocks of features is low. One final random forest is fit using the surviving features. This package fits random forests using the 'randomForest' package and allows for easy use of 'WGCNA' to split features into distinct blocks. See D. Conn, Ngun, T., C. Ramirez, and G. Li (2019) <doi:10.18637/jss.v091.i09> for further details.

Version: 1.0.8
Depends: R (≥ 3.2.1)
Imports: randomForest, foreach, doParallel, parallel, ggplot2, mvtnorm
Suggests: WGCNA, testthat
Published: 2020-03-25
DOI: 10.32614/CRAN.package.fuzzyforest
Author: Daniel Conn [aut, cre], Tuck Ngun [aut], Christina M. Ramirez [aut]
Maintainer: Daniel Conn <djconn17 at gmail.com>
License: GPL-3
NeedsCompilation: no
Citation: fuzzyforest citation info
Materials: README
CRAN checks: fuzzyforest results


Reference manual: fuzzyforest.pdf


Package source: fuzzyforest_1.0.8.tar.gz
Windows binaries: r-devel: fuzzyforest_1.0.8.zip, r-release: fuzzyforest_1.0.8.zip, r-oldrel: fuzzyforest_1.0.8.zip
macOS binaries: r-release (arm64): fuzzyforest_1.0.8.tgz, r-oldrel (arm64): fuzzyforest_1.0.8.tgz, r-release (x86_64): fuzzyforest_1.0.8.tgz, r-oldrel (x86_64): fuzzyforest_1.0.8.tgz
Old sources: fuzzyforest archive


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