About Anaconda Help Download Anaconda

r / packages / r-fuzzyforest

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.

Click on a badge to see how to embed it in your web page
badge
https://anaconda.org/r/r-fuzzyforest/badges/version.svg
badge
https://anaconda.org/r/r-fuzzyforest/badges/latest_release_date.svg
badge
https://anaconda.org/r/r-fuzzyforest/badges/latest_release_relative_date.svg
badge
https://anaconda.org/r/r-fuzzyforest/badges/platforms.svg
badge
https://anaconda.org/r/r-fuzzyforest/badges/license.svg
badge
https://anaconda.org/r/r-fuzzyforest/badges/downloads.svg

© 2025 Anaconda, Inc. All Rights Reserved. (v4.0.6) Legal | Privacy Policy