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fuzzyforest  

Fuzzy Forests
View on CRAN: Click here


Download and install fuzzyforest package within the R console
Install from CRAN:
install.packages("fuzzyforest")

Install from Github:
library("remotes")
install_github("cran/fuzzyforest")

Install by package version:
library("remotes")
install_version("fuzzyforest", "1.0.8")



Attach the package and use:
library("fuzzyforest")
Maintained by
Daniel Conn
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-02-18
Latest Update: 2020-03-25
Description:
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) for further details.
How to cite:
Daniel Conn (2016). fuzzyforest: Fuzzy Forests. R package version 1.0.8, https://cran.r-project.org/web/packages/fuzzyforest. Accessed 25 Jun. 2026.
Previous versions and publish date:
1.0.0 (2016-02-18 18:46), 1.0.1 (2016-03-10 00:28), 1.0.2 (2016-06-16 05:28), 1.0.3 (2017-06-11 22:05), 1.0.4 (2017-11-12 23:11), 1.0.5 (2018-02-03 05:16), 1.0.6 (2019-10-27 00:40), 1.0.7 (2020-02-05 16:40)
Other packages that cited fuzzyforest R package
View fuzzyforest citation profile
Other R packages that fuzzyforest depends, imports, suggests or enhances
Complete documentation for fuzzyforest
Functions, R codes and Examples using the fuzzyforest R package
Some associated functions: Liver_Expr . WGCNA_control . ctg . example_ff . ff.formula . ff . fuzzy_forest . fuzzyforest . iterative_RF . modplot . multi_class_lr . predict.fuzzy_forest . print.fuzzy_forest . screen_control . select_RF . select_control . wff.formula . wff . 
Some associated R codes: ff.R . ff_sims.R . fuzzy_forest_obj.R . fuzzyforest.R . onAttach.R . select_RF.R . tuning_parameters.R . wff.R .  Full fuzzyforest package functions and examples
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