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fuzzyforest (version 1.0.1)

Fuzzy Forests

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.

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Version

Install

install.packages('fuzzyforest')

Monthly Downloads

191

Version

1.0.1

License

GPL-3

Maintainer

Daniel Conn

Last Published

March 9th, 2016

Functions in fuzzyforest (1.0.1)

fuzzyforest

fuzzyforest: an implementation of the fuzzy forest algorithm in R.
wff

Fits WGCNA based fuzzy forest algorithm.
fuzzy_forest

Fuzzy Forest Object
example_ff

Fuzzy Forest Example
screen_control

Set Parameters for Screening Step of Fuzzy Forests
select_RF

Carries out the selection step of fuzzyforest algorithm.
modplot

Plots relative importance of modules.
select_control

Set Parameters for Selection Step of Fuzzy Forests
Liver_Expr

Liver Expression Data from Female Mice
print.fuzzy_forest

Print fuzzy_forest object. Prints output from fuzzy forests algorithm.
ctg

Cardiotocography Data Set
predict.fuzzy_forest

Predict method for fuzzy_forest object. Obtains predictions from fuzzy forest algorithm.
iterative_RF

Fits iterative random forest algorithm.
WGCNA_control

Set Parameters for WGCNA Step of Fuzzy Forests
ff

Fits fuzzy forest algorithm.