fuzzy_forest

List of selected features along with variable
importance measures.

feature_list

A final random forest fit using the features
selected by fuzzy forests.

final_rf

Module membership of each feature.

module_membership

If applicable, output of WGCNA analysis.

WGCNA_object

List of features that have survived screening step.

survivor_list

List of features retained at each iteration of
selection step.

selection_list

Fuzzy forests returns an object of type
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.

fuzzy_forest: Fuzzy Forest Object

Description

Usage

Arguments

Value