Liver_Expr

A data set containing gene expression levels in liver tissue from female
mice. This data set is a subset of the liver expression data set
from the WGCNA tutorial <a href="https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/Tutorials/">https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/Tutorials/</a>.
The tutorial contains further information about the data set as well as
extensive examples of WGCNA.

datasets

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.

Daniel Conn

fuzzyforest

Fuzzy Forests

Tuck Ngun

Christina M. Ramirez

Liver_Expr function

A data frame with 66 rows and 3601

Format

A data set containing gene expression levels in liver tissue from female
mice. This data set is a subset of the liver expression data set
from the WGCNA tutorial <a href='https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/Tutorials/'>https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/Tutorials/</a>.
The tutorial contains further information about the data set as well as
extensive examples of WGCNA.

Liver_Expr: Liver Expression Data from Female Mice

Description

Usage

Arguments

Format

Details