Learn R Programming

RRF (version 1.9.4)

Regularized Random Forest

Description

Feature Selection with Regularized Random Forest. This package is based on the 'randomForest' package by Andy Liaw. The key difference is the RRF() function that builds a regularized random forest. Fortran original by Leo Breiman and Adele Cutler, R port by Andy Liaw and Matthew Wiener, Regularized random forest for classification by Houtao Deng, Regularized random forest for regression by Xin Guan. Reference: Houtao Deng (2013) .

Copy Link

Version

Install

install.packages('RRF')

Monthly Downloads

1,654

Version

1.9.4

License

GPL (>= 2)

Maintainer

Last Published

May 30th, 2022

Functions in RRF (1.9.4)

grow

Add trees to an ensemble
plot.RRF

Plot method for RRF objects
RRF

Feature Selection with Regularized Random Forest
predict.RRF

predict method for random forest objects
MDSplot

Multi-dimensional Scaling Plot of Proximity matrix from RRF
outlier

Compute outlying measures
partialPlot

Partial dependence plot
varUsed

Variables used in a random forest
classCenter

Prototypes of groups.
rrfImpute

Missing Value Imputations by RRF
combine

Combine Ensembles of Trees
rrfNews

Show the NEWS file
margin

Margins of RRF Classifier
na.roughfix

Rough Imputation of Missing Values
varImpPlot

Variable Importance Plot
tuneRRF

Tune RRF for the optimal mtry parameter
importance

Extract variable importance measure
treesize

Size of trees in an ensemble
imports85

The Automobile Data
rrfcv

Random Forest Cross-Valdidation for feature selection
getTree

Extract a single tree from a forest.