A unified treatment of Breiman's random forests for survival, regression and classification problems based on Ishwaran and Kogalur's random survival forests (RSF) package. Now extended to include multivariate and unsupervised forests. Also includes quantile regression forests for univariate and multivariate training/testing settings. The package runs in both serial and parallel (OpenMP) modes.

Documentation

Manual: randomForestSRC.pdf
Vignette: None available.

Maintainer: Udaya B. Kogalur <ubk at kogalur.com>

Author(s): Hemant Ishwaran <hemant.ishwaran at gmail.com>, Udaya B. Kogalur <ubk at kogalur.com>

Install package and any missing dependencies by running this line in your R console:

install.packages("randomForestSRC")

Depends R (>= 3.1.0),
Imports parallel
Suggests glmnet, survival, pec, prodlim, mlbench
Enhances
Linking to
Reverse
depends
ggRandomForests
Reverse
imports
boostmtree, fifer, sprinter, SurvRank
Reverse
suggests
CFC, edarf, IPMRF, mlr, ModelGood, pec, pmml, riskRegression, RLT
Reverse
enhances
Reverse
linking to

Package randomForestSRC
Materials
URL http://web.ccs.miami.edu/~hishwaran http://www.kogalur.com https://github.com/kogalur/randomForestSRC
Task Views HighPerformanceComputing , MachineLearning , Survival
Version 2.5.1
Published 2017-10-17
License GPL (>= 3)
BugReports https://github.com/kogalur/randomForestSRC/issues/new
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks randomForestSRC check results
Package source randomForestSRC_2.5.1.tar.gz