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randomForestSRC (version 2.4.1)

Random Forests for Survival, Regression and Classification (RF-SRC)

Description

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. The package runs in both serial and parallel (OpenMP) modes. Now extended to include multivariate and unsupervised forests.

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Version

Install

install.packages('randomForestSRC')

Monthly Downloads

6,551

Version

2.4.1

License

GPL (>= 3)

Maintainer

Udaya Kogalur

Last Published

November 6th, 2016

Functions in randomForestSRC (2.4.1)

find.interaction

Find Interactions Between Pairs of Variables
pbc

Primary Biliary Cirrhosis (PBC) Data
follic

Follicular Cell Lymphoma
impute.rfsrc

Impute Only Mode
nutrigenomic

Nutrigenomic Study
partial.rfsrc

Acquire Partial Effect of a Variable
hd

Hodgkin's Disease
max.subtree

Acquire Maximal Subtree Information
breast

Wisconsin Prognostic Breast Cancer Data
plot.competing.risk

Plots for Competing Risks
stat.split

Acquire Split Statistic Information
plot.rfsrc

Plot Error Rate and Variable Importance from a RF-SRC analysis
print.rfsrc

Print Summary Output of a RF-SRC Analysis
randomForestSRC-package

Random Forests for Survival, Regression and Classification (RF-SRC)
plot.survival

Plot of Survival Estimates
rf2rfz

Save RF-SRC in .rfz Compressed Format
rfsrcSyn

Synthetic Random Forests
rfsrc.news

Show the NEWS file
predict.rfsrc

Prediction for Random Forests for Survival, Regression, and Classification
rfsrc

Random Forests for Survival, Regression and Classification (RF-SRC)
wihs

Women's Interagency HIV Study (WIHS)
vdv

van de Vijver Microarray Breast Cancer
var.select

Variable Selection
veteran

Veteran's Administration Lung Cancer Trial
vimp

VIMP for Single or Grouped Variables