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randomForestSRC (version 2.9.1)

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

Description

Fast OpenMP parallel computing of Breiman's random forests for survival, competing risks, regression and classification based on Ishwaran and Kogalur's popular random survival forests (RSF) package. Handles missing data and now includes multivariate, unsupervised forests, quantile regression and solutions for class imbalanced data. New fast interface using subsampling and confidence regions for variable importance.

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Version

Install

install.packages('randomForestSRC')

Monthly Downloads

5,081

Version

2.9.1

License

GPL (>= 3)

Issues

37

Pull Requests

0

Stars

126

Forks

19

Maintainer

Udaya Kogalur

Last Published

July 8th, 2019

Functions in randomForestSRC (2.9.1)

follic

Follicular Cell Lymphoma
hd

Hodgkin's Disease
breast

Wisconsin Prognostic Breast Cancer Data
max.subtree.rfsrc

Acquire Maximal Subtree Information
impute.rfsrc

Impute Only Mode
holdout.vimp.rfsrc

Hold out variable importance (VIMP)
nutrigenomic

Nutrigenomic Study
imbalanced.rfsrc

Imbalanced Two Class Problems
find.interaction.rfsrc

Find Interactions Between Pairs of Variables
housing

Ames Iowa Housing Data
plot.rfsrc

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

Plot Subsampled VIMP Confidence Intervals
pbc

Primary Biliary Cirrhosis (PBC) Data
partial.rfsrc

Acquire Partial Effect of a Variable
plot.survival.rfsrc

Plot of Survival Estimates
plot.variable.rfsrc

Plot Marginal Effect of Variables
predict.rfsrc

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

Print Summary Output of a RF-SRC Analysis
rfsrc.news

Show the NEWS file
plot.quantreg.rfsrc

Plot Quantiles from Quantile Regression Forests
plot.competing.risk.rfsrc

Plots for Competing Risks
tune.rfsrc

Tune Random Forest for the optimal mtry and nodesize parameters
var.select.rfsrc

Variable Selection
stat.split.rfsrc

Acquire Split Statistic Information
rfsrc.fast

Fast Random Forests
rfsrc

Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
subsample.rfsrc

Subsample Forests for VIMP Confidence Intervals
synthetic

Synthetic Random Forests
quantreg.rfsrc

Quantile Regression Forests
vimp.rfsrc

VIMP for Single or Grouped Variables
wihs

Women's Interagency HIV Study (WIHS)
randomForestSRC-package

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

White Wine Quality Data
vdv

van de Vijver Microarray Breast Cancer
veteran

Veteran's Administration Lung Cancer Trial