Learn R Programming

⚠️There's a newer version (3.3.3) of this package.Take me there.

randomForestSRC (version 2.9.3)

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.

Copy Link

Version

Install

install.packages('randomForestSRC')

Monthly Downloads

5,081

Version

2.9.3

License

GPL (>= 3)

Issues

Pull Requests

Stars

Forks

Repository

http://web.ccs.miami.edu/~hishwaran http://www.kogalur.com https://github.com/kogalur/randomForestSRC

Maintainer

Udaya Kogalur

Last Published

January 21st, 2020

Functions in randomForestSRC (2.9.3)

Hodgkin's Disease

imbalanced.rfsrc

Imbalanced Two Class Problems

holdout.vimp.rfsrc

Hold out variable importance (VIMP)

Ames Iowa Housing Data

find.interaction.rfsrc

Find Interactions Between Pairs of Variables

Follicular Cell Lymphoma

Wisconsin Prognostic Breast Cancer Data

max.subtree.rfsrc

Acquire Maximal Subtree Information

Impute Only Mode

Nutrigenomic Study

Acquire Partial Effect of a Variable

Primary Biliary Cirrhosis (PBC) Data

plot.variable.rfsrc

Plot Marginal Effect of Variables

plot.survival.rfsrc

Plot of Survival Estimates

plot.quantreg.rfsrc

Plot Quantiles from Quantile Regression Forests

plot.competing.risk.rfsrc

Plots for Competing Risks

plot.subsample.rfsrc

Plot Subsampled VIMP Confidence Intervals

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

Print Summary Output of a RF-SRC Analysis

Prediction for Random Forests for Survival, Regression, and Classification

Show the NEWS file

stat.split.rfsrc

Acquire Split Statistic Information

Tune Random Forest for the optimal mtry and nodesize parameters

subsample.rfsrc

Subsample Forests for VIMP Confidence Intervals

var.select.rfsrc

Variable Selection

Synthetic Random Forests

Veteran's Administration Lung Cancer Trial

randomForestSRC-package

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

van de Vijver Microarray Breast Cancer

Quantile Regression Forests

White Wine Quality Data

VIMP for Single or Grouped Variables

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

Fast Random Forests

Women's Interagency HIV Study (WIHS)