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randomForestSRC (version 2.5.0)

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. 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.

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Install

install.packages('randomForestSRC')

Monthly Downloads

7,355

Version

2.5.0

License

GPL (>= 3)

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Repository

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

Maintainer

Udaya Kogalur

Last Published

August 7th, 2017

Functions in randomForestSRC (2.5.0)

Follicular Cell Lymphoma

Hodgkin's Disease

Nutrigenomic Study

Acquire Partial Effect of a Variable

Impute Only Mode

Acquire Maximal Subtree Information

Primary Biliary Cirrhosis (PBC) Data

plot.competing.risk

Plots for Competing Risks

Wisconsin Prognostic Breast Cancer Data

find.interaction

Find Interactions Between Pairs of Variables

Print Summary Output of a RF-SRC Analysis

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

Plot Marginal Effect of Variables

Show the NEWS file

randomForestSRC-package

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

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

VIMP for Single or Grouped Variables

Women's Interagency HIV Study (WIHS)

Plot of Survival Estimates

Prediction for Random Forests for Survival, Regression, and Classification

van de Vijver Microarray Breast Cancer

Veteran's Administration Lung Cancer Trial

Quantile Regression Forests

Acquire Split Statistic Information

Variable Selection

Synthetic Random Forests