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randomForestSRC (version 2.6.0)

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

6,551

Version

2.6.0

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

May 2nd, 2018

Functions in randomForestSRC (2.6.0)

Plot Marginal Effect of Variables

randomForestSRC-package

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

Plot of Survival Estimates

Synthetic Random Forests

Acquire Split Statistic Information

Veteran's Administration Lung Cancer Trial

van de Vijver Microarray Breast Cancer

Women's Interagency HIV Study (WIHS)

VIMP for Single or Grouped Variables

Prediction for Random Forests for Survival, Regression, and Classification

Variable Selection

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

Primary Biliary Cirrhosis (PBC) Data

Follicular Cell Lymphoma

find.interaction

Find Interactions Between Pairs of Variables

Acquire Maximal Subtree Information

Nutrigenomic Study

Wisconsin Prognostic Breast Cancer Data

Hodgkin's Disease

Acquire Partial Effect of a Variable

plot.competing.risk

Plots for Competing Risks

Impute Only Mode

Show the NEWS file

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

Print Summary Output of a RF-SRC Analysis

Quantile Regression Forests