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randomForestSRC (version 2.11.0)

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

Description

Fast OpenMP parallel computing of Breiman's random forests for univariate, multivariate, unsupervised, survival, competing risks, class imbalanced classification and quantile regression. Extreme random forests and randomized splitting. Suite of imputation methods for missing data. Fast random forests using subsampling. Confidence regions and standard errors for variable importance. New improved holdout importance. Case-specific importance. Visualize trees on your Safari or Google Chrome browser. Anonymous random forests for data privacy.

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Version

Install

install.packages('randomForestSRC')

Monthly Downloads

6,551

Version

2.11.0

License

GPL (>= 3)

Issues

Pull Requests

Stars

Forks

Repository

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

Maintainer

Udaya Kogalur

Last Published

March 31st, 2021

Functions in randomForestSRC (2.11.0)

Impute Only Mode

find.interaction.rfsrc

Find Interactions Between Pairs of Variables

Extract a Single Tree from a Forest and plot it on your browser

Hodgkin's Disease

Wisconsin Prognostic Breast Cancer Data

max.subtree.rfsrc

Acquire Maximal Subtree Information

Ames Iowa Housing Data

imbalanced.rfsrc

Imbalanced Two Class Problems

Follicular Cell Lymphoma

plot.subsample.rfsrc

Plot Subsampled VIMP Confidence Intervals

holdout.vimp.rfsrc

Hold out variable importance (VIMP)

Acquire Partial Effect of a Variable

plot.quantreg.rfsrc

Plot Quantiles from Quantile Regression Forests

Nutrigenomic Study

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

plot.variable.rfsrc

Plot Marginal Effect of Variables

Prediction for Random Forests for Survival, Regression, and Classification

Show the NEWS file

sidClustering.rfsrc

sidClustering using SID (Staggered Interaction Data) for Unsupervised Clustering

Print Summary Output of a RF-SRC Analysis

Veteran's Administration Lung Cancer Trial

Quantile Regression Forests

VIMP for Single or Grouped Variables

van de Vijver Microarray Breast Cancer

plot.survival.rfsrc

Plot of Survival Estimates

var.select.rfsrc

Variable Selection

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

stat.split.rfsrc

Acquire Split Statistic Information

randomForestSRC-package

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

subsample.rfsrc

Subsample Forests for VIMP Confidence Intervals

White Wine Quality Data

Primary Biliary Cirrhosis (PBC) Data

Women's Interagency HIV Study (WIHS)

plot.competing.risk.rfsrc

Plots for Competing Risks

rfsrc.anonymous

Anonymous Random Forests

Synthetic Random Forests

Fast Random Forests

Tune Random Forest for the optimal mtry and nodesize parameters