iterative Random Forests (iRF)

The R package iRF implements iterative Random Forests, a method for iteratively growing ensemble of weighted decision trees, and detecting high-order feature interactions by analyzing feature usage on decision paths. This version uses source codes from the R package randomForest by Andy Liaw and Matthew Weiner and the original Fortran codes by Leo Breiman and Adele Cutler.

Installation

To install iRF from CRAN:

install.packages('iRF')

To install the development version from GitHub:

install.packages('devtools')
devtools::install_github("sumbose/iRF")

You can subsequently load the package with the usual R commands:

library(iRF)

This package requires gfortran to compile. OSX users may need to intall gfortran available here. For details on usage, see our vignette.

Contribute

To contribute to this project, please review the guidelines. This project is released with a contributor code of conduct. By participating in this project you agree to abide by its terms.