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.

To download and install the package, use devtools

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

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

library(iRF)

For a detailed description on the usage of iRF, see the vignette.

System requirements

This package requires C++11 and R (>= 3.1.2). OSX users may need to install gfortran to compile, which can be done with the following commands:

curl -O http://r.research.att.com/libs/gfortran-4.8.2-darwin13.tar.bz2
sudo tar fvxz gfortran-4.8.2-darwin13.tar.bz2 -C /

Binaries

Pre-compiled binaries are available for OSX and linux in the binaries directory and can be installed using the command:

R CMD INSTALL <filename>