README.md

In iRF: iterative Random Forests

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

library(devtools)
devtools::install_github("sumbose/iRF")

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

library(iRF)

OSX users may need to intall gfortran to compile. This 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 are available for OSX and linux in the binaries directory and can be installed using the command:

R CMD INSTALL <filename>

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

iRF documentation built on May 2, 2019, 11:02 a.m.