Iteratively grows feature weighted random forests and finds high-order feature interactions in a stable fashion.
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
To download and install the package, use
You can subsequently load the package with the usual R commands:
OSX users may need to intall gfortran to compile. This can be done with the following commands:
curl -Osudo 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
R CMD INSTALL <filename>
For a detailed description on the usage of
iRF, see the vignette.