mRFE

The goal of mRFE is to provide a package for mSVM-RFE: (multiple) Support Vector Machine Recursive Feature Elimination

This repository contains an R implementation of the mSVM-RFE algorithm (Duan et al., 2005), including the option to cut the features by half each round (instead of one-by-one) if there are many features.

Also included are tools for wrapping the feature ranking/selection process in an external layer of cross-validation for obtaining unbiased estimates of generalization error/accuracy (See Ambroise et al., 2002).

Installation

You can install the development version of mRFE from GitHub with:

# install.packages("devtools")
devtools::install_github("llrs/SVM-RFE")

Example

This is a basic example which shows you how to solve a common problem:

library(mRFE)
#> Loading required package: e1071
## basic example code

References

Please use citation(mRFE) to cite the original work:

SVM-RFE

An iterative algorithm that works backward from an initial set of features. At each round it 1. fits a simple linear SVM, 2. ranks the features based on their weights in the SVM solution, and 3. eliminates the feature with the lowest weight.

Multiple SVM-RFE

Extends this idea by using resampling techniques at each iteration to stabilize the feature rankings. Here we use cross validation. The mSVM-RFE paper is: