R implementation of SVM-RFE from literature

svm-rfe.R

svmrfeFeatureRanking = function(x,y){ 
	n = ncol(x)
	survivingFeaturesIndexes = seq(1:n) 
	featureRankedList = vector(length=n) 
	rankedFeatureIndex = n

	while(length(survivingFeaturesIndexes)>0){ 

		#train the support vector machine 
		svmModel = svm(x[, survivingFeaturesIndexes], y, cost = 10, cachesize=500,scale=F, type="C-classification", kernel="linear" )	

		#compute the weight vector 
		w = t(svmModel$coefs)%*%svmModel$SV

		#compute ranking criteria 
		rankingCriteria = w * w

		#rank the features 
		ranking = sort(rankingCriteria, index.return = TRUE)$ix
		
		#update feature ranked list 
		featureRankedList[rankedFeatureIndex] = survivingFeaturesIndexes[ranking[1]] 
		rankedFeatureIndex = rankedFeatureIndex - 1
		
		#eliminate the feature with smallest ranking criterion 
		(survivingFeaturesIndexes = survivingFeaturesIndexes[-ranking[1]])
	} 

	return (featureRankedList)
}