greedy.select <- function(data,classes,N=3,k=1)
{
	require(class)
	variates <- NULL
	best.perf <- nrow(data)
	num <- 0
	k <- 1
	cat(date(),"\n")
	for(j in 1:ncol(data)){
		ind <- 0
		best <- nrow(data)
		for(i in setdiff(1:ncol(data),variates)){
			a <- knn.cv(data[,c(variates,i)],classes,k=k)
			perf <- sum(a != classes)
			if(perf<best){
				ind <- i
				best <- perf
			}
		}
		if(best == best.perf){
			num <- num+1
			if(num>=N) break
			variates <- c(variates,ind)
			best.perf <- best
		}
		else if(best < best.perf){
			variates <- c(variates,ind)
			best.perf <- best
			num <- 0
		}
		else break
		cat(date(),j,best.perf,num,"\n")
	}
   variates
}