Code to reproduce https://mbq.me/blog/relevance-and-redundancy/

relevance-and-redundancy.R

setNames(
 do.call(expand.grid,rep(list(c(T,F)),5)),
 c("A","B","N1","N2","N3")
)->X
cbind(X,AoB=with(X,A|B),AnB=with(X,A&B),nA=!X$A)->X
factor(with(X,A!=B))->Y
data.frame(lapply(X,factor))->X

greedySVM<-function(X,Y,sel=names(X),err=Inf){
 #Empty selection is not interesting
 if(length(sel)==0) return(NULL)

 #Try proposed selection
 cerr<-try(kernlab::ksvm(Y~.,X[,sel,drop=FALSE],cross=5)@cross)

 #Cross-validation may fail
 if(inherits(cerr,"try-error")) return(NULL)
 
 #Error increase, not good
 if(cerr>err) return(NULL)
 
 #It is not worse, but maybe can be even better?
 for(remove in seq(along=sel))
  if(!is.null(ans<-greedySVM(X,Y,sel[-remove],cerr)))
   return(ans)

 #Current solution is an optimum 
 return(paste(sort(sel),collapse="+"))
}

permuteGreedySVM<-function(X,Y,tries=100){
 unlist(parallel::mclapply(1:tries,
  function(.) greedySVM(X[,sample(ncol(X))],Y),
  mc.cores=parallel::detectCores()
 ))->sels
 sort(table(sels)/length(sels),dec=TRUE)
}