Convert R data structures to text files for VW, FM, LIBSVM

RML.R

write.libsvm = function(data, filename= "out.dat", class = 1) { 
  out = file(filename) 
  writeLines(apply(data, 1, function(X) paste(X[class],apply(cbind(which(X!=0)[-class], X[which(X!=0)[-class]]), 1, paste, collapse=":"), collapse=" ") ), out) 
  close(out) 
}

#' x should be a model matrix
#' y is a response vector
write.vw = function(data, outcomeName, weightName = '', classification=F, file = 'vw.txt') {
  
  objDF <- data
  predictors <- names(objDF)[!names(objDF) %in% c(outcomeName, weightName)]
  
  # LABELS & IMPORTANCE
  if (classification) {
    # everything should be -1,1 for classification
    objDF[,outcomeName] <- ifelse(objDF[,outcomeName]>0,1,-1)
  }
  
  if (weightName != '')
    objDF[,outcomeName] <- paste(objDF[,outcomeName], objDF[,weightName], "|")
  else
    objDF[,outcomeName] <- paste(objDF[,outcomeName], "|")
  
  
  # Pairing column names with data... adding 1 blank character before each variable
  for (i in predictors) {
    objDF[,i] <- ifelse(objDF[,i]==1,paste0(' ',i),
                        ifelse(objDF[,i]==0,'',paste0(' ', i,':', objDF[,i])))
  }
  
  # reorder columns so that label (outcome) is first followed by predictors     
  objDF <- objDF[c(outcomeName, predictors)]
  
  write.table(objDF, file, sep="", quote = F, row.names = F,  col.names = F)
}

write.fm = function(data, filename= "out.dat", class = 1)
  write.libsvm(data, filename, class)
}