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> # Creating dummy dat> set.seed(123)> mydata = data.frame(y= ifelse(sign(rnorm(100))==-1,0,1),+ x1= sample(LETTERS[1:5],100,replace = TRUE),+                     x2= factor(sample(1:7, 100, replace = TRUE)))

> # Convert categorical variables to continuous variables> TransformCateg <- function(y,x,inputdata,cutoff){+ for (i in seq(1,length(x),1)) {+ if (class(inputdata[,x[i]]) %in% c("factor", "character")){+ len <- NULL+ t1 <- aggregate(inputdata[,y], list(inputdata[,x[i]]), mean)+ names(t1)[2] <- "avg"+ t2 <- aggregate(inputdata[,y], list(inputdata[,x[i]]), length)+ names(t2)[2] <- "len"+ temp <- merge(t1, t2, by = "Group.1")+ t1 <- subset(temp, len >= cutoff)+ t2 <- subset(temp, len < cutoff)+ if(nrow(t2) > 0)+ {+ t2$avg <- sum(t2$avg*t2$len)/sum(t2$len)+ t2$len <- sum(t2$len)+ }+ temp <- rbind(t1, t2)+ inputdata <- merge(inputdata, temp, by.x = x[i], by.y = "Group.1", all.x = T)+ inputdata[,paste(x[i],"mean", sep="_")] <- ((inputdata$avg * inputdata$len) - (inputdata[,y]))/(inputdata$len - 1)+ inputdata <- inputdata[, !(colnames(inputdata) %in% c("avg","len"))]+ }+ else{+ warning(paste(x[i], " is not a factor or character variable", sep = ""))+ }+ }+ return(inputdata)+ }

> # Run Function> train2 = TransformCateg(y= "y",x= c("x1","x2"), inputdata = mydata, cutoff = 15)