Solved – Decision tree more than 2 output levels

Question

I have a classification problem where my dependent variable has 3 possible values. They are ordered variables.

I have been using trees and random forests in R to tackle this problem, but have to convert the problem into a binary one, so i'm predicting if the dependent variable is or isn't 1, then is or isn't 2, then is or isn't 3 in 3 different models.

Can I build a random forest or decision tree with an ordinal variable as the dependent variable?

Are there any better ways I should be approaching this problem?

Thanks

Answer 1

I know that randomForest in R, at least, will handle 3 level categorical variables just fine. You could also do 1 vs other and 2 vs 3; you'd only need 2 models. But I'm not sure if this makes a difference.