# CART with Ordinal Response Variable using rpartScore Stuck

I'm trying to fit a decision tree over some data which has ~40K rows and ~200 features. The response variable, y, is ordinal and takes values {1,2,3} or {1,2,3,4} depending on the problem definition.

If I treat y as a categorical/factor variable, the response time for the training CART (using the rpart package) and testing (80/20 split) takes 20-30 seconds.

However, as soon as I try to use the rpartScore package in R and frame y as ordinal, the training doesn't complete even after close to 30-40 minutes.

I'm not very familiar with CART and the implementations here. I'm looking for hints to understand theoretically why this could be the case.

Resources for ordinal CARTs would be helpful. Especially an analysis of convergence-related issues.

• Just wondering if this belongs on Stack Overflow. – Placidia Aug 13 '15 at 1:15
• @Placidia I'm not sure what the logic is. :) I want to know theoretically if there are problems with convergence and things of the like. I can't get rpartScore to work but rpart works as expected. – Navneet Aug 13 '15 at 1:50
• @Navneet why don't you simply stick to rpart, if it works? – Antoine Aug 19 '15 at 18:23
• @Antoine I need to order the response classes. rpart is nominal as far as I know. Please correct me if I'm wrong. :) – Navneet Aug 19 '15 at 18:58
• For that sort of question you ought to present the data and the syntax. So that people have a chance to try to reproduce your results/error. Otherwise how is it possible to test it all? – ttnphns Aug 20 '15 at 8:51