How does rapdiminer decision tree (the basic one) AUC being calculated? For example, I have a dataset with only 1 parameter, and then I use 10 fold cross validation. The "performance" operator gives me AUCs (Optimistic, pessimistic, general), how did it generate? (I am guessing something like this: rapidminer try different cut-off for the single variable and determine the AUC?)
Also, what's the difference among optimistic, pessimistic, and general ?
Thanks a lot!