Reduced error pruning

Hello,

In the Decision Tree Learner node, there is an option for Reduced Error Pruning (REP). As I understand it, REP is a post-pruning technique which evaluates the change in misclassification error by systematically creating sub-trees. The literature on REP indicates that a separate data set (sometimes called a pruning set) is used to evaluate misclassification error for every subtree. I have not been able to find how the KNIME Decision Tree Learner creates the pruning set or sets. Any help would be appreciated.

Thanks.

Frank