Stacking

RapidMiner supports Meta Learning by embedding one or several basic learners as children into a parent meta learning operator. Here, we use a three base learners inside the stacking operator: decision tree induction, linear regression, and a nearest neighbours classifier. Finally, a Naive Bayes learner is used as a stacking learner which uses the predictions of the preceeding three learners to make a combined prediction.