Pairwise Naive Bayes Classifier
Jan-Nikolas Sulzmann · HilDok – Institutional Repository (Universität Hildesheim) · 2006
Class binarizations are effective methods that break multi-class problem down into several 2-class or binary problems to improve weak learners. This paper analyzes which effects these methods have if we choose a Naive Bayes learner for the base classifier. We consider the known unordered and pairwise class binarizations and propose an alternative approach for a pairwise calculation of a modified Naive Bayes classifier.