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Pairwise Naive Bayes Classifier
Abstract
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.
Publication Type
ConferencePaper
Author
Sulzmann, Jan-Nikolas
Date Issued
2006
Faculty
Institute / Institution
Published in
LWA 2006 : Lernen – Wissensentdeckung – Adaptivität (9.–11.10.2006 in Hildesheim)
Conference
LWA 2006, Hildesheim, 09.10.-11.10.2006
Page Start
356
Page End
363
URN
urn:nbn:de:gbv:hil2-opus-685
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