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Pairwise Naive Bayes Classifier

  • 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.

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Metadaten
Author:Jan-Nikolas Sulzmann
URN:https://nbn-resolving.org/urn:nbn:de:gbv:hil2-opus-685
Document Type:Conference Proceeding
Language:English
Date of Publication (online):2011/05/06
Contributing Corporation:Technische Universität Darmstadt
Release Date:2011/05/06
Tag:clustering; data mining; k-means; law-enforcement; semi-supervised learning
Source:LWA 2006: Lernen - Wissensentdeckung - Adaptivität, Hildesheim, 9. - 11. Oktober 2006
PPN:Link zum Katalog
Contributor:Althoff, Klaus-Dieter
Institutes:Fachbereich IV / Informatik
DDC classes:000 Allgemeines, Informatik, Informationswissenschaft / 000 Allgemeines, Wissenschaft / 004 Informatik
Licence (German):License LogoDeutsches Urheberrecht