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dc.contributor.authorMadden, Michael G.en
dc.date.accessioned2009-06-10T14:42:56Zen
dc.date.available2009-06-10T14:42:56Zen
dc.date.issued2009en
dc.identifier.citationOn the Classification Performance of TAN and General Bayesian Networks , Michael G. Madden. Knowledge Based Systems, 2009.en
dc.identifier.urihttp://hdl.handle.net/10379/216en
dc.description.abstractOver a decade ago, Friedman et al. introduced the Tree Augmented Naïve Bayes (TAN) classifier, with experiments indicating that it significantly outperformed Naïve Bayes (NB) in terms of classification accuracy, whereas general Bayesian network (GBN) classifiers performed no better than NB. This paper challenges those claims, using a careful experimental analysis to show that GBN classifiers significantly outperform NB on datasets analyzed, and are comparable to TAN performance. It is found that the poor performance reported by Friedman et al. are not attributable to the GBN per se, but rather to their use of simple empirical frequencies to estimate GBN parameters, whereas basic parameter smoothing (used in their TAN analyses but not their GBN analyses) improves GBN performance significantly. It is concluded that, while GBN classifiers may have some limitations, they deserve greater attention, particularly in domains where insight into classification decisions, as well as good accuracy, is required.en
dc.formatapplication/pdfen
dc.language.isoenen
dc.publisherElsevieren
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Ireland
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/ie/
dc.subjectBayesian networks and classificationen
dc.subjectTree augmented naive Bays classifier (TAN)en
dc.subjectNaive Bays (NB)en
dc.subjectGeneral Bayesian Networks (GBN)en
dc.subject.lcshNeural networks (Computer science)en
dc.subject.lcshBayesian statistical decision theory -- Data processingen
dc.titleOn the Classification Performance of TAN and General Bayesian Networksen
dc.typeArticleen
dc.identifier.doi10.1016/j.knosys.2008.10.006en
dc.local.publisherstatementwww.elsevier.com/locate/knosysen
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