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arXiv:cs/0202020 (cs)
[Submitted on 17 Feb 2002 (v1), last revised 24 Aug 2012 (this version, v3)]

Title:The Mysterious Optimality of Naive Bayes: Estimation of the Probability in the System of "Classifiers"

Authors:Oleg Kupervasser, Alexsander Vardy
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Abstract:Bayes Classifiers are widely used currently for recognition, identification and knowledge discovery. The fields of application are, for example, image processing, medicine, chemistry (QSAR). But by mysterious way the Naive Bayes Classifier usually gives a very nice and good presentation of a recognition. It can not be improved considerably by more complex models of Bayes Classifier. We demonstrate here a very nice and simple proof of the Naive Bayes Classifier optimality, that can explain this interesting this http URL derivation in the current paper is based on arXiv:cs/0202020v1
Comments: 9 pages,1 figure, all changes in the second version is made by Kupervasser only
Subjects: Computer Vision and Pattern Recognition (cs.CV); Artificial Intelligence (cs.AI)
ACM classes: E.5; E.4; E.2; H.1.1; F.1.1; F.1.3
Cite as: arXiv:cs/0202020 [cs.CV]
  (or arXiv:cs/0202020v3 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.cs/0202020
Journal reference: Pattern Recognition and Image Analysis, 2014, Vol. 24, No. 1
Related DOI: https://doi.org/10.1134/S1054661814010088

Submission history

From: Oleg Kupervasser [view email]
[v1] Sun, 17 Feb 2002 14:55:47 UTC (9 KB)
[v2] Thu, 30 Jun 2011 14:23:47 UTC (24 KB)
[v3] Fri, 24 Aug 2012 14:57:32 UTC (25 KB)
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