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On the Performance of Approximations of Bayesian Networks in Model-
Linköping University, The Institute of Technology. Linköping University, Department of Mathematics, Mathematical Statistics .
Linköping University, The Institute of Technology. Linköping University, Department of Mathematics, Mathematical Statistics .
2006 (English)In: The Annual Workshop of the Swedish Artificial Intelligence Society,2006, Umeå: SAIS , 2006, 73- p.Conference paper, Published paper (Refereed)
Abstract [en]

When the true class conditional model and class probabilities are approximated in a pattern recognition/classification problem the performance of the optimal classifier is expected to deteriorate. But calculating this reduction is far from trivial in the general case. We present one generalization, and easily computable formulas for estimating the degradation in performance with respect to the optimal classifier. An example of an approximation is the Naive Bayes classifier. We generalize and sharpen results for evaluating this classifier.

Place, publisher, year, edition, pages
Umeå: SAIS , 2006. 73- p.
Keyword [en]
Plug-in classifiers, Naive Bayes
National Category
Mathematics
Identifiers
URN: urn:nbn:se:liu:diva-34261Local ID: 21109OAI: oai:DiVA.org:liu-34261DiVA: diva2:255109
Available from: 2009-10-10 Created: 2009-10-10

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http://sais2006.cs.umu.se/proceedings/

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Ekdahl, MagnusKoski, Timo

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CiteExportLink to record
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