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AuthorEl Chakik, Fadi
AuthorShahine, Ahmad
AuthorJaam, Jihad
AuthorHasnah, Ahmad
Available date2009-12-30T07:52:26Z
Publication Date2003-06-20
Publication NameInformation Sciences
Identifierhttp://dx.doi.org/10.1016/j.ins.2003.06.011
CitationFadi El Chakik, Ahmad Shahine, Jihad Jaam, Ahmad Hasnah, An approach for constructing complex discriminating surfaces based on Bayesian interference of the maximum entropy, Information Sciences, Volume 163, Issue 4, 18 June 2004, Pages 275-291
URIhttp://hdl.handle.net/10576/10584
AbstractIn this paper we present a comprehensive Maximum Entropy (MaxEnt) procedure for the classification tasks. This MaxEnt is applied successfully to the problem of estimating the probability distribution function (pdf) of a class with a specific pattern, which is viewed as a probabilistic model handling the classification task. We propose an efficient algorithm allowing to construct a non-linear discriminating surfaces using the MaxEnt procedure. The experiments that we carried out shows the performance and the various advantages of our approach.
Languageen
PublisherElsevier Inc.
SubjectMaximum entropy
Classification
Probability estimation
Neural networks
Hebbian learning
TitleAn approach for constructing complex discriminating surfaces based on Bayesian interference of the maximum entropy
TypeArticle
dc.accessType Abstract Only


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