An approach for constructing complex discriminating surfaces based on Bayesian interference of the maximum entropy

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Author El Chakik, Fadi en_US
Author Shahine, Ahmad en_US
Author Jaam, Jihad en_US
Author Hasnah, Ahmad en_US
Available date 2009-12-30T07:52:26Z en_US
Publication Date 2003-06-20 en_US
Citation Fadi 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 en_US
URI http://dx.doi.org/10.1016/j.ins.2003.06.011 en_US
URI http://hdl.handle.net/10576/10584 en_US
Abstract In 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. en_US
Language en en_US
Publisher Elsevier Inc. en
Subject Maximum entropy en_US
Subject Classification en_US
Subject Probability estimation en_US
Subject Neural networks en_US
Subject Hebbian learning en_US
Title An approach for constructing complex discriminating surfaces based on Bayesian interference of the maximum entropy en_US
Type Article en_US


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