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

Authors:
Fadi El Chakik;Ahmad Shahine;Jihad Jaam;Ahmad Hasnah
Affiliations:
Centre University de Technologie, P.O. Box 732 Tripoli, Deddeh, Lebanon;Notre Dame University, P.O. Box 72, Zouk Mikael, Keserouan, Lebanon;Computer Science Department, University of Qatar, College of Science, P.O. Box 2713, Doha, Qatar,;Computer Science Department, University of Qatar, College of Science, P.O. Box 2713, Doha, Qatar,
Venue:
Information Sciences: an International Journal - Special issue: Information technology
Year:
2004

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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.