The bayes-optimal feature extraction procedure for pattern recognition using genetic algorithm

Authors:
Marek Kurzynski;Edward Puchala;Aleksander Rewak
Affiliations:
Faculty of Electronics, Chair of Systems and Computer Networks, Wroclaw University of Technology, Wroclaw, Poland;Faculty of Electronics, Chair of Systems and Computer Networks, Wroclaw University of Technology, Wroclaw, Poland;Faculty of Electronics, Chair of Systems and Computer Networks, Wroclaw University of Technology, Wroclaw, Poland
Venue:
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Year:
2006

Citing 9
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Abstract

The paper deals with the extraction of features for statistical pattern recognition. Bayes probability of correct classification is adopted as the extraction criterion. The problem with complete probabilistic information is discussed and Bayes-optimal feature extraction procedure is presented in detail. The case of recognition with learning is also considered. As method of solution of optimal feature extraction a genetic algorithm is proposed. A numerical example demonstrating capability of proposed approach to solve feature extraction problem is presented.