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. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Kurzynski, M., Puchala, E., & Rewak, A. (2006). The Bayes-optimal feature extraction procedure for pattern recognition using genetic algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4131 LNCS-I, pp. 21–30). Springer Verlag. https://doi.org/10.1007/11840817_3
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