Classification algorithm based on human social behavior

Abstract

This paper proposes the new approach to deal with the classification problems by employing the sociological concept of "in-group" and "out-group." The main idea of the concept is about the behavior of in-group members that try to unite with their own group as much as possible, and at the same time maintain social distance from the out-group members. The performance of the proposed model was compared with the fuzzy ARTMAP neural network. The results on five benchmark problems are very encouraging. © 2007 IEEE.