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Classification algorithm based on human social behavior
Author(s)
Moolwong, Jittraporn
Date Issued
December 1, 2007
Type
Conference Paper
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.
Citation
CIT 2007 7th IEEE International Conference on Computer and Information Technology, 105-109, 2007
