Immunity-based genetic algorithm for classification rule discovery

Authors:
Ziqiang Wang;Dexian Zhang
Affiliations:
School of Information Science and Engineering, Henan University of Technology, Zheng Zhou, P.R. China;School of Information Science and Engineering, Henan University of Technology, Zheng Zhou, P.R. China
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Year:
2005

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Abstract

Immune algorithm is a global optimal algorithms based on the biological immune theory. In this paper, a novel immune algorithm is proposed for classification rule discovery. The idea of immunity is mainly realized through two steps based on reasonably selecting vaccines, i.e., a vaccination and an immune selection. Experimental results show that immune algorithm performs better than RISE with respect to predictive accuracy and rule list mined simplicity.