Mining Class Association Rules with Artificial Immune System

Do, T. D., Hui, S. C. and Fong, A. C.M. (2005) Mining Class Association Rules with Artificial Immune System. In: International Conference on Knowledge- Based Intelligent Information and Engineering Systems, Melbourne, Australia, 14-16 Sept 2005, pp. 94-100. (doi: 10.1007/11554028_14)

Abstract

Associative classification, which is based on association rules, has shown great promise over many other classification techniques. However, the very large search space of possible rules may cause performance degradation in the rule mining process as well as classification accuracy. In this paper, we propose a new approach known as AIS-AC, which is based on Artificial Immune System (AIS), for mining class association rules for associative classification. Instead of massively searching for all possible association rules, AIS-AC will only find a subset of association rules that are suitable for effective associative classification in an evolutionary manner.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Fong, Dr Alvis Cheuk Min
• Authors: Do, T. D., Hui, S. C., and Fong, A. C.M.
• College/School: College of Science and Engineering > School of Computing Science
• ISSN: 0302-9743