Classification rule mining based on particle swarm optimization

Authors:
Ziqiang Wang;Xia Sun;Dexian Zhang
Affiliations:
School of Information Science and Engineering, Henan University of Technology, Zheng Zhou, China;School of Information Science and Engineering, Henan University of Technology, Zheng Zhou, China;School of Information Science and Engineering, Henan University of Technology, Zheng Zhou, China
Venue:
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Year:
2006

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Abstract

The Particle Swarm Optimization(PSO) algorithm,is a robust stochastic evolutionary algorithm based on the movement and intelligence of swarms. In this paper, a PSO-based algorithm for classification rule mining is presented. Compared with the Ant-Miner and ESIA in public domain data sets,the proposed method achieved higher predictive accuracy and much smaller rule list than Ant-Miner and ESIA