JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2015, Vol. 45 ›› Issue (2): 1-9.doi: 10.6040/j.issn.1672-3961.1.2014.095

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A clustering ensemble algorithm based on co-evolution

DONG Hongbin, ZHANG Guangjiang, PANG Jinwei, HAN Qilong   

  1. College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, Heilongjiang, China
  • Received:2014-03-26 Revised:2015-03-17 Online:2015-04-20 Published:2014-03-26

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Abstract: Since clustering could not solve the problem of generalization, the integration technology was introduced into clustering algorithm, which could significantly improve the generalization ability of learning systems. A co-evolutionary clustering ensemble algorithm based on particle swarm optimization and genetic algorithm (CEGPCE) was proposed. PSO (particle swarm optimization) ensured the algorithm with fast convergence, and GA (genetic algorithm) expanded the search scope with its global search capability, which improved the performance of the algorithm and the convergence speed. Experiments on the UCI data sets verified the effectiveness of CEGPCE.

Key words: particle swarm optimization, genetic algorithm, co-evolutionary clustering ensemble, clustering, clustering ensemble, co-evolution

CLC Number: 

  • TP18
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