Particle swarm clustering ensemble

  • Authors:

  • Abbas Ahmadi;Fakhri Karray;Mohamed Kamel

  • Affiliations:

  • University of Waterloo, Waterloo, ON, Canada;University of Waterloo , Waterloo, ON, Canada;University of Waterloo, Waterloo, ON, Canada

  • Venue:
  • Proceedings of the 10th annual conference on Genetic and evolutionary computation
  • Year:
  • 2008

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Abstract

Extracting natural groups of the unlabeled data is known as clustering. To improve the stability and robustness of the clustering outputs, clustering ensembles have emerged recently. In this paper, an ensemble of particle swarm clustering algorithms is proposed. That is, the members of the ensemble are based on the cooperative swarms clustering approaches. The performance of the proposed particle swarm clustering ensemble is evaluated using di®erent data sets and is compared to that of other clustering techniques.