Weighted Cluster Ensemble Using a Kernel Consensus Function

  • Sandro Vega-Pons
  • Jyrko Correa-Morris
  • José Ruiz-Shulcloper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5197)


Cluster ensemble is a good alternative to face the problem of data clustering. Some studies based on mathematical models have shown that cluster ensemble methods lead to an effective improvement of the results of the standard clustering algorithms. In this paper, we focus on this problem, proposing a new approach to solve it, by adding a new step into the usual cluster ensemble methodology. Representing partitions by graphs and a new kernel function to measure the similarity between partitions are other proposals for this work. Experiments with synthetic and real databases show the suitability and effectiveness of our method.


cluster ensemble graph kernel consensus function 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Sandro Vega-Pons
    • 1
  • Jyrko Correa-Morris
    • 1
  • José Ruiz-Shulcloper
    • 1
  1. 1.Advanced Technologies Application CenterHavanaCuba

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