Parallelized Kernel Patch Clustering

  • Stefan Faußer
  • Friedhelm Schwenker
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5998)


Kernel based clustering methods allow to unsupervised partition samples in feature space but have a quadratic computation time O(n 2) where n are the number of samples. Therefore these methods are generally ineligible for large datasets. In this paper we propose a meta-algorithm that performs parallelized clusterings of subsets of the samples and merges them repeatedly. The algorithm is able to use many Kernel based clustering methods where we mainly emphasize on Kernel Fuzzy C-Means and Relational Neural Gas. We show that the computation time of this algorithm is basicly linear, i.e. O(n). Further we statistically evaluate the performance of this meta-algorithm on a real-life dataset, namely the Enron Emails.


  1. 1.
    Fahim, A.M., Salem, A.M., Torkey, F.A., Ramadan, M.A.: An efficient enhanced k-means clustering algorithm. Journal of Zhejiang University SCIENCE A, 1626–1633 (2006) ISSN 1009-3095Google Scholar
  2. 2.
    Ng, R.T., Han, J.: Efficient and Effective Clustering Methods for Spatial Data Mining. In: Proceedings of the 20th VLDB Conference, pp. 286–296. Morgan Kaufmann Publishers, San Francisco (1994)Google Scholar
  3. 3.
    Guha, S., Meyerson, A., Mishra, N., Motwani, R., O’Callaghan, L.: Clustering Data Streams: Theory and Practice. Proceedings of IEEE Transactions on Knowledge and Data Engineering 15(3), 515–528 (2003)CrossRefGoogle Scholar
  4. 4.
    Kantabutra, S., Couch, A.L.: Parallel K-means Clustering Algorithm on NOWs. NECTEC Technical Journal 1(6) (2000)Google Scholar
  5. 5.
    Alex, N., Hammer, B.: Parallelizing single patch pass clustering. In: ESANN 2008 (2008) ISBN 2-930307-08-0Google Scholar
  6. 6.
    Zhang, R., Rudnicky, A.I.: A Large Scale Clustering Scheme for Kernel K-Means. In: ICPR 2002, 16th International Conference on Pattern Recognition, vol. 4, p. 40289 (2002)Google Scholar
  7. 7.
    Hasenfuss, A., Hammer, B., Rossi, F.: Patch Relational Neural Gas Clustering of Huge Dissimilarity Datasets. In: Prevost, L., Marinai, S., Schwenker, F. (eds.) ANNPR 2008. LNCS (LNAI), vol. 5064, pp. 1–12. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  8. 8.
    Zhang, D.Q., Chen, S.C.: Fuzzy clustering using kernel methods. In: International Conference of Control and Automatation (ICCA 2002), Xiamen, China, pp. 123–128 (2002)Google Scholar
  9. 9.
    Hammer, B., Hasenfuss, A.: Relational Neural Gas. In: Hertzberg, J., Beetz, M., Englert, R. (eds.) KI 2007. LNCS (LNAI), vol. 4667, pp. 190–204. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  10. 10.
    Jebara, T., Kondor, R., Howard, A.: Probability Product Kernels. Journal of Machine Learning Research 5, 819–844 (2004)MathSciNetGoogle Scholar
  11. 11.
    Asuncion, A., Newman, D.J.: UCI Machine Learning Repository (2009),

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Stefan Faußer
    • 1
  • Friedhelm Schwenker
    • 1
  1. 1.Institute of Neural Information ProcessingUniversity of UlmUlmGermany

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