Advertisement

A Kernel Method for Classification

  • Donald MacDonald
  • Jos Koetsier
  • Emilio Corchado
  • Colin Fyfe
  • Juan Corchado
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2972)

Abstract

Kernel Maximum Likelihood Hebbian Learning Scale Invariant Maps is a novel technique developed to facilitate the clustering of complex data effectively and efficiently and that is characterised for converging remarkably quickly. The combination of Maximum Likelihood Hebbian Learning Scale Invariant Map and the Kernel Space provides a very smooth scale invariant quantisation which can be used as a clustering technique. The efficiency of this method have been used to analyse an oceanographic problem.

Keywords

Scale Invariant Output Neuron Kernel Method Kernel Space Winning Neuron 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Corchado, E., Fyfe, C.: The Scale Invariant Map and Maximum Likelihood Hebbian Learning. In: Sixth International Conference on Knowledge-Based Intelligent Information Engineering Systems, KES 2002, Italy (2002)Google Scholar
  2. 2.
    Corchado, E., Fyfe, C.: Relevance and kernel self-organising maps. In: Kaynak, O., Alpaydın, E., Oja, E., Xu, L. (eds.) ICANN 2003 and ICONIP 2003. LNCS, vol. 2714, Springer, Heidelberg (2003)Google Scholar
  3. 3.
    Corchado E., MacDonald, D., Fyfe, C.: Optimal projections of high dimensionald data. In: IEEE International Conference on Data Mining, ICDM 2002 (2002)Google Scholar
  4. 4.
    Corchado, E., MacDonald, D., Fyfe, C.: Maximum and Minimum Likelihood Hebbian Learning for Exploratory Projection Pursuit. Data Mining and Knowledge Discovery (in press)Google Scholar
  5. 5.
    Fyfe, C.P.: properties of interneurons. In: From Neurobiology to Real World Computing, ICANN 1993, pp. 183–188 (1993)Google Scholar
  6. 6.
    Fyfe, C.: A scale-invariant feature map. Network:Computation in Neural Systems 7, 269–275 (1996)CrossRefGoogle Scholar
  7. 7.
    Fyfe, C., Baddeley, R.: Non-linear data structure extraction using simple hebbian networks. Biological Cybernetics 72(6), 533–541 (1995)zbMATHCrossRefGoogle Scholar
  8. 8.
    Fyfe, C., Baddeley, R., McGregor, D.R.: Exploratory Projection Pursuit: An Artificial Neural Network Approach, University of Strathclyde Research report/94/160 (1994)Google Scholar
  9. 9.
    Fyfe, C., Corchado, J.M.: Automating the construction of CBR Systems using Kernel Methods. International Journal of Intelligent Systems 16(4) (April 2001) ISSN 0884-8173Google Scholar
  10. 10.
    Fyfe, C., MacDonald, D.: Epsilon-insensitive Hebbian Learning. Neurocomputing 47, 35–57 (2002)zbMATHCrossRefGoogle Scholar
  11. 11.
    Fyfe, C., MacDonald, D., Lai, P.L., Rosipal, R., Charles, D.: Unsupervised Learning with Radial Kernels. In: Howlett, R.J., Jain, L.C. (eds.) Recent Advances in Radial Basis Functions, Elsevier, Amsterdam (2000)Google Scholar
  12. 12.
    MacDonald, D.: Unsupervised Neural Networks for the Visualisation of Data. PhD Thesis, University of Paisley (2002)Google Scholar
  13. 13.
    MacDonald, D., Corchado, E., Fyfe, C., Merenyi, E.: Maximum and Minimum Likelihood Hebbian Learning for Exploratory Projection Pursuit. In: Dorronsoro, J.R. (ed.) ICANN 2002. LNCS, vol. 2415, p. 649. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  14. 14.
    Scholkopf, B.: The Kernel Trick for Distances. Technical report, Microsoft Research (May 2000)Google Scholar
  15. 15.
    Scholkopf, B., Smola, A., Muller, K.R.: Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation 10, 1299–1319 (1998)CrossRefGoogle Scholar
  16. 16.
    Vapnik, V.: The nature of statistical learning theory. Springer, Heidelberg (1995)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Donald MacDonald
    • 1
  • Jos Koetsier
    • 1
  • Emilio Corchado
    • 1
  • Colin Fyfe
    • 1
  • Juan Corchado
    • 2
  1. 1.School of Information and Communication TechnologiesThe University of PaisleyPaisleyScotland
  2. 2.Departamento de Informática y AutomáticaUniversidad de SalamancaSpain

Personalised recommendations