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Categorical Topological Map

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Artificial Neural Networks — ICANN 2002 (ICANN 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2415))

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Abstract

This paper introduces a topological map dedicated to an automatic classification categorical data. Usually, topological maps uses a numerical (or binary) coding of the categorical data during the learning process. In the present paper, we propose a probabilistic formalism where the neurons now represent probability tables. Two examples using actual and synthetic data allow to validate the approach. The results show the good quality of the topological order obtained as well as its performances in classification.

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References

  1. Anouar, F. Badran, F. Thiria, S. Probabilistic self-organizing map and radial basis function networks. Neurocomputing 20, 83–96. (1998)

    Article  MATH  Google Scholar 

  2. Dempster, A. P. Laird, N. M. Rubin, D. B. Maximum likelihood from incomplete data via the EM algorithm. Journal of royal Statistic Society, Series B, 39, 1–38

    Google Scholar 

  3. Lebbah, M. Badran, F. Thiria, S. Topological Map for Binary Data, ESANN 2000, Bruges, April 26–27-28, 2000, Proceedings

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  4. Leich, F. Weingessel, A. Dimitriadou, E. Competitive Learning for Binary Data. Proc of ICANN’98, septembre 2–4. Springer Verlag. (1998)

    Google Scholar 

  5. Luttrel S. P, 1994. A Bayesian Analysis of Self-Organizing Maps, Neural Computing vol 6

    Google Scholar 

  6. Kohonen, T. Self-Organizing Map. Springer, Berlin.(1994)

    Google Scholar 

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Author information

Authors and Affiliations

  1. RENAULT, Direction de la recherche, TCR RUC T 62, 1 avenue du golf F, 78288, Guyancourt Cedex

    Mustapha Lebbah & Christian Chabanon

  2. Laboratoire LODYC, Université Paris 6, Tour 26-4eétage, 4 place Jussieu, 75252, Paris cedex 05, France

    Mustapha Lebbah & Sylvie Thiria

  3. CEDRIC, Conservatoire National des Arts et Métiers, 292 rue Saint Martin, 75003, Paris, France

    Fouad Badran

Authors
  1. Mustapha Lebbah
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  2. Christian Chabanon
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  3. Fouad Badran
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  4. Sylvie Thiria
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Editor information

Editors and Affiliations

  1. ETS Informática, Universidad Autónoma de Madrid, 28049, Madrid, Spain

    José R. Dorronsoro

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© 2002 Springer-Verlag Berlin Heidelberg

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Lebbah, M., Chabanon, C., Badran, F., Thiria, S. (2002). Categorical Topological Map. In: Dorronsoro, J.R. (eds) Artificial Neural Networks — ICANN 2002. ICANN 2002. Lecture Notes in Computer Science, vol 2415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46084-5_144

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  • DOI: https://doi.org/10.1007/3-540-46084-5_144

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44074-1

  • Online ISBN: 978-3-540-46084-8

  • eBook Packages: Springer Book Archive

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