Chapter 20. Multi-Layer Perceptrons and Symbolic Data

  1. Edwin Diday3 and
  2. Monique Noirhomme-Fraiture4
  1. Fabrice Rossi1 and
  2. Brieuc Conan-Guez2

Published Online: 28 JAN 2008

DOI: 10.1002/9780470723562.ch20

Symbolic Data Analysis and the SODAS Software

Symbolic Data Analysis and the SODAS Software

How to Cite

Rossi, F. and Conan-Guez, B. (2007) Multi-Layer Perceptrons and Symbolic Data, in Symbolic Data Analysis and the SODAS Software (eds E. Diday and M. Noirhomme-Fraiture), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470723562.ch20

Editor Information

  1. 3

    Université Paris IX-Dauphine, LISE-CEREMADE, Place du Marechal de Lattre de Tassigny, Paris Cedex 16, France F-75775

  2. 4

    Facultés Universitaires Notre-Dame de la Paix, Faculté d'Informatique, Rue Grandgagnage, 21, Namur, Belgium, B-5000

Author Information

  1. 1

    Projet AxIS, INRIA, Centre de Rechoche Paris-Roquencourt, Domaine de Volucean, BP 105, Le Chesney Cedex, France F-78153

  2. 2

    LITA EA3097, Université de Metz, Ile de Saulcy, F-57045, Metz, France

Publication History

  1. Published Online: 28 JAN 2008
  2. Published Print: 18 JAN 2007

ISBN Information

Print ISBN: 9780470018835

Online ISBN: 9780470723562

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Keywords:

  • normed vector space;
  • empirical error;
  • quadratic distance or the cross-entropy;
  • disjunctive coding scheme;
  • penalize complex models;
  • softmax activation function;
  • probabilistic interpretation;
  • cross-entropy distance;
  • optimal lossy encoding;
  • total monthly precipitations

Summary

This chapter contains sections titled:

  • Introduction

  • Background

  • A numerical coding approach

  • Open problems

  • Experiments

  • Conclusion

  • References