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Multi-Layer Perceptrons and Symbolic Data

Rossi, Fabrice; Conan-Guez, Brieuc (2008), Multi-Layer Perceptrons and Symbolic Data, in Diday, Edwin; Noirhomme-Fraiture, Monique, Symbolic Data Analysis and the SODAS Software, Wiley : Chichester (UK), p. 373-391

Type
Chapitre d'ouvrage
External document link
http://hal.inria.fr/inria-00232878/en/
Date
2008
Book title
Symbolic Data Analysis and the SODAS Software
Book author
Diday, Edwin; Noirhomme-Fraiture, Monique
Publisher
Wiley
Published in
Chichester (UK)
ISBN
978-0-470-01883-5
Number of pages
457
Pages
373-391
Metadata
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Author(s)
Rossi, Fabrice
Conan-Guez, Brieuc
Abstract (EN)
In some real world situations, linear models are not sufficient to represent accurately complex relations between input variables and output variables of a studied system. Multilayer Perceptrons are one of the most successful non-linear regression tool but they are unfortunately restricted to inputs and outputs that belong to a normed vector space. In this chapter, we propose a general recoding method that allows to use symbolic data both as inputs and outputs to Multilayer Perceptrons. The recoding is quite simple to implement and yet provides a flexible framework that allows to deal with almost all practical cases. The proposed method is illustrated on a real world data set.
Subjects / Keywords
Symbolic Data; Interval Data; Multi-Layer Perceptron