Multi-Layer Perceptrons and Symbolic Data

Details Multi-Layer Perceptrons and Symbolic Data Multi-Layer Perceptrons and Symbolic Data

2008-02-02

arxiv.org/abs/0802.0251v1

Symbolic Data Analysis and the SODAS Software Wiley (Ed.) (2008) 373-391

Computer Science

Neural and Evolutionary Computing

Scientific paper

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.

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