Multi-Layer Perceptrons and Symbolic Data

  title={Multi-Layer Perceptrons and Symbolic Data},
  author={F. Rossi and B. Conan-Guez},
  • F. Rossi, B. Conan-Guez
  • Published 2008
  • Computer Science
  • ArXiv
  • 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… CONTINUE READING
    3 Citations


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    • J. Síma
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