Multi-Layer Perceptrons and Symbolic Data

@article{Rossi2008MultiLayerPA,
  title={Multi-Layer Perceptrons and Symbolic Data},
  author={F. Rossi and B. Conan-Guez},
  journal={ArXiv},
  year={2008},
  volume={abs/0802.0251}
}
  • 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

    References

    SHOWING 1-10 OF 16 REFERENCES
    Functional multi-layer perceptron: a non-linear tool for functional data analysis
    • 71
    • PDF
    Multi-layer Perceptron on Interval Data ?
    • 43
    • PDF
    On interval weighted three-layer neural networks
    • 37
    • Highly Influential
    • PDF
    Neural expert systems
    • J. Síma
    • Computer Science
    • Neural Networks
    • 1995
    • 58
    Neural Networks for Pattern Recognition
    • 12,955
    • Highly Influential
    Representation of functional data in neural networks
    • 113
    • PDF
    Connectionist nonparametric regression: Multilayer feedforward networks can learn arbitrary mappings
    • H. White
    • Mathematics, Computer Science
    • Neural Networks
    • 1990
    • 691
    Handling uncertainty in neural networks: an interval approach
    • S. Simoff
    • Computer Science
    • Proceedings of International Conference on Neural Networks (ICNN'96)
    • 1996
    • 20
    • Highly Influential
    Analysis of Symbolic Data: Exploratory Methods for Extracting Statistical Information from Complex Data
    • 517
    Numerical recipes in C
    • 16,291