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Neural Network Classifiers

  • Šarūnas Raudys
Part of the Advances in Pattern Recognition book series (ACVPR)

Abstract

In this chapter we will utilise the methods from multivariate statistical analysis to investigate the pattern classification algorithms that can be obtained while training artificial neural networks. Our attention will be primarily focused on the similarities and differences between the statistical and neural approaches. For an introduction and a detailed acquaintance with artificial neural networks, the reader is referred to the textbooks of Hertz, Krogh and Palmer (1991), Bishop (1995), Haykin (1999) and others.

Keywords

Generalisation Error Radial Basis Function Training Vector Hide Layer Neurone Neural Network Classifier 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London Limited 2001

Authors and Affiliations

  • Šarūnas Raudys
    • 1
  1. 1.Data Analysis DepartmentInstitute of Mathematics and InformaticsVilniusLithuania

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