Evolution of Multi-class Single Layer Perceptron

  • Sarunas Raudys
Conference paper

DOI: 10.1007/978-3-540-71629-7_1

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4432)
Cite this paper as:
Raudys S. (2007) Evolution of Multi-class Single Layer Perceptron. In: Beliczynski B., Dzielinski A., Iwanowski M., Ribeiro B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2007. Lecture Notes in Computer Science, vol 4432. Springer, Berlin, Heidelberg

Abstract

While training single layer perceptron (SLP) in two-class situation, one may obtain seven types of statistical classifiers including minimum empirical error and support vector (SV) classifiers. Unfortunately, both classifiers cannot be obtained automatically in multi-category case. We suggest designing K(K-1)/2 pair-wise SLPs and combine them in a special way. Experiments using K=24 class chromosome and K=10 class yeast infection data illustrate effectiveness of new multi-class network of the single layer perceptrons.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Sarunas Raudys
    • 1
  1. 1.Vilnius Gediminas Technical University, Sauletekio 11, Vilnius, LT-10223Lithuania

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