A task decomposition algorithm using radial basis functions for classification problems

Seiji Ishihara, Harukazu Igarashi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes an algorithm for decomposing a multi-class classification problem into a set of two-class classification problems. The algorithm divides a set of input pattern vectors in each class into subsets according to the distribution of the selected input pattern vectors. The distribution is represented by RBF network, whose parameters are estimated according to the evaluation based on MDL criterion. In this paper, the algorithm applied for constructing a modular neural network. Experimental results showed that the algorithm simplifies multi-class classification problems effectively.

Original languageEnglish
Title of host publicationProceedings of the Digital Imaging Computing
Subtitle of host publicationTechniques and Applications, DICTA 2005
Pages2-7
Number of pages6
DOIs
Publication statusPublished - 2005 Dec 1
EventDigital Imaging Computing: Techniques and Applications, DICTA 2005 - Cairns, Australia
Duration: 2005 Dec 62005 Dec 8

Publication series

NameProceedings of the Digital Imaging Computing: Techniques and Applications, DICTA 2005
Volume2005

Conference

ConferenceDigital Imaging Computing: Techniques and Applications, DICTA 2005
CountryAustralia
CityCairns
Period05/12/605/12/8

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Ishihara, S., & Igarashi, H. (2005). A task decomposition algorithm using radial basis functions for classification problems. In Proceedings of the Digital Imaging Computing: Techniques and Applications, DICTA 2005 (pp. 2-7). [1578100] (Proceedings of the Digital Imaging Computing: Techniques and Applications, DICTA 2005; Vol. 2005). https://doi.org/10.1109/DICTA.2005.1578100