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An Approach to RBF Initialization with Feature Selection

  • Conference paper
Intelligent Systems'2014

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 322))

Abstract

The paper focuses on a radial basis function network initialization. An application of the agent-based population learning algorithm to set RBF networks main parameters including number and locations of centroids is discussed. The main contribution of the paper is proposing and evaluating an agent-based approach to determine unique subset of features independently for each hidden unit. Two versions of the proposed algorithm for selecting values of the RBF networks parameters are considered. The approach is validated experimentally. Advantages and main features of the PLA-based RBF designs are discussed basing on results of the computational experiment.

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Author information

Authors and Affiliations

  1. Department of Information Systems, Gdynia Maritime University, Morska 83, 81-225, Gdynia, Poland

    Ireneusz Czarnowski & Piotr Jędrzejowicz

Authors
  1. Ireneusz Czarnowski
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  2. Piotr Jędrzejowicz
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Corresponding author

Correspondence to Ireneusz Czarnowski .

Editor information

Editors and Affiliations

  1. School of Computing and Communications, Lancaster University, Lancaster, United Kingdom

    P. Angelov

  2. Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria

    K.T. Atanassov

  3. Intelligent Systems Department, Bulgarian Academy of Sciences Inst. of Infor. & Communication Techn., Sofia, Bulgaria

    L. Doukovska

  4. Metalurgy, University of Chemical Technology and, Sofia, Bulgaria

    M. Hadjiski

  5. University of Library Studies and IT (ULSIT), Sofia, Bulgaria

    V. Jotsov

  6. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    J. Kacprzyk

  7. Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland, New Zealand

    N. Kasabov

  8. Intelligent Systems Laboratory, Prof. Assen Zlatarov University Faculty of Technical Sciences, Bourgas, Bulgaria

    S. Sotirov

  9. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    E. Szmidt

  10. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    S. Zadrożny

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Czarnowski, I., Jędrzejowicz, P. (2015). An Approach to RBF Initialization with Feature Selection. In: Angelov, P., et al. Intelligent Systems'2014. Advances in Intelligent Systems and Computing, vol 322. Springer, Cham. https://doi.org/10.1007/978-3-319-11313-5_59

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  • DOI: https://doi.org/10.1007/978-3-319-11313-5_59

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11312-8

  • Online ISBN: 978-3-319-11313-5

  • eBook Packages: EngineeringEngineering (R0)

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