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MAICS: Multilevel Artificial Immune Classification System

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Artificial Intelligence and Soft Computing – ICAISC 2006 (ICAISC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4029))

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Abstract

This paper presents a novel approach to feature selection and multiple-class classification problems. The proposed method is based on metaphors derived from artificial immune systems, clonal and negative selection paradigms. A novel clonal selection algorithm – Immune K-Means, is proposed. The proposed system is able to perform feature selection and model identification tasks by evolving specialized subpopulations of T- and B-lymphocytes. Multilevel evolution and real-valued coding enable for further extending of the proposed model and interpreting the subpopulations of lymphocytes as sets of evolving fuzzy rules.

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References

  1. de Castro, L.N., Timmis, J.: Artificial Immune Systems: A New Computational Approach. Springer, London (2002)

    MATH  Google Scholar 

  2. Bereta, M., Burczyński, T.: Hybrid immune algorithm for feature selection and classification of ECG signals. In: Burczyński, T., Cholewa, W., Moczulski, W. (eds.) Recent Developments in Artificial Intelligence Methods, Gliwice. AI-METH Series, pp. 25–28 (2005)

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  3. Goodman, D., Boggess, L., Watkins, A.: Artificial immune system classification of multiple-class problems. In: Artificial Neural Networks in Engineering (ANNIE 2002) (2002)

    Google Scholar 

  4. Hoffmann, F.: Combining boosting and evolutionary algorithms for learning of fuzzy classification rules. Fuzzy Sets and Systems 141(1), 47–58 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  5. Ji, Z., Dasgupta, D.: Real -valued negative selection algorithm with variable-sized. In: Deb, K., et al. (eds.) International Conference on Genetic and Evolutionary Computation (GECCO 2004), Seattle, Washington USA, pp. 287–298. Springer, Heidelberg (2004)

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Author information

Authors and Affiliations

  1. Institute of Computer Modeling, Artificial Intelligence Department, Cracow University of Technology, Warszawska 24, 31-155, Cracow, Poland

    Michal Bereta & Tadeusz Burczynski

  2. Department for Strength of Materials and Computational Mechanics, Silesian University of Technology, Konarskiego 18a, 44-100, Gliwice, Poland

    Tadeusz Burczynski

Authors
  1. Michal Bereta
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  2. Tadeusz Burczynski
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Academy of Humanities and Economics, Poland

    Leszek Rutkowski

  2. Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  3. Department of Electrical Engineering and Computer Sciences, Berkeley Initiative in Soft Computing (BISC), University of California, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

  4. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Żurada

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© 2006 Springer-Verlag Berlin Heidelberg

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Bereta, M., Burczynski, T. (2006). MAICS: Multilevel Artificial Immune Classification System. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2006. ICAISC 2006. Lecture Notes in Computer Science(), vol 4029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11785231_59

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  • DOI: https://doi.org/10.1007/11785231_59

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-35748-3

  • Online ISBN: 978-3-540-35750-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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