MAICS: multilevel artificial immune classification system

  • Authors:

  • Michal Bereta;Tadeusz Burczynski

  • Affiliations:

  • Institute of Computer Modeling, Artificial Intelligence Department, Cracow University of Technology, Cracow, Poland;Institute of Computer Modeling, Artificial Intelligence Department, Cracow University of Technology, Cracow, Poland

  • Venue:
  • ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
  • Year:
  • 2006

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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.