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Genetic Programming and Evolvable Machines

, Volume 5, Issue 3, pp 291–317 | Cite as

Artificial Immune Recognition System (AIRS): An Immune-Inspired Supervised Learning Algorithm

  • Andrew Watkins
  • Jon Timmis
  • Lois Boggess
Article

Abstract

This paper presents the inception and subsequent revisions of an immune-inspired supervised learning algorithm, Artificial Immune Recognition System (AIRS). It presents the immunological components that inspired the algorithm and describes the initial algorithm in detail. The discussion then moves to revisions of the basic algorithm that remove certain unnecessary complications of the original version. Experimental results for both versions of the algorithm are discussed and these results indicate that the revisions to the algorithm do not sacrifice accuracy while increasing the data reduction capabilities of AIRS.

supervised learning artificial immune systems classification neural networks 

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Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • Andrew Watkins
    • 1
  • Jon Timmis
    • 1
  • Lois Boggess
    • 2
  1. 1.Computing LaboratoryUniversity of KentUK
  2. 2.Department of Computer Science and EngineeringMississippi State UniversityUSA

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