• DocumentCode
    1945566
  • Title

    A Discrimination Based Artificial Immune System for Classification

  • Author

    Igawa, Kazushi ; Ohashi, Hirotada

  • Author_Institution
    Dept. of Quantum Eng. & Syst. Sci., Tokyo Univ.
  • Volume
    2
  • fYear
    2005
  • fDate
    28-30 Nov. 2005
  • Firstpage
    787
  • Lastpage
    792
  • Abstract
    This paper presents a new artificial immune system for classification. It is named a discrimination based artificial immune system (DAIS). It is based on the principle of self-nonself discrimination by T cells in the human immune system. Ability of a natural immune system to distinguish between self and nonself molecules is applicable for classification in a way that one class is distinguished from other. We demonstrate the behavior of DAIS and show this system is efficient for artificial datasets and also for real world datasets. It has comparable performance to other classifier systems, while it needs much less memory
  • Keywords
    artificial intelligence; genetic algorithms; pattern classification; DAIS; classifier system; discrimination based artificial immune system; natural immune system; Adaptive systems; Artificial immune systems; Biological system modeling; Computational intelligence; Data analysis; Humans; Immune system; Information filtering; Machine learning; Systems engineering and theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
  • Conference_Location
    Vienna
  • Print_ISBN
    0-7695-2504-0
  • Type

    conf

  • DOI
    10.1109/CIMCA.2005.1631564
  • Filename
    1631564