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
Link To Document :
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