A Discrimination Based Artificial Immune System for Classification

Authors:
Kazushi Igawa;Hirotada Ohashi
Affiliations:
University of Tokyo;University of Tokyo
Venue:
CIMCA '05 Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-2 (CIMCA-IAWTIC'06) - Volume 02
Year:
2005

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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.