Discrimination-based Artificial Immune System: Modeling the Learning Mechanism of Self and Non-self Discrimination for Classification

Abstract

This study presents a new artificial immune system for classification. It was named discrimination-based artificial immune system (DAIS) and was based on the principle of self and non-self discrimination by T cells in the human imm une system. Ability of a natural immune system to distinguish between self and non-self molecules was applicable for classification in a way that one class was distinguished from others. We model this and the mechanism of the education in a thymus for classification. Especially, we introduce the me thod to decide the recognition distance threshold o f the artificial lymphocyte, as the negative selectio n algorithm. We apply DAIS to real world datasets and show its performance to be comparable to that o f other classifier systems. We conclude that this modeling was appropriate and DAIS was a useful classifier.