A New Classifier Based on Resource Limited Artificial Immune Systems

Watkins, Andrew and Boggess, Lois C. (2002) A New Classifier Based on Resource Limited Artificial Immune Systems. In: Proceedings of the 2002 Congress on Evolutionary Computation. IEEE, pp. 1546-1551. ISBN 0-7803-7282-4. (doi:10.1109/CEC.2002.1004472) (KAR id:13793)

PDF Language: English
Download this file (PDF/223kB)
Request a format suitable for use with assistive technology e.g. a screenreader
Official URL: http://dx.doi.org/10.1109/CEC.2002.1004472

Abstract

This paper presents a new tool for supervised learning, modeled on resource limited Artificial Immune Systems. A supervised learning system, it is self-regulatory, efficient, and stable under a wide range of user-set parameters. Its performance is comparable to well-established classifiers on a variety of testbeds, including the iris data, the diabetes classification problem, the ionosphere problem, and the rock/metal classification problem for mine detection.

Item Type:	Book section
DOI/Identification number:	10.1109/CEC.2002.1004472
Uncontrolled keywords:	pathogens; immune system; genetic mutations; artificial immune systems; clustering algorithms; evolution biology; computer networks; laboratories; collaborative work; books
Subjects:	Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions:	Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Funders:	Institute of Electrical and Electronics Engineers (https://ror.org/01n002310)
Depositing User:	Mark Wheadon
Date Deposited:	24 Nov 2008 18:00 UTC
Last Modified:	05 Nov 2024 09:47 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/13793 (The current URI for this page, for reference purposes)

University of Kent Author Information

Depositors only (login required):

Altmetric

Download Statistics

Total unique views for this document in KAR since July 2020. For more details click on the image.