Title :
A new classifier based on resource limited artificial immune systems
Author :
Watkins, Andrew ; Boggess, Lois
Author_Institution :
Comput. Lab., Kent Univ., Canterbury, UK
fDate :
6/24/1905 12:00:00 AM
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
Keywords :
artificial life; learning (artificial intelligence); Classifier; diabetes classification problem; ionosphere problem; iris data; mine detection; resource limited artificial immune systems; supervised learning; testbeds; user-set parameters; Artificial immune systems; Biological system modeling; Diabetes; Immune system; Ionosphere; Iris; Laboratories; Pathogens; Software tools; Supervised learning;
Conference_Titel :
Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7282-4
DOI :
10.1109/CEC.2002.1004472
