Effect of nonlinear resource allocation on AIRS classifier accuracy

Citation

Hormozi, Shahram Golzari and C. Doraisamy, Shyamala and Sulaiman, Md. Nasir and Udzir, Nur Izura (2008) Effect of nonlinear resource allocation on AIRS classifier accuracy. In: Knowledge Management International Conference 2008 (KMICe 2008), 10-12 June 2008, Langkawi, Kedah. (pp. 596-600).

Abstract

Artificial Immune Recognition System (AIRS) is most popular immune inspired classifier. It also has shown itself to be a competitive classifier. AIRS uses linear method to allocate resources. In this paper, two different nonlinear resource allocation methods apply to AIRS. Then new algorithms are tested on 8 benchmark datasets. Based on the results of experiments, one of them increases the accuracy of AIRS in the majority of cases.

Download File

Text
596-600-CR162.pdf
Restricted to Repository staff only
Download (34kB)

Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Computer Science and Information Technology
Publisher:	Universiti Utara Malaysia
Keywords:	Artificial immune system; AIRS; Classification; Nonlinear
Depositing User:	Nabilah Mustapa
Date Deposited:	21 Mar 2018 07:00
Last Modified:	21 Mar 2018 07:00
URI:	http://psasir.upm.edu.my/id/eprint/59741
Statistic Details:	View Download Statistic

Actions (login required)

View Item