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Effect of fuzzy resource allocation method on AIRS classifier accuracy


Citation

Golzari, Shahram and Doraisamy, Shyamala and Sulaiman, Md. Nasir and Udzir, Nur Izura (2009) Effect of fuzzy resource allocation method on AIRS classifier accuracy. Journal of Theoretical and Applied Information Technology, 5 (1). pp. 18-24. ISSN 1992-8645

Abstract / Synopsis

Artificial Immune Recognition System (AIRS) is immune inspired classifier that competes with famous classifiers. Many researches have been conducted to improve the accuracy of AIRS and to investigate the source of power of AIRS. Some of these researches have focused on resource allocation method of AIRS.This study investigates the difference between the accuracy of AIRS with fuzzy resource allocation and the accuracy of original AIRS, by using the reliable statistical method. The combination of ten fold cross validation and t-test was used as evaluation method and algorithms tested on ten benchmark datasets of UCI machine learning repository. Based on the results of experiments, using fuzzy resource allocation increases the accuracy of AIRS in majority of datasets but the increase is significant in minority of datasets.


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Additional Metadata

Item Type: Article
Subject: Immune system - Computer simulation
Subject: Immunocomputers
Subject: Artificial intelligence
Divisions: Faculty of Computer Science and Information Technology
Keywords: Artificial immune system; AIRS: Fuzzy resource allocation; Statistical evaluation
Depositing User: Umikalthom Abdullah
Date Deposited: 10 May 2012 14:40
Last Modified: 27 Nov 2015 16:46
URI: http://psasir.upm.edu.my/id/eprint/14248
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