An efficient and effective immune based classifier
Problem statement: Artificial Immune Recognition System (AIRS) is most popular and effective immune inspired classifier. Resource competition is one stage of AIRS. Resource competition is done based on the number of allocated resources. AIRS uses a linear method to allocate resources. The linear res...
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Science Publications
2011
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Online Access: | http://psasir.upm.edu.my/id/eprint/22513/1/An%20efficient%20and%20effective%20immune%20based%20classifier.pdf http://psasir.upm.edu.my/id/eprint/22513/ http://thescipub.com/html/10.3844/jcssp.2011.148.153 |
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my.upm.eprints.225132015-10-13T07:25:28Z http://psasir.upm.edu.my/id/eprint/22513/ An efficient and effective immune based classifier Golzari, Shahram C. Doraisamy, Shyamala Sulaiman, Md. Nasir Udzir, Nur Izura Problem statement: Artificial Immune Recognition System (AIRS) is most popular and effective immune inspired classifier. Resource competition is one stage of AIRS. Resource competition is done based on the number of allocated resources. AIRS uses a linear method to allocate resources. The linear resource allocation increases the training time of classifier. Approach: In this study, a new nonlinear resource allocation method is proposed to make AIRS more efficient. New algorithm, AIRS with proposed nonlinear method, is tested on benchmark datasets from UCI machine learning repository. Results: Based on the results of experiments, using proposed nonlinear resource allocation method decreases the training time and number of memory cells and doesn't reduce the accuracy of AIRS. Conclusion: The proposed classifier is an efficient and effective classifier. Science Publications 2011 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/22513/1/An%20efficient%20and%20effective%20immune%20based%20classifier.pdf Golzari, Shahram and C. Doraisamy, Shyamala and Sulaiman, Md. Nasir and Udzir, Nur Izura (2011) An efficient and effective immune based classifier. Journal of Computer Science, 7 (2). pp. 148-153. ISSN 1549-3636; ESSN: 1552-6607 http://thescipub.com/html/10.3844/jcssp.2011.148.153 10.3844/jcssp.2011.148.153 |
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Problem statement: Artificial Immune Recognition System (AIRS) is most popular and effective immune inspired classifier. Resource competition is one stage of AIRS. Resource competition is done based on the number of allocated resources. AIRS uses a linear method to allocate resources. The linear resource allocation increases the training time of classifier. Approach: In this study, a new nonlinear resource allocation method is proposed to make AIRS more efficient. New algorithm, AIRS with proposed nonlinear method, is tested on benchmark datasets from UCI machine learning repository. Results: Based on the results of experiments, using proposed nonlinear resource allocation method decreases the training time and number of memory cells and doesn't reduce the accuracy of AIRS. Conclusion: The proposed classifier is an efficient and effective classifier. |
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Article |
author |
Golzari, Shahram C. Doraisamy, Shyamala Sulaiman, Md. Nasir Udzir, Nur Izura |
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Golzari, Shahram C. Doraisamy, Shyamala Sulaiman, Md. Nasir Udzir, Nur Izura An efficient and effective immune based classifier |
author_facet |
Golzari, Shahram C. Doraisamy, Shyamala Sulaiman, Md. Nasir Udzir, Nur Izura |
author_sort |
Golzari, Shahram |
title |
An efficient and effective immune based classifier |
title_short |
An efficient and effective immune based classifier |
title_full |
An efficient and effective immune based classifier |
title_fullStr |
An efficient and effective immune based classifier |
title_full_unstemmed |
An efficient and effective immune based classifier |
title_sort |
efficient and effective immune based classifier |
publisher |
Science Publications |
publishDate |
2011 |
url |
http://psasir.upm.edu.my/id/eprint/22513/1/An%20efficient%20and%20effective%20immune%20based%20classifier.pdf http://psasir.upm.edu.my/id/eprint/22513/ http://thescipub.com/html/10.3844/jcssp.2011.148.153 |
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