Effect of nonlinear resource allocation on AIRS classifier accuracy
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 t...
| Κύριοι συγγραφείς: | , , , |
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| Μορφή: | Conference or Workshop Item |
| Γλώσσα: | English |
| Έκδοση: |
2008
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| Θέματα: | |
| Διαθέσιμο Online: | https://repo.uum.edu.my/id/eprint/11422/1/596-600-CR162.pdf |
| Περίληψη: | 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. |
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