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Iranian Journal of Fuzzy Systems، جلد ۱۰، شماره ۴، صفحات ۴۱-۵۵
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| عنوان فارسی |
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| چکیده فارسی مقاله |
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| کلیدواژه‌های فارسی مقاله |
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| عنوان انگلیسی |
A QUADRATIC MARGIN-BASED MODEL FOR WEIGHTING FUZZY CLASSIFICATION RULES INSPIRED BY SUPPORT VECTOR MACHINES |
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| چکیده انگلیسی مقاله |
Recently, tuning the weights of the rules in Fuzzy Rule-Base Classification Systems is researched in order to improve the accuracy of classification. In this paper, a margin-based optimization model, inspired by Support Vector Machine classifiers, is proposed to compute these fuzzy rule weights. This approach not only considers both accuracy and generalization criteria in a single objective function, but also is independent of any order in presenting data patterns or fuzzy rules. It has a global optimum solution and needs only one regularization parameter C to be adjusted. In addition, a rule reduction method is proposed to eliminating low weighted rules and having a compact rule-base. This method is compared with some greedy, reinforcement and local search rule weighting methods on 13 standard datasets. The experimental results show that, the proposed method significantly outperforms the other ones especially from the viewpoint of generalization. |
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| کلیدواژه‌های انگلیسی مقاله |
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| نویسندگان مقاله |
Mohammad Taheri |
Department of Computer Science & Engineering & IT, Shiraz
University, Shiraz, Fars, Iran
Hamid Azad |
Department of Electrical Engineering, Science & Research Branch,
Islamic Azad University, Marvdasht, Fars, Iran
Koorush Ziarati |
Department of Computer Science & Engineering & IT, Shiraz Uni-
versity, Shiraz, Fars, Iran
Reza Sanaye |
Department of Computer Science & Engineering & IT, Shiraz Univer-
sity, Shiraz, Fars, Iran
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| نشانی اینترنتی |
http://ijfs.usb.ac.ir/article_1046_d68480fb8f7424785567ae239c3b8c1f.pdf |
| فایل مقاله |
اشکال در دسترسی به فایل - ./files/site1/rds_journals/448/article-448-1095252.pdf |
| کد مقاله (doi) |
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| زبان مقاله منتشر شده |
en |
| موضوعات مقاله منتشر شده |
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