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USING DISTRIBUTION OF DATA TO ENHANCE PERFORMANCE OF FUZZY CLASSIFICATION SYSTEMS | ||
| Iranian Journal of Fuzzy Systems | ||
| مقاله 3، دوره 4، شماره 1، تابستان 2007، صفحه 21-36 اصل مقاله (249.7 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22111/ijfs.2007.355 | ||
| نویسندگان | ||
EGHBAL G. MANSOORI  ؛ MANSOOR J. ZOLGHADRI؛ SERAJ D. KATEBI
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| COMPUTER SCIENCE AND ENGINEERING DEPARTMENT, COLLEGE OF ENGINEERING, SHIRAZ UNIVERSITY, SHIRAZ, IRAN | ||
| چکیده | ||
| This paper considers the automatic design of fuzzy rule-based classification systems based on labeled data. The classification performance and interpretability are of major importance in these systems. In this paper, we utilize the distribution of training patterns in decision subspace of each fuzzy rule to improve its initially assigned certainty grade (i.e. rule weight). Our approach uses a punishment algorithm to reduce the decision subspace of a rule by reducing its weight, such that its performance is enhanced. Obviously, this reduction will cause the decision subspace of adjacent overlapping rules to be increased and consequently rewarding these rules. The results of computer simulations on some well-known data sets show the effectiveness of our approach. | ||
| کلیدواژه‌ها | ||
| Fuzzy rule-based classification systems؛ Rule weight | ||
| مراجع | ||
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