کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10361537 | 870361 | 2005 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Adaptive classification with ellipsoidal regions for multidimensional pattern classification problems
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
This paper presents an adaptive classification method that utilizes ellipsoidal regions for multidimensional pattern classification problems with continuous input variables. The classification method fits a finite number of the ellipsoidal regions to data pattern by using adaptive operations iteratively. The method adaptively expands, rotates, shrinks, and/or moves the ellipsoidal regions while each ellipsoidal region is separately handled with a fitness value assigned. The adaptation procedure is combined with a variable selection process in the outer loop, where significant input variables for the ellipsoids are determined by using a stepwise selection method. The performance of the method is evaluated on well-known classification problems from the UCI machine learning repository. The evaluation result shows that the proposed method can exert equivalent or superior performance, with smaller number of rules, to other classification methods such as fuzzy rules, decision trees, or neural networks.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 26, Issue 9, 1 July 2005, Pages 1232-1243
Journal: Pattern Recognition Letters - Volume 26, Issue 9, 1 July 2005, Pages 1232-1243
نویسندگان
Ki K. Lee, Wan C. Yoon,