Title :
Fuzzy support vector regression for function approximation with noises
Author :
Zhang, Rui ; Duan, Xian-Bao ; Hao, Lei
Author_Institution :
Sch. of Sci., Shandong Univ. of Technol., Zibo, China
Abstract :
Fuzzy support vector machine (FSVM) have been very successful in pattern recognition problems with outliers or noises. FSVM enhances the SVM in reducing the effect of noises in data points. In this paper, we introduce FSVM to regression problems for function approximation with noises. We apply a fuzzy membership to each input point of SVR and reformulate SVR into fuzzy SVR (FSVR) such that different input points can make different contributions to the learning of decision function.
Keywords :
decision making; function approximation; fuzzy set theory; learning (artificial intelligence); pattern classification; regression analysis; signal denoising; support vector machines; data point; decision function; function approximation; fuzzy membership; fuzzy support vector machine; noise effect reduction; pattern recognition; regression problem; Artificial neural networks; Function approximation; Noise; Support vector machines; Testing; Training; Training data; FSVM; SVM; SVR; regression;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5623271
