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Support Vector Regression (SVR) has been very successful in pattern recognition, text categorization and function approximation. In real application systems ...
Abstract. Support Vector Regression (SVR) has been very successful in pattern recognition, text categorization and function approximation.
Support Vector Regression (SVR) has been very successful in pattern recognition, text categorization and function approximation. In real application systems ...
In this paper, a new method is proposed for estimating fuzzy regression models based on a novel robust support vector machines with exact predictors and fuzzy ...
In this paper, a new method is proposed for estimating fuzzy regression models based on a novel robust support vector machines with exact predictors and ...
In this paper we propose a robust LS-SVM regression method which imposes the robustness on the estimation of LS-SVM regression by assigning weight to each data ...
In the proposed approach, the fuzzy c-mean (FCM) clus- tering algorithm, the SVR approach, and a fuzzy weighted mechanism are used. In the proposed algorithm, ...
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Nov 21, 2013 · The robust SVM is an extension of SVM for interval-valued data classification. We compare our proposed method with SVM, robust SVM, ISVM-FC ( ...
Missing: Regression | Show results with:Regression
A Robust Support Vector Regression Based on Fuzzy Clustering · Horng-Lin Shieh. Computer Science, Mathematics. International Conference on Industrial… 2009.
Aug 18, 2017 · To solve this problem, a multi-model modeling approach based on fuzzy C-means clustering and support vector regression is proposed in this ...