A bilateral-truncated-loss based robust support vector machine for classification problems
| LEADER | caa a22 4500 | ||
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| 001 | 605469687 | ||
| 003 | CHVBK | ||
| 005 | 20210128100323.0 | ||
| 007 | cr unu---uuuuu | ||
| 008 | 210128e20151001xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s00500-014-1448-9 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00500-014-1448-9 | ||
| 245 | 0 | 2 | |a A bilateral-truncated-loss based robust support vector machine for classification problems |h [Elektronische Daten] |c [Xiaowei Yang, Le Han, Yan Li, Lifang He] |
| 520 | 3 | |a Support vector machine (SVM) is sensitive to outliers or noise in the training dataset. Fuzzy SVM (FSVM) and the bilateral-weighted FSVM (BW-FSVM) can partly overcome this shortcoming by assigning different fuzzy membership degrees to different training samples. However, it is a difficult task to set the fuzzy membership degrees of the training samples. To avoid setting fuzzy membership degrees, from the beginning of the BW-FSVM model, this paper outlines the construction of a bilateral-truncated-loss based robust SVM (BTL-RSVM) model for classification problems with noise. Based on its equivalent model, we theoretically analyze the reason why the robustness of BTL-RSVM is higher than that of SVM and BW-FSVM. To solve the proposed BTL-RSVM model, we propose an iterative algorithm based on the concave-convex procedure and the Newton-Armijo algorithm. A set of experiments is conducted on ten real world benchmark datasets to test the robustness of BTL-RSVM. The statistical tests of the experimental results indicate that compared with SVM, FSVM and BW-FSVM, the proposed BTL-RSVM can significantly reduce the effects of noise and provide superior robustness. | |
| 540 | |a Springer-Verlag Berlin Heidelberg, 2014 | ||
| 690 | 7 | |a Bilateral-weighted fuzzy support vector machine |2 nationallicence | |
| 690 | 7 | |a Support vector machine |2 nationallicence | |
| 690 | 7 | |a Fuzzy support vector machine |2 nationallicence | |
| 690 | 7 | |a Concave-convex procedure |2 nationallicence | |
| 690 | 7 | |a Class noise |2 nationallicence | |
| 700 | 1 | |a Yang |D Xiaowei |u Department of Mathematics, School of Sciences, South China University of Technology, 510641, Guangzhou, People's Republic of China |4 aut | |
| 700 | 1 | |a Han |D Le |u Department of Mathematics, School of Sciences, South China University of Technology, 510641, Guangzhou, People's Republic of China |4 aut | |
| 700 | 1 | |a Li |D Yan |u Department of Mathematics, School of Sciences, South China University of Technology, 510641, Guangzhou, People's Republic of China |4 aut | |
| 700 | 1 | |a He |D Lifang |u School of Computer Science and Engineering, South China University of Technology, 510641, Guangzhou, People's Republic of China |4 aut | |
| 773 | 0 | |t Soft Computing |d Springer Berlin Heidelberg |g 19/10(2015-10-01), 2871-2882 |x 1432-7643 |q 19:10<2871 |1 2015 |2 19 |o 500 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00500-014-1448-9 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s00500-014-1448-9 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Yang |D Xiaowei |u Department of Mathematics, School of Sciences, South China University of Technology, 510641, Guangzhou, People's Republic of China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Han |D Le |u Department of Mathematics, School of Sciences, South China University of Technology, 510641, Guangzhou, People's Republic of China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Li |D Yan |u Department of Mathematics, School of Sciences, South China University of Technology, 510641, Guangzhou, People's Republic of China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a He |D Lifang |u School of Computer Science and Engineering, South China University of Technology, 510641, Guangzhou, People's Republic of China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Soft Computing |d Springer Berlin Heidelberg |g 19/10(2015-10-01), 2871-2882 |x 1432-7643 |q 19:10<2871 |1 2015 |2 19 |o 500 | ||