MLTSVM
swMATH ID: | 27170 |
Software Authors: | Chen, Wei-Jie; Shao, Yuan-Hai; Li, Chun-Na; Deng, Nai-Yang |
Description: | MLTSVM: a novel twin support vector machine to multi-label learning. Multi-label learning paradigm, which aims at dealing with data associated with potential multiple labels, has attracted a great deal of attention in machine intelligent community. In this paper, we propose a novel multi-label twin support vector machine (MLTSVM) for multi-label classification. MLTSVM determines multiple nonparallel hyperplanes to capture the multi-label information embedded in data, which is a useful promotion of twin support vector machine (TWSVM) for multi-label classification. To speed up the training procedure, an efficient successive overrelaxation (SOR) algorithm is developed for solving the involved quadratic programming problems (QPPs) in MLTSVM. Extensive experimental results on both synthetic and real-world multi-label datasets confirm the feasibility and effectiveness of the proposed MLTSVM. |
Homepage: | https://www.sciencedirect.com/science/article/pii/S0031320315003751 |
Keywords: | multi-label classification; support vector machines; twin support vector machines; quadratic programming; successive overrelaxation |
Related Software: | ML-KNN; LIBSVM; ReGEC_L1; SSA; CheXpert; HCP; Pegasos; RSVM; TPMSVM; SSVM; LIBLINEAR; SIFT; NESVM; MEKA; PASCAL VOC; LibD3C; MULAN |
Cited in: | 11 Documents |
Standard Articles
1 Publication describing the Software, including 1 Publication in zbMATH | Year |
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MLTSVM: a novel twin support vector machine to multi-label learning. Zbl 1394.68277 Chen, Wei-Jie; Shao, Yuan-Hai; Li, Chun-Na; Deng, Nai-Yang |
2016
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Cited by 44 Authors
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top 5
Cited in 7 Serials
Cited in 4 Fields
10 | Computer science (68-XX) |
5 | Statistics (62-XX) |
1 | Numerical analysis (65-XX) |
1 | Operations research, mathematical programming (90-XX) |