Group feature selection with multiclass support vector machine | |
Adam, Lukas1; Tang FZ(唐凤珍)2; Si BL(斯白露)2 | |
刊名 | NEUROCOMPUTING |
2018-11-23 | |
卷号 | 317页码:42-49 |
关键词 | Group Feature Selection Support Vector Machine Multiclass Support Vector Machine Alternating Direction Method Of Multipliers Eeg Channel Selection |
ISSN号 | 0925-2312 |
产权排序 | 1 |
英文摘要 | Feature reduction is nowadays an important topic in machine learning as it reduces the complexity of the final model and makes it easier to interpret. In some applications, the features arise from multiple sources and it is not so important to select the individual features as to select the important sources. This leads to a group feature selection problem. In this paper, we consider the group feature selection in the multiclass classification setting based on the framework of support vector machines. We reformulate it as a sparse problem by prescribing the maximum number of active groups and propose a novel method based on the ADMM algorithm. We proposed the method in such a way that the main computational load is performed in the first iteration and the remaining iterations can be computed fast. This allows us to handle large problems. We demonstrate the good performance of our method on several real-world datasets. (C) 2018 Elsevier B.V. All rights reserved. |
资助项目 | State Key Laboratory of Robotics[Y7C120E101] ; Distinguished Young Scholar Project of the Thousand Talents Program of China[Y5A1370101] ; Ministry of Science and Technology of China[2017YFC0804003] ; National Natural Science Foundation of China[61329302] |
WOS关键词 | Optimality Conditions ; Pattern-recognition ; Sparse ; Bci |
WOS研究方向 | Computer Science |
语种 | 英语 |
WOS记录号 | WOS:000444237900004 |
资助机构 | State Key Laboratory of Robotics ; Distinguished Young Scholar Project of the Thousand Talents Program of China ; Ministry of Science and Technology of China ; National Natural Science Foundation of China |
内容类型 | 期刊论文 |
源URL | [http://ir.sia.cn/handle/173321/22776] |
专题 | 沈阳自动化研究所_机器人学研究室 |
通讯作者 | Adam, Lukas |
作者单位 | 1.Southern University of Science and Technology, Shenzhen, Guangdong Province 518055, China 2.State key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences,Shenyang, Liaoning Province 110016, China |
推荐引用方式 GB/T 7714 | Adam, Lukas,Tang FZ,Si BL. Group feature selection with multiclass support vector machine[J]. NEUROCOMPUTING,2018,317:42-49. |
APA | Adam, Lukas,Tang FZ,&Si BL.(2018).Group feature selection with multiclass support vector machine.NEUROCOMPUTING,317,42-49. |
MLA | Adam, Lukas,et al."Group feature selection with multiclass support vector machine".NEUROCOMPUTING 317(2018):42-49. |
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