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Group feature selection with multiclass support vector machine
Tang FZ(唐凤珍)1; Adam, Lukas2; Si BL(斯白露)1
作者部门机器人学研究室
关键词Group Feature Selection Support Vector Machine Multiclass Support Vector Machine Alternating Direction Method Of Multipliers Eeg Channel Selection
发表期刊NEUROCOMPUTING
ISSN0925-2312
2018-11-23
卷号317页码:42-49
收录类别SCI ; EI
EI收录号20183605788718
WOS记录号WOS:000444237900004
产权排序1
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
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.

语种英语
WOS类目Computer Science, Artificial Intelligence
关键词[WOS]Optimality Conditions ; Pattern-recognition ; Sparse ; Bci
WOS研究方向Computer Science
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]
引用统计
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/22776
专题机器人学研究室
通讯作者Adam, Lukas
作者单位1.State key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences,Shenyang, Liaoning Province 110016, China
2.Southern University of Science and Technology, Shenzhen, Guangdong Province 518055, China
推荐引用方式
GB/T 7714
Tang FZ,Adam, Lukas,Si BL. Group feature selection with multiclass support vector machine[J]. NEUROCOMPUTING,2018,317:42-49.
APA Tang FZ,Adam, Lukas,&Si BL.(2018).Group feature selection with multiclass support vector machine.NEUROCOMPUTING,317,42-49.
MLA Tang FZ,et al."Group feature selection with multiclass support vector machine".NEUROCOMPUTING 317(2018):42-49.
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