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Fast instance selection for speeding up support vector machines

文献类型：期刊论文

作者Chen, Jingnian1; Zhang, Caiming2; Xue, Xiaoping3; Liu, Cheng-Lin4
刊名KNOWLEDGE-BASED SYSTEMS
出版日期2013-06-01
卷号45页码:1-7
关键词SVM Classification Multi-class Instance selection Clustering
英文摘要Support vector machine (SVM) has shown prominent performance for binary classification. How to effectively apply it to massive datasets with large number of classes and instances is still a serious challenge. Instance selection methods have been proposed and shown significant efficacy for reducing the training complexity of SVM, but more or less trade off the generalization performance. This paper presents an instance selection method especially for multi-class problems. With cluster centers of positive class as reference points instances are selected for each one-versus-rest SVM model. The purpose of clustering here is to improve the efficiency of instance selection, other than to select instances directly from clusters as previous methods did. Experiments on a wide variety of datasets demonstrate that the proposed method selects fewer instances than most competitive algorithms and keeps the highest classification accuracy on most datasets. Additionally, experimental results show that this method also performs superiorly for binary problems. (C) 2013 Elsevier B.V. All rights reserved.
WOS标题词Science & Technology ; Technology
类目[WOS]Computer Science, Artificial Intelligence
研究领域[WOS]Computer Science
关键词[WOS]LARGE DATA SETS ; CLASSIFIERS
收录类别SCI
语种英语
WOS记录号WOS:000318384200001
源URL[http://ir.ia.ac.cn/handle/173211/3080]  
专题自动化研究所_模式识别国家重点实验室_模式分析与学习团队
作者单位1.Shandong Univ Finance & Econ, Dept Informat & Comp Sci, Jinan 250014, Peoples R China
2.Shandong Univ, Sch Comp Sci & Technol, Jinan 250014, Peoples R China
3.Tongji Univ, Sch Elect & Informat, Shanghai 201804, Peoples R China
4.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Chen, Jingnian,Zhang, Caiming,Xue, Xiaoping,et al. Fast instance selection for speeding up support vector machines[J]. KNOWLEDGE-BASED SYSTEMS,2013,45:1-7.
APA Chen, Jingnian,Zhang, Caiming,Xue, Xiaoping,&Liu, Cheng-Lin.(2013).Fast instance selection for speeding up support vector machines.KNOWLEDGE-BASED SYSTEMS,45,1-7.
MLA Chen, Jingnian,et al."Fast instance selection for speeding up support vector machines".KNOWLEDGE-BASED SYSTEMS 45(2013):1-7.

入库方式： OAI收割

来源：自动化研究所

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