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A parallel incremental extreme SVM classifier

文献类型：期刊论文

作者He, Qing1; Du, Changying1,2; Wang, Qun1,2; Zhuang, Fuzhen1,2; Shi, Zhongzhi1
刊名NEUROCOMPUTING
出版日期2011-09-01
卷号74期号:16页码:2532-2540
关键词Parallel extreme SVM (PESVM) MapReduce Incremental extreme SVM (IESVM) Parallel incremental extreme SVM (PIESVM)
ISSN号0925-2312
DOI10.1016/j.neucom.2010.11.036
英文摘要The classification algorithm extreme SVM (ESVM) proposed recently has been proved to provide very good generalization performance in relatively short time, however, it is inappropriate to deal with large-scale data set due to the highly intensive computation. Thus we propose to implement an efficient parallel ESVM (PESVM) based on the current and powerful parallel programming framework MapReduce. Furthermore, we investigate that for some new coming training data, it is brutal for ESVM to always retrain a new model on all training data (including old and new coming data). Along this line, we develop an incremental learning algorithm for ESVM (IESVM), which can meet the requirement of online learning to update the existing model. Following that we also provide the parallel version of IESVM (PIESVM), which can solve both the large-scale problem and the online problem at the same time. The experimental results show that the proposed parallel algorithms not only can tackle large-scale data set, but also scale well in terms of the evaluation metrics of speedup, sizeup and scaleup. It is also worth to mention that PESVM, IESVM and PIESVM are much more efficient than ESVM, while the same solutions as ESVM are exactly obtained. (C) 2011 Elsevier B.V. All rights reserved.
资助项目National Natural Science Foundation of China[60933004] ; National Natural Science Foundation of China[60975039] ; National Natural Science Foundation of China[61035003] ; National Natural Science Foundation of China[60903141] ; National Natural Science Foundation of China[61072085] ; National Basic Research Priorities Programme[2007CB311004] ; National Science and Technology Support Plan[2006BAC08B06]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000295106000016
出版者ELSEVIER SCIENCE BV
源URL[http://119.78.100.204/handle/2XEOYT63/12759]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者He, Qing
作者单位1.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Grad Sch, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 He, Qing,Du, Changying,Wang, Qun,et al. A parallel incremental extreme SVM classifier[J]. NEUROCOMPUTING,2011,74(16):2532-2540.
APA He, Qing,Du, Changying,Wang, Qun,Zhuang, Fuzhen,&Shi, Zhongzhi.(2011).A parallel incremental extreme SVM classifier.NEUROCOMPUTING,74(16),2532-2540.
MLA He, Qing,et al."A parallel incremental extreme SVM classifier".NEUROCOMPUTING 74.16(2011):2532-2540.

入库方式： OAI收割

来源：计算技术研究所

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