A parallel incremental extreme SVM classifier

doi:10.1016/j.neucom.2010.11.036

	A parallel incremental extreme SVM classifier
	He, Qing 1; Du, Changying 1,2; Wang, Qun 1,2; Zhuang, Fuzhen 1,2; Shi, Zhongzhi 1
	2011-09-01
发表期刊	NEUROCOMPUTING
ISSN	0925-2312
卷号	74 期号:16 页码:2532-2540
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.
关键词	Parallel extreme SVM (PESVM) MapReduce Incremental extreme SVM (IESVM) Parallel incremental extreme SVM (PIESVM)
DOI	10.1016/j.neucom.2010.11.036
收录类别	SCI
语种	英语
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
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000295106000016
出版者	ELSEVIER SCIENCE BV
引用统计	被引频次：35[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/12760
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.