Support vector analysis of large-scale data based on kernels with iteratively increasing order

doi:10.1007/s11227-015-1404-1

	Support vector analysis of large-scale data based on kernels with iteratively increasing order
	Chen, Bo-Wei 1; He, Xinyu 1; Ji, Wen 2; Rho, Seungmin 3; Kung, Sun-Yuan 1
	2016-09-01
发表期刊	JOURNAL OF SUPERCOMPUTING
ISSN	0920-8542
卷号	72 期号:9 页码:3297-3311
摘要	This study presents an efficient approach for large-scale data training. To deal with the rapid growth of training complexity for big data analysis, a novel mechanism, which utilizes fast kernel ridge regression (Fast KRR) and ridge support vector machines (Ridge SVMs), is proposed in this study. Firstly, Fast KRR based on low-order intrinsic-space computation is developed. Preliminary support vectors are located by using Fast KRR. Subsequently, the system iteratively removes indiscriminant data until a Ridge SVM with a high-order kernel can accommodate the data size and generate a hyperplane. To speed up the removal of indiscriminant data, quick intrinsic-matrix rebuilding is devised in the iteration. Experiments on three databases were carried out for evaluating the proposed method. Moreover, different percentages of data removal were examined in the test. The results show that the performance is enhanced by as high as 78-152 folds. Besides, the mechanisms still maintain the accuracy. These findings thereby demonstrate the effectiveness of the proposed idea.
关键词	Support vector analysis Big data analysis Kernel ridge regression (KRR) Ridge support vector machine (Ridge SVM)
DOI	10.1007/s11227-015-1404-1
收录类别	SCI
语种	英语
资助项目	Ministry of Science and Technology, the Republic of China[103-2917-I-564-058] ; Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences[2015-4]
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:000382094500002
出版者	SPRINGER
引用统计	被引频次：9[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/2XEOYT63/8204
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Chen, Bo-Wei
作者单位	1.Princeton Univ, Dept Elect Engn, Princeton, NJ 08544 USA 2.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 3.Sungkyul Univ, Dept Multimedia, Anyang, South Korea
推荐引用方式 GB/T 7714	Chen, Bo-Wei,He, Xinyu,Ji, Wen,et al. Support vector analysis of large-scale data based on kernels with iteratively increasing order[J]. JOURNAL OF SUPERCOMPUTING,2016,72(9):3297-3311.
APA	Chen, Bo-Wei,He, Xinyu,Ji, Wen,Rho, Seungmin,&Kung, Sun-Yuan.(2016).Support vector analysis of large-scale data based on kernels with iteratively increasing order.JOURNAL OF SUPERCOMPUTING,72(9),3297-3311.
MLA	Chen, Bo-Wei,et al."Support vector analysis of large-scale data based on kernels with iteratively increasing order".JOURNAL OF SUPERCOMPUTING 72.9(2016):3297-3311.