Support vector analysis of large-scale data based on kernels with iteratively increasing order | |
Chen, Bo-Wei1; He, Xinyu1; Ji, Wen2; Rho, Seungmin3; Kung, Sun-Yuan1 | |
刊名 | JOURNAL OF SUPERCOMPUTING
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2016-09-01 | |
卷号 | 72期号:9页码:3297-3311 |
关键词 | Support vector analysis Big data analysis Kernel ridge regression (KRR) Ridge support vector machine (Ridge SVM) |
ISSN号 | 0920-8542 |
DOI | 10.1007/s11227-015-1404-1 |
英文摘要 | 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. |
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 |
语种 | 英语 |
出版者 | SPRINGER |
WOS记录号 | WOS:000382094500002 |
内容类型 | 期刊论文 |
源URL | [http://119.78.100.204/handle/2XEOYT63/8203] ![]() |
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. |
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