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A generalized S-K algorithm for learning v-SVM classifiers
Tao, Q; Wu, GW; Wang, J
2004-07-16
发表期刊PATTERN RECOGNITION LETTERS
卷号25期号:10页码:1165-1171
文章类型Article
摘要The S-K algorithm (Schlesinger-Kozinec algorithm) and the modified kernel technique due to Friess et al. have been recently combined to solve SVM with L-2 cost function. In this paper, we generalize S-K algorithm to be applied for soft convex hulls. As a result, our algorithm can solve v-SVM based on L-1 cost function. Simple in nature, our soft algorithm is essentially a algorithm for finding the epsilon-optimal nearest points between two soft convex hulls. As only the vertexes of the hard convex hulls are used, the obvious superiority of our algorithm is that it has almost the same computational cost as that of the hard S-K algorithm. The theoretical analysis and some experiments demonstrate the performance of our algorithm. (C) 2004 Elsevier B.V. All rights reserved.
关键词Statistical Machine Learning Support Vector Machines Classification V-svm S-k Algorithms Soft Convex Hulls
WOS标题词Science & Technology ; Technology
关键词[WOS]ITERATIVE ALGORITHM ; POINT
收录类别SCI
语种英语
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000222392000008
引用统计
被引频次:18[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/9055
专题09年以前成果
作者单位1.New Star Res Inst Appl Tech, Hefei 230031, Peoples R China
2.Chinese Acad Sci, Comp Technol Inst, Bioinformat Lab, Beijing 100080, Peoples R China
3.Chinese Acad Sci, Inst Automat, Beijing 100080, Peoples R China
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Tao, Q,Wu, GW,Wang, J. A generalized S-K algorithm for learning v-SVM classifiers[J]. PATTERN RECOGNITION LETTERS,2004,25(10):1165-1171.
APA Tao, Q,Wu, GW,&Wang, J.(2004).A generalized S-K algorithm for learning v-SVM classifiers.PATTERN RECOGNITION LETTERS,25(10),1165-1171.
MLA Tao, Q,et al."A generalized S-K algorithm for learning v-SVM classifiers".PATTERN RECOGNITION LETTERS 25.10(2004):1165-1171.
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