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A new maximum margin algorithm for one-class problems and its boosting implementation

文献类型:期刊论文

作者Tao, Q; Wu, GW; Wang, J
刊名PATTERN RECOGNITION
出版日期2005-07-01
卷号38期号:7页码:1071-1077
关键词one-class problems outliers statistical learning theory support vector machines margin boosting
英文摘要In this paper, each one-class problem is regarded as trying to estimate a function that is positive on a desired slab and negative on the complement. The main advantage of this viewpoint is that the loss function and the expected risk can be defined to ensure that the slab can contain as many samples as possible. Inspired by the nature of SVMs, the intuitive margin is also defined. As a result, a new linear optimization problem to maximize the margin and some theoretically motivated learning algorithms are obtained. Moreover, the proposed algorithms can be implemented by boosting techniques to solve nonlinear one-class classifications. (c) 2005 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
WOS标题词Science & Technology ; Technology
类目[WOS]Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
研究领域[WOS]Computer Science ; Engineering
关键词[WOS]SUPPORT
收录类别SCI
语种英语
WOS记录号WOS:000228700900010
公开日期2015-12-24
源URL[http://ir.ia.ac.cn/handle/173211/9182]  
专题自动化研究所_09年以前成果
作者单位Chinese Acad Sci, Inst Automat, Key Lab Complex Syst & Intelligence Sci, Beijing 100080, Peoples R China
推荐引用方式
GB/T 7714
Tao, Q,Wu, GW,Wang, J. A new maximum margin algorithm for one-class problems and its boosting implementation[J]. PATTERN RECOGNITION,2005,38(7):1071-1077.
APA Tao, Q,Wu, GW,&Wang, J.(2005).A new maximum margin algorithm for one-class problems and its boosting implementation.PATTERN RECOGNITION,38(7),1071-1077.
MLA Tao, Q,et al."A new maximum margin algorithm for one-class problems and its boosting implementation".PATTERN RECOGNITION 38.7(2005):1071-1077.

入库方式: OAI收割

来源:自动化研究所

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