A closed-form reduction of multi-class cost-sensitive learning to weighted multi-class learning

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	A closed-form reduction of multi-class cost-sensitive learning to weighted multi-class learning
	Xia, Fen 1; Yang, Yan-wu 1; Zhou, Liang 1; Li, Fuxin 1; Cai, Min 2; Zeng, Daniel D.1,3
发表期刊	PATTERN RECOGNITION
	2009-07-01
卷号	42 期号:7 页码:1572-1581
文章类型	Article
摘要	in cost-sensitive learning, misclassification costs can vary for different classes. This paper investigates an approach reducing a multi-class cost-sensitive learning to a standard classification task based on the data space expansion technique developed by Abe et al., which coincides with Elkan's reduction with respect to binary classification tasks. Using this proposed reduction approach, a cost-sensitive learning problem can be solved by considering a standard 0/1 loss classification problem on a new distribution determined by the cost matrix. We also propose a new weighting mechanism to solve the reduced standard classification problem, based on a theorem stating that the empirical loss on independently identically distributed samples from the new distribution is essentially the same as the loss on the expanded weighted training set. Experimental results on several synthetic and benchmark datasets show that our weighting approach is more effective than existing representative approaches for cost-sensitive learning. (C) 2008 Elsevier Ltd. All rights reserved.
关键词	Cost-sensitive Learning Supervised Learning Statistical Learning Theory Classification
WOS标题词	Science & Technology ; Technology
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000265365500031
引用统计	被引频次：14[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/173211/3538
专题	多模态人工智能系统全国重点实验室_平行智能技术与系统团队
作者单位	1.Chinese Acad Sci, Key Lab Complex Syst & Intelligence Sci, Inst Automat, Beijing 100864, Peoples R China 2.Beijing Jaiotong Univ, Dept Comp Sci, Beijing, Peoples R China 3.Univ Arizona, Dept Management Informat Syst, Tucson, AZ 85721 USA
推荐引用方式 GB/T 7714	Xia, Fen,Yang, Yan-wu,Zhou, Liang,et al. A closed-form reduction of multi-class cost-sensitive learning to weighted multi-class learning[J]. PATTERN RECOGNITION,2009,42(7):1572-1581.
APA	Xia, Fen,Yang, Yan-wu,Zhou, Liang,Li, Fuxin,Cai, Min,&Zeng, Daniel D..(2009).A closed-form reduction of multi-class cost-sensitive learning to weighted multi-class learning.PATTERN RECOGNITION,42(7),1572-1581.
MLA	Xia, Fen,et al."A closed-form reduction of multi-class cost-sensitive learning to weighted multi-class learning".PATTERN RECOGNITION 42.7(2009):1572-1581.