Convex ensemble learning with sparsity and diversity

	Convex ensemble learning with sparsity and diversity
	Yin, Xu-Cheng; Huang, Kaizhu; Yang, Chun; Hao, Hong-Wei
发表期刊	INFORMATION FUSION
	2014-11-01
卷号	20 页码:49-59
文章类型	Article
摘要	Classifier ensemble has been broadly studied in two prevalent directions, i.e., to diversely generate classifier components, and to sparsely combine multiple classifiers. While most current approaches are emphasized on either sparsity or diversity only, we investigate classifier ensemble focused on both in this paper. We formulate the classifier ensemble problem with the sparsity and diversity learning in a general mathematical framework, which proves beneficial for grouping classifiers. In particular, derived from the error-ambiguity decomposition, we design a convex ensemble diversity measure. Consequently, accuracy loss, sparseness regularization, and diversity measure can be balanced and combined in a convex quadratic programming problem. We prove that the final convex optimization leads to a closed-form solution, making it very appealing for real ensemble learning problems. We compare our proposed novel method with other conventional ensemble methods such as Bagging, least squares combination, sparsity learning, and AdaBoost, extensively on a variety of UCI benchmark data sets and the Pascal Large Scale Learning Challenge 2008 webspam data. Experimental results confirm that our approach has very promising performance. (C) 2013 Elsevier B.V. All rights reserved.
关键词	Classifier Ensemble Sparsity Diversity Convex Quadratic Programming
WOS标题词	Science & Technology ; Technology
关键词[WOS]	NEURAL-NETWORKS ; COMBINING CLASSIFIERS ; MULTIPLE CLASSIFIERS ; COMBINATION ; SELECTION ; RECOGNITION ; REGRESSION
收录类别	SCI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods
WOS记录号	WOS:000337863500007
引用统计	被引频次：37[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/173211/40867
专题	复杂系统认知与决策实验室_听觉模型与认知计算
推荐引用方式 GB/T 7714	Yin, Xu-Cheng,Huang, Kaizhu,Yang, Chun,et al. Convex ensemble learning with sparsity and diversity[J]. INFORMATION FUSION,2014,20:49-59.
APA	Yin, Xu-Cheng,Huang, Kaizhu,Yang, Chun,&Hao, Hong-Wei.(2014).Convex ensemble learning with sparsity and diversity.INFORMATION FUSION,20,49-59.
MLA	Yin, Xu-Cheng,et al."Convex ensemble learning with sparsity and diversity".INFORMATION FUSION 20(2014):49-59.