Initialization Independent Clustering With Actively Self-Training Method

CORC > 西安光学精密机械研究所 > 中国科学院西安光学精密机械研究所 > 光学影像学习与分析中心

	Initialization Independent Clustering With Actively Self-Training Method
	Nie, Feiping 1; Xu, Dong 2; Li, Xuelong 3
刊名	ieee transactions on systems man and cybernetics part b-cybernetics
	2012-02-01
卷号	42 期号:1 页码:17-27
关键词	Active learning initialization independent clustering self-training spectral clustering (SC)
ISSN号	1083-4419
产权排序	3
合作状况	国际
中文摘要	the results of traditional clustering methods are usually unreliable as there is not any guidance from the data labels, while the class labels can be predicted more reliable by the semisupervised learning if the labels of partial data are given. in this paper, we propose an actively self-training clustering method, in which the samples are actively selected as training set to minimize an estimated bayes error, and then explore semisupervised learning to perform clustering. traditional graph-based semisupervised learning methods are not convenient to estimate the bayes error; we develop a specific regularization framework on graph to perform semisupervised learning, in which the bayes error can be effectively estimated. in addition, the proposed clustering algorithm can be readily applied in a semisupervised setting with partial class labels. experimental results on toy data and real-world data sets demonstrate the effectiveness of the proposed clustering method on the unsupervised and the semisupervised setting. it is worthy noting that the proposed clustering method is free of initialization, while traditional clustering methods are usually dependent on initialization.
英文摘要	the results of traditional clustering methods are usually unreliable as there is not any guidance from the data labels, while the class labels can be predicted more reliable by the semisupervised learning if the labels of partial data are given. in this paper, we propose an actively self-training clustering method, in which the samples are actively selected as training set to minimize an estimated bayes error, and then explore semisupervised learning to perform clustering. traditional graph-based semisupervised learning methods are not convenient to estimate the bayes error; we develop a specific regularization framework on graph to perform semisupervised learning, in which the bayes error can be effectively estimated. in addition, the proposed clustering algorithm can be readily applied in a semisupervised setting with partial class labels. experimental results on toy data and real-world data sets demonstrate the effectiveness of the proposed clustering method on the unsupervised and the semisupervised setting. it is worthy noting that the proposed clustering method is free of initialization, while traditional clustering methods are usually dependent on initialization.
学科主题	automation & control systems ; computer science ; artificial intelligence ; computer science ; cybernetics
WOS标题词	science & technology ; technology
类目[WOS]	automation & control systems ; computer science, artificial intelligence ; computer science, cybernetics
研究领域[WOS]	automation & control systems ; computer science
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:000302096700002
公开日期	2012-09-03
内容类型	期刊论文
源URL	[http://ir.opt.ac.cn/handle/181661/20258]
专题	西安光学精密机械研究所_光学影像学习与分析中心
作者单位	1.Univ Texas Arlington, Dept Comp Sci & Engn, Arlington, TX 76019 USA 2.Nanyang Technol Univ, Sch Comp Engn, Singapore 639798, Singapore 3.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr OPT IMagery Anal & Learning OPTIMAL, Xian 710119, Peoples R China
推荐引用方式 GB/T 7714	Nie, Feiping,Xu, Dong,Li, Xuelong. Initialization Independent Clustering With Actively Self-Training Method[J]. ieee transactions on systems man and cybernetics part b-cybernetics,2012,42(1):17-27.
APA	Nie, Feiping,Xu, Dong,&Li, Xuelong.(2012).Initialization Independent Clustering With Actively Self-Training Method.ieee transactions on systems man and cybernetics part b-cybernetics,42(1),17-27.
MLA	Nie, Feiping,et al."Initialization Independent Clustering With Actively Self-Training Method".ieee transactions on systems man and cybernetics part b-cybernetics 42.1(2012):17-27.