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Unsupervised Feature Selection with Local Structure Learning
Yang, Sheng1; Nie, Feiping1; Li, Xuelong2
2018-08-29
Conference Name25th IEEE International Conference on Image Processing, ICIP 2018
Source Publication2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings
Pages3398-3402
Conference Date2018-10-07
Conference PlaceAthens, Greece
PublisherIEEE Computer Society
Contribution Rank2
AbstractConventional graph-based unsupervised feature selection approaches carry out the feature selection requiring two stages: first, constructing the data similarity matrix and next performing feature selection. In this way, the similarity matrix is invariably kept unchanged, totally separated from the process of feature selection and the performance of feature selection highly depends on the initially constructed similarity matrix. In order to address this problem, a novel unsupervised feature selection method is proposed in this paper where constructing similarity matrix and performing feature selection are together incorporated into a coherent model. Besides, the constructed similarity matrix has k connected components (k is the number of data clusters). At last, five state-of-the-art unsupervised feature selection methods are compared to validate the effectiveness of the proposed method. © 2018 IEEE.
Department光学影像学习与分析中心
DOI10.1109/ICIP.2018.8451101
Indexed ByEI
ISBN9781479970612
Language英语
ISSN15224880
EI Accession Number20191206646371
Citation statistics
Document Type会议论文
Identifierhttp://ir.opt.ac.cn/handle/181661/31348
Collection光学影像学习与分析中心
Affiliation1.School of Computer Science, Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Xi'an, Shaanxi; 710072, China;
2.Center for OPTical IMagery Analysis and Learning (OPTIMAL), State Key Laboratory of Transient Optics and Photonics, Xi'An Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, Shaanxi; 710119, China
Recommended Citation
GB/T 7714
Yang, Sheng,Nie, Feiping,Li, Xuelong. Unsupervised Feature Selection with Local Structure Learning[C]:IEEE Computer Society,2018:3398-3402.
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