Extensive semi-quantitative regression

	Extensive semi-quantitative regression
	Shao, Yuan-Hai ; Ye, Ya-Fen ; Wang, Yong-Cui ; Deng, Nai-Yang
刊名	NEUROCOMPUTING
	2016-12-19
英文摘要	In this paper, we propose and solve a new machine learning problem called the extensive semi-quantitative regression, where the information about some target values is incomplete; we only know their lower bounds and/or upper bounds instead of their exact values. To employ the information efficiently in extensive semi-quantitative regression, we introduce a local graph to capture the geometric structure for the samples with the exact target values and the target bounds, and construct a graph-based support vector regressor, called ESQ-SVR. The efficiency of our ESQ-SVR is supported by the results of preliminary experiments conducted on both the artificial and real world datasets. (C) 2016 Elsevier B.V. All rights reserved.
内容类型	期刊论文
源URL	[http://ir.nwipb.ac.cn/handle/363003/6674]
专题	西北高原生物研究所_中国科学院西北高原生物研究所
推荐引用方式 GB/T 7714	Shao, Yuan-Hai,Ye, Ya-Fen,Wang, Yong-Cui,et al. Extensive semi-quantitative regression[J]. NEUROCOMPUTING,2016.
APA	Shao, Yuan-Hai,Ye, Ya-Fen,Wang, Yong-Cui,&Deng, Nai-Yang.(2016).Extensive semi-quantitative regression.NEUROCOMPUTING.
MLA	Shao, Yuan-Hai,et al."Extensive semi-quantitative regression".NEUROCOMPUTING (2016).