Extensive semi-quantitative regression
文献类型:期刊论文
作者 | Shao, Yuan-Hai1; Ye, Ya-Fen1; Wang, Yong-Cui2; Deng, Nai-Yang3 |
刊名 | neurocomputing |
出版日期 | 2016-12-19 |
卷号 | 218页码:26-36 |
关键词 | Machine learning Regression Extensive semi-quantitative regression Support vector machines Laplacian graph |
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. |
WOS标题词 | science & technology ; technology |
类目[WOS] | computer science, artificial intelligence |
研究领域[WOS] | computer science |
关键词[WOS] | support vector regression ; extreme learning-machine ; kernel approximation ; knowledge ; framework |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:000388053700004 |
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 |
作者单位 | 1.Zhejiang Univ Technol, Zhijiang Coll, Hangzhou 310024, Zhejiang, Peoples R China 2.Chinese Acad Sci, Northwest Inst Plateau Biol, Key Lab Adaptat & Evolut Plateau Biota, Xining 810001, Peoples R China 3.China Agr Univ, Coll Sci, Beijing 100083, Peoples R China |
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,2016,218:26-36. |
APA | Shao, Yuan-Hai,Ye, Ya-Fen,Wang, Yong-Cui,&Deng, Nai-Yang.(2016).Extensive semi-quantitative regression.neurocomputing,218,26-36. |
MLA | Shao, Yuan-Hai,et al."Extensive semi-quantitative regression".neurocomputing 218(2016):26-36. |
入库方式: OAI收割
来源:西北高原生物研究所
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