Groupwise Retargeted Least-Squares Regression
文献类型：期刊论文
| 作者 | Wang, Lingfeng ; Pan, Chunhong
|
| 刊名 | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
 |
| 出版日期 | 2018-04-01 |
| 卷号 | 29期号:4页码:1352-1358 |
| 关键词 | Groupwise Least-squares Regression (Lsr) Multicategory Classification Retargeted Least-squares Regression (Relsr) |
| DOI | 10.1109/TNNLS.2017.2651169 |
| 文献子类 | Article |
| 英文摘要 | In this brief, we propose a new groupwise retargeted least squares regression (GReLSR) model for multicategory classification. The main motivation behind GReLSR is to utilize an additional regularization to restrict the translation values of ReLSR, so that they should be similar within same class. By analyzing the regression targets of ReLSR, we propose a new formulation of ReLSR, where the translation values are expressed explicitly. On the basis of the new formulation, discriminative least-squares regression can be regarded as a special case of ReLSR with zero translation values. Moreover, a groupwise constraint is added to ReLSR to form the new GReLSR model. Extensive experiments on various machine leaning data sets illustrate that our method outperforms the current state-of-the-art approaches. |
| WOS关键词 | FEATURE-SELECTION ; CLASSIFICATION ; ALGORITHM ; MACHINE |
| WOS研究方向 | Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000427859600047 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/19748]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_遥感图像处理团队 |
| 作者单位 | Chinese Acad Sci, Inst Automat, Dept Natl Lab Pattern Recognit, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Lingfeng,Pan, Chunhong. Groupwise Retargeted Least-Squares Regression[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2018,29(4):1352-1358. |
| APA | Wang, Lingfeng,&Pan, Chunhong.(2018).Groupwise Retargeted Least-Squares Regression.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,29(4),1352-1358. |
| MLA | Wang, Lingfeng,et al."Groupwise Retargeted Least-Squares Regression".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 29.4(2018):1352-1358. |
入库方式： OAI收割
来源：自动化研究所
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