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| theoretically optimal parameter choices for support vector regression machines with noisy input | |
| Wang ST; Zhu JG; Chung FL; Lin Q; Hu DW | |
| 2005 | |
| Source | SOFT COMPUTING
 |
| ISSN | 1432-7643 |
| Volume | 9Issue:10Pages:732-741 |
| Indexed Type | sci ; acm ; cnki |
| Abstract | 在大规模事件通知服务的通用框架基础上,通过分析提出了复合事件检测的基本模型,并对照该基本模型剖析了复合事件检测的四种基本方法:基于Petri网、基于匹配树、基于图以及基于自动机的检测方法,评价了各种方法的优缺点,为开发适用于新的应用需求的复合事件检测技术打下了基础。 |
| Keyword | 复合事件,检测regularized Linear Regression Support Vectors Huber Loss Functions Norm-r Loss Functions |
| Department | So Yangtze Univ, Sch Informat Engn, Wuxi, Peoples R China. Nanjing Univ Sci & Tech, Dept Comp Sci & Engn, Nanjing, Peoples R China. HongKong Polytech Univ, Dept Comp, Hong Kong, Hong Kong, Peoples R China. Natl Def Univ Sci & Tech, Sch Automat, Changsha, Peoples R China. Chinese Acad Sci, Inst Software, Comp Sci Lab, Beijing, Peoples R China. |
| Subject | Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications |
| Language | 英语 |
| Content Type | 期刊论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/12442 |
| Collection | 中国科学院软件研究所 |
| Recommended Citation GB/T 7714 | Wang ST,Zhu JG,Chung FL,et al. theoretically optimal parameter choices for support vector regression machines with noisy input[J]. SOFT COMPUTING,2005,9(10):732-741. |
| APA | Wang ST,Zhu JG,Chung FL,Lin Q,&Hu DW.(2005).theoretically optimal parameter choices for support vector regression machines with noisy input.SOFT COMPUTING,9(10),732-741. |
| MLA | Wang ST,et al."theoretically optimal parameter choices for support vector regression machines with noisy input".SOFT COMPUTING 9.10(2005):732-741. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| theoretically optima（428KB） | 开放获取 | -- | Application Full Text | |||
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