| 自适应误差惩罚支撑向量回归机 |
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| 引用本文： | 陈晓峰,王士同,曹苏群.自适应误差惩罚支撑向量回归机[J].电子与信息学报,2008,30(2):367-370. |
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| 作者姓名： | 陈晓峰 王士同 曹苏群 |
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| 作者单位： | 1. 江南大学信息学院,无锡,214122
2. 江南大学信息学院,无锡,214122;淮阴工学院机械系,淮安,223001 |
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| 基金项目： | 教育部优秀人才支持计划
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国家重点实验室基金
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教育部科学技术研究项目
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国防应用基础研究基金 |
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| 摘 要： | 该文提出一种支撑向量回归机AEPSVR。它首先用 -SVR求得一个近似的支撑向量回归函数，在此基础上，引入一种新自适应误差惩罚函数，通过迭代，得到鲁棒的支撑向量回归机。该方法因以 -SVR为基础，故可以应用各种求解SVR的优化算法。实验表明，该支撑向量回归机AEPSVR能显著地降低离群点的影响，具有良好的泛化性能。
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| 关 键 词： | 支撑向量回归 离群点 自适应误差惩罚 |
| 文章编号： | 1009-5896（2008）02-0367-04 |
| 收稿时间： | 2006-07-20 |
| 修稿时间： | 2007-01-31 |
SVR with Adaptive Error Penalization |
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| Chen Xiao-feng,Wang Shi-tong,Cao Su-qun.SVR with Adaptive Error Penalization[J].Journal of Electronics & Information Technology,2008,30(2):367-370. |
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| Authors: | Chen Xiao-feng Wang Shi-tong Cao Su-qun |
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| Affiliation: | School of Information, Southern Yangtz University, Wuxi 214122, China; Department of Mechanical Engineering, Huaiyin Institute of Technology, Huaian 223001, China |
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| Abstract: | A novel support vector regression method AEPSVR is proposed in this paper. First, an approximate regression function is obtained using -SVR method, and then a new adaptive error penalization function is introduced to enhance the robust performance of SVR such that a robust support vector regression is derived. Because the proposed AEPSVR here is based on -SVR, so various optimization methods for SVR can be used. Experimental results show that the proposed AEPSVR can reduce the affect of outliers, and have the very good generalization capability. |
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| Keywords: | Support Vector Regression (SVR) Outlier Adaptive Error Penalization (AEP) |
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