ISSN 1000-1239 CN 11-1777/TP

• 人工智能 •

### 光滑CHKS孪生支持向量回归机

1. 1(中国矿业大学计算机科学与技术学院 江苏徐州 221116); 2(中国科学院计算技术研究所智能信息处理重点实验室 北京 100190); 3(广西民族大学信息科学与工程学院 南宁 530006) (hhj-025@163.com)
• 出版日期: 2015-03-01
• 基金资助:
基金项目：国家“九七三”重点基础研究发展计划基金项目(2013CB329502)；国家自然科学基金项目(61379101)

### Smooth CHKS Twin Support Vector Regression

Huang Huajuan1,2,3, Ding Shifei1,2, Shi Zhongzhi2

1. 1(School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, Jiangsu 221116); 2(Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190); 3(College of Information Science and Engineering, Guangxi University for Nationalities, Nanning 530006)
• Online: 2015-03-01

Abstract: Twin support vector regression (TSVR) was proposed recently as a novel regressor that tries to find a pair of nonparallel planes, i.e., ε insensitive down- and up- bounds, by solving two related SVM-type problems. However, it may incur suboptimal solution since its objective function is positive semi-definite and it is lack of complexity control. In order to address this shortcoming, smooth twin support vector regression (STSVR) is introduced using sigmoid function as smoothing technique to convert the original problems into unconstrained minimization, which can improve the training speed. However, its accuracy needs to be improved. In this paper, aiming at the low approximation ability of sigmoid function of STSVR, using CHKS (chen-harker-kanzow-smale) function which has better approximation ability as the smooth function, a new version of smooth TSVR called smooth CHKS twin support vector regression (SCTSVR) model is proposed. In SCTSVR, CHKS function is used to approximate the non-differential term of twin support vector regression. Then Newton-Armijo algorithm is used to solve the corresponding model. We have proved that SCTSVR is not only strictly convex, but also can meet the arbitrary order smooth performance. Meanwhile, the experimental results on several artificial and benchmark datasets show that SCTSVR has better regression performance than STSVR.