首页|Application of smoothing technique on twin support vector hypersphere

Application of smoothing technique on twin support vector hypersphere

扫码查看
原文链接
  • NETL
  • NSTL
  • 万方数据
  • 维普
In order to improve the learning speed and reduce computational complexity of twin support vector hypersphere (TSVH),this paper presents a smoothed twin support vector hypersphere (STSVH) based on the smoothing technique.STSVH can generate two hyperspheres with each one covering as many samples as possible from the same class respectively.Additionally,STSVH only solves a pair of unconstraint differentiable quadratic programming problems (QPPs) rather than a pair of constraint dual QPPs which makes STSVH faster than the TSVH.By considering the differentiable characteristics of STSVH,a fast Newton-Armijo algorithm is used for solving STSVH.Numerical experiment results on normally distributed clustered datasets (NDC) as well as University of California Irvine (UCI) data sets indicate that the significant advantages of the proposed STSVH in terms of efficiency and generalization performance.

twin support vector hypersphereNewton-Armijo algorithmsmoothing approximation functionunconstraint differentiable optimization

Wu Qing、Gao Xiaofeng、Fan Jiulun、Zhang Hengchang

展开 >

School of Automation, Xi'an University of Posts and Telecommunications, Xi'an 710121, China

School of Telecommunication and Information Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China

This work was supported by the National Natural Science Foundation of ChinaKey Research Project of Shanxi ProvinceInternational S&T Cooperation Program of Shanxi Province

518754572019GY-0612019KW-056.

2020

中国邮电高校学报(英文版)
北京邮电大学

中国邮电高校学报(英文版)

CSCDEI
影响因子：0.419
ISSN：1005-8885
年,卷(期)：2020.27(3)
  • 1
  • 2