Two smooth support vector machines for ε -insensitive regression

Weizhe Gu, Wei Po Chen, Chun Hsu Ko, Yuh Jye Lee, Jein Shan Chen

研究成果: 雜誌貢獻期刊論文同行評審

3 引文 斯高帕斯(Scopus)

摘要

In this paper, we propose two new smooth support vector machines for ε-insensitive regression. According to these two smooth support vector machines, we construct two systems of smooth equations based on two novel families of smoothing functions, from which we seek the solution to ε-support vector regression (ε-SVR). More specifically, using the proposed smoothing functions, we employ the smoothing Newton method to solve the systems of smooth equations. The algorithm is shown to be globally and quadratically convergent without any additional conditions. Numerical comparisons among different values of parameter are also reported.

原文英語
頁(從 - 到)171-199
頁數29
期刊Computational Optimization and Applications
70
發行號1
DOIs
出版狀態已發佈 - 2018 五月 1

ASJC Scopus subject areas

  • 控制和優化
  • 計算數學
  • 應用數學

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