计算机科学 ›› 2011, Vol. 38 ›› Issue (3): 243-247.

• 人工智能 • 上一篇    下一篇

一个新的多项式光滑支持向量机

袁华强,涂文根,熊金志,刘婷婷   

  1. (东莞理工学院工程技术研究院 东莞523808);(华南理工大学计算机科学与工程学院 广州510006)
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金(60573029,60773048,60773050)资助。

New Polynomial Smooth Support Vector Machine

YUAN Hua-qiang,TU Wen-gen,XIONG Jin-zhi,LIU Ting-ting   

  • Online:2018-11-16 Published:2018-11-16

摘要: 光滑支持向量机(SSVM)是支持向量机(SVM)的快速求解模型,拥有更快的求解速度和训练效果。基于光滑的分段多项式函数和插值思想推导出一个新的光滑函数,从而可以更好地逼近正号函数。通过所得到的新光滑函数改进多项式光滑支持向量机模型(PSSVM),得到了更新的光滑支持向量机模型。还给出了新光滑函数的逼近性能和精度分析以及新模型的收敛性证明和最优解的逼近上限。数值实验表明,所提出的新光滑支持向量机模型性能优于PSSVM模型。

关键词: 模式识别,多项式光滑支持向量机,样条多项式,光滑技术

Abstract: Smooth Support Vector Machine(SSVM),which has better advantage than Support Vector Machine(SVM),is a model of SVM for ctuick solving. We got a new smooth function for approximating the plus function by interpolation base on smooth piecewise polynomial functions. We found a new model of Smooth Support Vector Machine by improving the model of Polynomial Smooth Support Vector Machine using the new smooth function. Performances of approaching and approximate error were given for the new smooth function, as well as the study of convergence and the approximation limit of optimum for the new model. Obviously numeric experiment shows that the new model has better performance than PSSVM.

Key words: Pattern recognition, Polynomial smooth support vector machine, Spline polynomial, Smooth technology

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