计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (29): 179-181.

• 数据库与信息处理 • 上一篇    下一篇

基于Hermite插值的SVM研究

范艳峰1,2,张德贤2,何华灿1   

  1. 1.西北工业大学 计算机学院,西安 710072
    2.河南工业大学 信息科学与工程学院,郑州 450001
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-10-11 发布日期:2007-10-11
  • 通讯作者: 范艳峰

SVM research based on Hermite interpolation

FAN Yan-feng1,2,ZHANG De-xian2,HE Hua-can1   

  1. 1.College of Computer Science,Northwest Polytechnical University,Xi’an 710072,China
    2.College of Information Science and Engineering,Henan University of Technology,Zhengzhou 450052,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-10-11 Published:2007-10-11
  • Contact: FAN Yan-feng

摘要: 在传统SVM的分类求解算法中,由于严格凸的无约束最优化问题中单变量函数x+是不可微的,不能使用通常的最优化的算法进行求解。三次Hermite插值多项式光滑的支持向量机模型采用的是一种多项式光滑技术,用三次Hermite插值多项式代替单变量函数x+,将原来不可微的模型变为可微的模型,并且给出了三次Hermite插值多项式光滑化单变量函数x+的推导过程。使用UCI机器学习数据集中的数据,通过实验验证了该模型的有效性。

关键词: 支持向量机, Hermite插值, 多项式光滑

Abstract: In traditional SVM solution algorithms,objective function is a strictly convex unconstrained optimization problem,but is not differentiable due to x+,which precludes the use of most used optimization algorithms.Polynomial smooth techniques are applied to SVM model and replace x+ by a very accurate smooth approximation that is Hermite Interpolation polynomial,thus the undifferential model is converted into a differential model.The deduction procedure of Hermite Interpolation polynomial smoothing x+ is extended.Experiments with UCI datasets show the validity of the model.

Key words: SVM, Hermite interpolation, polynomial smooth