计算机科学 ›› 2012, Vol. 39 ›› Issue (7): 222-224.

• 人工智能 • 上一篇    下一篇

基于支持向量机分类问题的勒让德核函数

张瑞,王文剑,张亚丹,孙芳玲   

  1. (山东理工大学理学院 淄博 255049) (山西大学计算智能与中文信息处理教育部重点实验室 太原 030006) (山西大学计算机与信息技术学院 太原 030006)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Legendre Kernel Function for Support Vector Classification

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

摘要: 基于勒让德正交多项式,提出了一类新的核函数—勒让德核函数。在双螺旋集和标准UCI数据集上的实验表明,在鲁棒性与泛化性能方面,该核函数比常用的核函数(多项式核、高斯径向基核等)具有更好的表现,而且其参数仅在自然数中取值,能大大缩短参数优化时间。

关键词: 支持向量机,核函数,模型选择

Abstract: This paper presented a new set of kernel function-Legendre kernel function based on Legendre polynomial.The performance and robustness of the presented kernel were investigated on bi-spiral benchmark data set as well as five data sets from the UCI benchmark repository. I}he experiment results demonstrate that the presented kernel has competitive robust and generalization performance compared with commonly used kernel functions (polynomial kernel and Radial Basis Function ctc.).Moreover, the I_egendre kernel has one parameter which is only chosen from natural number, thus parameter optimization is facilitated greatly.

Key words: Support vector machine, Kernel function, Model selection

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