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  1. (1. 陕西师范大学 计算机学院, 陕西 西安 710062;
    2. 西安电子科技大学 电子工程学院, 陕西 西安 710071)

  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2004-08-20 发布日期:2004-08-20

A fast algorithm for extracting the support vector on the Mahalanobis distance

WANG Xi-li1,2;JIAO Li-cheng2


  1. (1. School of Computer Science, Shaanxi Normal Univ, Xi'an 710062, China;
    2. School of Electronic Engineering, Xidian Univ., Xi'an 710071, China)
  • Received:1900-01-01 Revised:1900-01-01 Online:2004-08-20 Published:2004-08-20

摘要: 针对用支持向量机解决分类问题,提出了一种采用样本到某一类的马氏距离来提取可能为支持向量的数据的方法,同时阐明了如何解决在输入空间和特征空间中求马氏距离所遇到的问题.利用特征值、特征矢量及伪逆运算的并行计算方法,建立了一种提取支持向量的快速算法.用该方法对训练数据进行预处理后,可以加快支持向量机的训练速度.实验结果也表明了该方法的有效性.

关键词: 支持向量机, 支持向量, 马氏距离, 核函数, 伪逆

Abstract: A method for extracting data which most probably are suport vectors for SVM by the Mahalanobis distance from a vector to a class is presented. How to compute Mahalanobis distance in the input and feature space is described in detail. The algorithm is fast since there are efficient methods for finding eigenvalues and eigenvectors of a symmetric matrix or comptuing pseudoinversion involved in finding the Mahalanobis distance. The training time for SVM can be reduced when the training set is preprocessed in this way. Experimental results illustrate its effectiveness.

Key words: support vector machine, support vector, Mahalanobis distance, kernel function, pseudoinvertion


  • TP391.4