A fast algorithm for extracting the support vector on the Mahalanobis distance
Xili Wang, Licheng Jiao · Journal of Xidian University · 2004
A method for extracting training data which most probably are support 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 methos for finding eigenvalues and eigenvectors of a symmetric matrix or computing 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.