Asymmetric kernel method and its application to Fisher’s discriminant
Naoya Koide, Yukihiko Yamashita · 2006
In this paper, we propose the asymmetric kernel method. Furthermore, we apply it to Fisher's discriminant and provide an kernel Fisher's discriminant with variable kernel parameters. We also provide the experimental result of the existing and the new kernel Fisher's discriminants by using several standard datasets and show the advantage of our method