Title :
Asymmetric kernel method and its application to Fisher´s discriminant
Author :
Koide, N. ; Yamashita, Yukihiko
Author_Institution :
Graduate Sch. of Sci. & Eng., Tokyo Inst. of Technol.
Abstract :
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
Keywords :
statistical analysis; Fisher discriminant; asymmetric kernel method; variable kernel parameters; Error analysis; Hilbert space; Kernel; Pattern recognition; Principal component analysis; Support vector machine classification; Support vector machines;
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2521-0
DOI :
10.1109/ICPR.2006.278