2004
@article{YJY2004,
vgclass = {refpap},
author = {Jian Yang and Zhong Jin and Jing-yu Yang and David Zhang
and Alejandro F. Frangi},
title = {Essence of kernel {F}isher discriminant: {KPCA} plus {LDA}},
journal = {Pattern Recognition},
volume = {37},
number = {10},
pages = {2097--2100},
month = {October},
year = {2004},
url = {http://dx.doi.org/10.1016/j.patcog.2003.10.015},
abstract = {In this paper, the method of kernel Fisher discriminant
(KFD) is analyzed and its nature is revealed, i.e., KFD is equivalent
to kernel principal component analysis (KPCA) plus Fisher linear
discriminant analysis (LDA). Based on this result, a more transparent
KFD algorithm is proposed. That is, KPCA is first performed and then
LDA is used for a second feature extraction in the KPCA-transformed
space. Finally, the effectiveness of the proposed algorithm is verified
using the CENPARMI handwritten numeral database.},
}