LETTER
Two-fold regularization for kernel Fisher discriminant analysis in face recognition
2009 Volume 6 Issue 9 Pages 540-545
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2009 Volume 6 Issue 9 Pages 540-545
Due to the inherent nature of kernel implementation, the kernel Fisher discriminant suffers from the small sample size problem. In this paper, we introduce a novel variant of the kernel Fisher discriminant formulation to circumvent this problem. By adopting a two-fold regularization scheme on the scatter matrices, we show both effectiveness and reliability of the proposed method particularly regarding the small sample size and the lack of dimensionality issues.
