46 search results - page 1 / 10 » Kernel quadratic discriminant analysis for small sample size... |
PR
2008
13 years 4 months ago
2008
It is generally believed that quadratic discriminant analysis (QDA) can better fit the data in practical pattern recognition applications compared to linear discriminant analysis ...
PR
2008
13 years 4 months ago
2008
In this paper, we make a study on three Linear Discriminant Analysis (LDA) based methods: Regularized Discriminant Analysis (RDA), Discriminant Common Vectors (DCV) and Maximal Ma...
ICMCS
2006
IEEE
13 years 10 months ago
2006
IEEE
It is well-known that supervised learning techniques such as linear discriminant analysis (LDA) often suffer from the so called small sample size problem when apply to solve face ...
ICPR
2002
IEEE
14 years 5 months ago
2002
IEEE
The small sample size problem is often encountered in pattern recognition. It results in the singularity of the within-class scatter matrix Sw in Linear Discriminant Analysis (LDA...
ECCV
2004
Springer
13 years 9 months ago
2004
Springer
The null space of the within-class scatter matrix is found to express most discriminative information for the small sample size problem (SSSP). The null space-based LDA takes full ...