19 search results - page 1 / 4 » Null space versus orthogonal linear discriminant analysis |
ICML
2006
IEEE
14 years 5 months ago
2006
IEEE
Dimensionality reduction is an important pre-processing step for many applications. Linear Discriminant Analysis (LDA) is one of the well known methods for supervised dimensionali...
JMLR
2006
13 years 4 months ago
2006
Dimensionality reduction is an important pre-processing step in many applications. Linear discriminant analysis (LDA) is a classical statistical approach for supervised dimensiona...
PAKDD
2007
ACM
13 years 10 months ago
2007
ACM
While null space based linear discriminant analysis (NLDA) obtains a good discriminant performance, the ability easily suffers from an implicit assumption of Gaussian model with sa...
CVPR
2004
IEEE
14 years 6 months ago
2004
IEEE
Linear Discriminant Analysis (LDA) is popular feature extraction technique for face recognition. However, it often suffers from the small sample size problem when dealing with the...
ICPR
2004
IEEE
14 years 5 months ago
2004
IEEE
In a previous paper [1], we have presented a new linear classification algorithm, Principal Component Null Space Analysis (PCNSA) which is designed for problems like object recogn...