35 search results - page 3 / 7 » Symmetric two dimensional linear discriminant analysis (2DLD... |
KDD
2006
ACM
14 years 6 months ago
2006
ACM
Linear and Quadratic Discriminant Analysis have been used widely in many areas of data mining, machine learning, and bioinformatics. Friedman proposed a compromise between Linear ...
CVPR
2007
IEEE
14 years 8 months ago
2007
IEEE
Dimensionality reduction is an important issue when facing high-dimensional data. For supervised dimensionality reduction, Linear Discriminant Analysis (LDA) is one of the most po...
AI
2006
Springer
13 years 9 months ago
2006
Springer
Abstract. We present a performance analysis of three linear dimensionality reduction techniques: Fisher's discriminant analysis (FDA), and two methods introduced recently base...
VLSISP
2002
13 years 5 months ago
2002
Dimensionality reduction is an important problem in pattern recognition. There is a tendency of using more and more features to improve the performance of classifiers. However, not...
SIAMMAX
2010
13 years 21 days ago
2010
Linear Discriminant Analysis (LDA) is one of the most popular approaches for feature extraction and dimension reduction to overcome the curse of the dimensionality of the high-dime...