97 search results - page 1 / 20 » Regularized discriminant analysis for high dimensional, low ... |
KDD
2006
ACM
14 years 4 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 ...
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...
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 ...
SIAMMAX
2010
12 years 11 months 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...
BMCBI
2007
13 years 4 months ago
2007
Background: Mean-based clustering algorithms such as bisecting k-means generally lack robustness. Although componentwise median is a more robust alternative, it can be a poor cent...