125 search results - page 17 / 25 » Rotational Linear Discriminant Analysis Technique for Dimens... |
PR
2006
13 years 7 months ago
2006
In the past few years, some nonlinear dimensionality reduction (NLDR) or nonlinear manifold learning methods have aroused a great deal of interest in the machine learning communit...
BMCBI
2008
13 years 7 months ago
2008
Background: Analysis of gene expression data for tumor classification is an important application of bioinformatics methods. But it is hard to analyse gene expression data from DN...
ICIAR
2004
Springer
14 years 28 days ago
2004
Springer
Previous work has shown that principal component analysis (PCA) of three-dimensional face models can be used to perform recognition to a high degree of accuracy. However, experimen...
ICONIP
2007
13 years 9 months ago
2007
Abstract. Principal component analysis (PCA) is a widely used technique for data analysis and dimensionality reduction. Eigenvalue decomposition is the standard algorithm for solvi...
ICDM
2007
IEEE
13 years 11 months ago
2007
IEEE
Recently the problem of dimensionality reduction (or, subspace learning) has received a lot of interests in many fields of information processing, including data mining, informati...