1126 search results - page 33 / 226 » Strong Feature Sets from Small Samples |
TCBB
2010
13 years 6 months ago
2010
—Gene expression data usually contain a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best...
IJON
2008
13 years 7 months ago
2008
The Fisher-Rao metric for the focus of expansion is approximated, under the assumption that the focus is estimated from correspondences between two images taken by a translating ca...
CIBCB
2005
IEEE
14 years 1 months ago
2005
IEEE
Feature selection is an important preprocessing technique for many pattern recognition problems. When the number of features is very large while the number of samples is relatively...
COMPGEOM
2006
ACM
14 years 1 months ago
2006
ACM
In the last decade, a great deal of work has been devoted to the elaboration of a sampling theory for smooth surfaces. The goal was to ensure a good reconstruction of a given surf...
IJON
2007
13 years 7 months ago
2007
Kernel principal component analysis (KPCA) extracts features of samples with an efficiency in inverse proportion to the size of the training sample set. In this paper, we develop...