317 search results - page 14 / 64 » From Transformation-Based Dimensionality Reduction to Featur... |
SDM
2010
SIAM
14 years 7 months ago
2010
SIAM
A popular approach for dimensionality reduction and data analysis is principal component analysis (PCA). A limiting factor with PCA is that it does not inform us on which of the o...
PR
2006
14 years 9 months ago
2006
In many pattern recognition applications, high-dimensional feature vectors impose a high computational cost as well as the risk of "overfitting". Feature Selection addre...
JMLR
2010
14 years 4 months ago
2010
The rapid advance of computer technologies in data processing, collection, and storage has provided unparalleled opportunities to expand capabilities in production, services, comm...
ICPR
2004
IEEE
15 years 10 months ago
2004
IEEE
Feature subset selection, applied as a pre-processing step to machine learning, is valuable in dimensionality reduction, eliminating irrelevant data and improving classifier perfo...
CIBCB
2005
IEEE
15 years 3 months ago
2005
IEEE
Efficient and reliable methods that can find a small sample of informative genes amongst thousands are of great importance. In this area, much research is investigating the combina...