433 search results - page 25 / 87 » Local-Learning-Based Feature Selection for High-Dimensional ... |
KAIS
2008
13 years 7 months ago
2008
Much work on skewed, stochastic, high dimensional, and biased datasets usually implicitly solve each problem separately. Recently, we have been approached by Texas Commission on En...
JUCS
2008
13 years 7 months ago
2008
: Feature selection methods are often applied in the context of document classification. They are particularly important for processing large data sets that may contain millions of...
ESANN
2006
13 years 9 months ago
2006
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
EVOW
2006
Springer
13 years 11 months ago
2006
Springer
Abstract. Computational analysis of mass spectrometric (MS) proteomic data from sera is of potential relevance for diagnosis, prognosis, choice of therapy, and study of disease act...
IJCNN
2008
IEEE
14 years 2 months ago
2008
IEEE
— We propose a feature selection criterion based on kernel discriminant analysis (KDA) for an -class problem, which finds eigenvectors on which the projected class data are loca...