218 search results - page 16 / 44 » A Neural Adaptive Algorithm for Feature Selection and Classi... |
PR
2006
13 years 8 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...
VLSISP
2002
13 years 8 months ago
2002
In this paper two agglomerative learning algorithms based on new similarity measures defined for hyperbox fuzzy sets are proposed. They are presented in a context of clustering and...
AAAI
2008
13 years 11 months ago
2008
Based on Information Theory, optimal feature selection should be carried out by searching Markov blankets. In this paper, we formally analyze the current Markov blanket discovery ...
HIS
2004
13 years 10 months ago
2004
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
BMCBI
2010
13 years 8 months ago
2010
Background: Data generated using `omics' technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of...