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» Parallelizing Feature Selection
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ENC
2004
IEEE
15 years 1 months ago
Feature Selection for Visual Gesture Recognition Using Hidden Markov Models
Hidden Markov models have become the preferred technique for visual recognition of human gestures. However, the recognition rate depends on the set of visual features used, and al...
José Antonio Montero, Luis Enrique Sucar
IEAAIE
2003
Springer
15 years 3 months ago
Fast Feature Selection by Means of Projections
The attribute selection techniques for supervised learning, used in the preprocessing phase to emphasize the most relevant attributes, allow making models of classification simple...
Roberto Ruiz, José Cristóbal Riquelm...
ICML
2004
IEEE
15 years 3 months ago
Gradient LASSO for feature selection
LASSO (Least Absolute Shrinkage and Selection Operator) is a useful tool to achieve the shrinkage and variable selection simultaneously. Since LASSO uses the L1 penalty, the optim...
Yongdai Kim, Jinseog Kim
CATA
2009
14 years 11 months ago
Nearest Shrunken Centroid as Feature Selection of Microarray Data
The nearest shrunken centroid classifier uses shrunken centroids as prototypes for each class and test samples are classified to belong to the class whose shrunken centroid is nea...
Myungsook Klassen, Nyunsu Kim
AAAI
2011
13 years 10 months ago
A Feasible Nonconvex Relaxation Approach to Feature Selection
Variable selection problems are typically addressed under a penalized optimization framework. Nonconvex penalties such as the minimax concave plus (MCP) and smoothly clipped absol...
Cuixia Gao, Naiyan Wang, Qi Yu, Zhihua Zhang