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» Feature Selection for Support Vector Machines
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CVPR
2003
IEEE
14 years 9 months ago
Simultaneous Feature Selection and Classifier Training via Linear Programming: A Case Study for Face Expression Recognition
A linear programming technique is introduced that jointly performs feature selection and classifier training so that a subset of features is optimally selected together with the c...
Guodong Guo, Charles R. Dyer
ICPR
2008
IEEE
14 years 9 months ago
A method of feature selection using contribution ratio based on boosting
AdaBoost and support vector machines (SVM) algorithms are commonly used in the field of object recognition. As classifiers, their classification performance is sensitive to affect...
Masamitsu Tsuchiya, Hironobu Fujiyoshi
ICIAP
2005
ACM
14 years 7 months ago
A Neural Adaptive Algorithm for Feature Selection and Classification of High Dimensionality Data
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
Elisabetta Binaghi, Ignazio Gallo, Mirco Boschetti...
TNN
2008
133views more  TNN 2008»
13 years 7 months ago
A General Wrapper Approach to Selection of Class-Dependent Features
In this paper, we argue that for a C-class classification problem, C 2-class classifiers, each of which discriminating one class from the other classes and having a characteristic ...
Lipo Wang, Nina Zhou, Feng Chu
ICCV
2001
IEEE
14 years 9 months ago
Face Recognition with Support Vector Machines: Global versus Component-based Approach
We present a component-based method and two global methods for face recognition and evaluate them with respect to robustness against pose changes. In the component system we first...
Bernd Heisele, Purdy Ho, Tomaso Poggio