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» Feature selection for linear support vector machines
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IJCNN
2008
IEEE
14 years 2 months ago
Feature selection based on kernel discriminant analysis for multi-class problems
— 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...
Tsuneyoshi Ishii, Shigeo Abe
DAGM
2006
Springer
13 years 11 months ago
Feature Selection for Automatic Image Annotation
Automatic image annotation empowers the user to search an image database using keywords, which is often a more practical option than a query-by-example approach. In this work, we p...
Lokesh Setia, Hans Burkhardt
ICML
2003
IEEE
14 years 8 months ago
Incorporating Diversity in Active Learning with Support Vector Machines
In many real world applications, active selection of training examples can significantly reduce the number of labelled training examples to learn a classification function. Differ...
Klaus Brinker
ICAPR
2009
Springer
14 years 2 months ago
Relevant and Redundant Feature Analysis with Ensemble Classification
— Feature selection and ensemble classification increase system efficiency and accuracy in machine learning, data mining and biomedical informatics. This research presents an ana...
Rakkrit Duangsoithong, Terry Windeatt
ICDM
2008
IEEE
160views Data Mining» more  ICDM 2008»
14 years 2 months ago
Direct Zero-Norm Optimization for Feature Selection
Zero-norm, defined as the number of non-zero elements in a vector, is an ideal quantity for feature selection. However, minimization of zero-norm is generally regarded as a combi...
Kaizhu Huang, Irwin King, Michael R. Lyu