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ICDM
2007
IEEE
248views Data Mining» more  ICDM 2007»
15 years 5 months ago
Adapting SVM Classifiers to Data with Shifted Distributions
Many data mining applications can benefit from adapting existing classifiers to new data with shifted distributions. In this paper, we present Adaptive Support Vector Machine (Ada...
Jun Yang 0003, Rong Yan, Alexander G. Hauptmann
TNN
2008
133views more  TNN 2008»
15 years 1 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
PAMI
2011
14 years 8 months ago
Revisiting Linear Discriminant Techniques in Gender Recognition
—Emerging applications of computer vision and pattern recognition in mobile devices and networked computing require the development of resourcelimited algorithms. Linear classifi...
Juan Bekios-Calfa, José Miguel Buenaposada,...
ICML
2009
IEEE
16 years 2 months ago
Ranking interesting subgroups
Subgroup discovery is the task of identifying the top k patterns in a database with most significant deviation in the distribution of a target attribute Y . Subgroup discovery is ...
Stefan Rueping
ICML
2008
IEEE
16 years 2 months ago
Composite kernel learning
The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Mul...
Marie Szafranski, Yves Grandvalet, Alain Rakotomam...