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» Training of Support Vector Machines with Mahalanobis Kernels
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PKDD
2009
Springer
113views Data Mining» more  PKDD 2009»
16 years 14 days ago
Feature Selection for Density Level-Sets
A frequent problem in density level-set estimation is the choice of the right features that give rise to compact and concise representations of the observed data. We present an eï¬...
Marius Kloft, Shinichi Nakajima, Ulf Brefeld
IJCNN
2006
IEEE
15 years 12 months ago
Leave-One-Out Cross-Validation Based Model Selection Criteria for Weighted LS-SVMs
Abstract— While the model parameters of many kernel learning methods are given by the solution of a convex optimisation problem, the selection of good values for the kernel and r...
Gavin C. Cawley
MMM
2006
Springer
133views Multimedia» more  MMM 2006»
15 years 12 months ago
A SVM-based personal recommendation system for TV programs
This paper presents a SVM-based prediction approach for constructing personal recommendation system for TV programs. We have applied Support Vector Machine (SVM) to personal predi...
Jin An Xu, Kenji Araki
PRL
2008
133views more  PRL 2008»
15 years 5 months ago
Better multiclass classification via a margin-optimized single binary problem
We develop a new multiclass classification method that reduces the multiclass problem to a single binary classifier (SBC). Our method constructs the binary problem by embedding sm...
Ran El-Yaniv, Dmitry Pechyony, Elad Yom-Tov
PAMI
2010
132views more  PAMI 2010»
15 years 4 months ago
Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters
—Adapting the hyperparameters of support vector machines (SVMs) is a challenging model selection problem, especially when flexible kernels are to be adapted and data are scarce....
Tobias Glasmachers, Christian Igel