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PAMI
2010
14 years 8 months ago
2010
—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....
82
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JMLR
2008
14 years 9 months ago
2008
Ensemble learning algorithms such as boosting can achieve better performance by averaging over the predictions of some base hypotheses. Nevertheless, most existing algorithms are ...
IWANN
2005
Springer
15 years 3 months ago
2005
Springer
Based on the Nystr¨om approximation and the primal-dual formulation of Least Squares Support Vector Machines (LS-SVM), it becomes possible to apply a nonlinear model to a large sc...
109
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FLAIRS
2004
14 years 11 months ago
2004
One important feature of the gene expression data is that the number of genes M far exceeds the number of samples N. Standard statistical methods do not work well when N < M. D...
63
Voted
GECCO
2007
Springer
15 years 1 months ago
2007
Springer
In this paper we introduce XCSF with support vector prediction: the problem of learning the prediction function is solved as a support vector regression problem and each classifie...