The nature of statistical learning theory
The nature of statistical learning theory
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Sparse bayesian learning and the relevance vector machine
The Journal of Machine Learning Research
Information Theory, Inference & Learning Algorithms
Information Theory, Inference & Learning Algorithms
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In the paper we propose a method based on Bayesian framework for selecting the best kernel function for supervised learning problem. The parameters of the kernel function are considered as model parameters and maximum evidence principle is applied for model selection. We describe a general scheme of Bayesian regularization, present model of kernel classifiers as well as our approximations for evidence estimation, and then give some results of experimental evaluation.