A New Implementation for SVM Regression Based on Mean Field Analysis
نویسنده
چکیده
This paper deals with two subjects. First, we will show how support vector machine (SVM) regression problem can be solved as the maximum a posteriori (MAP) prediction in the Bayesian framework. The second part describes an approximation technique that is useful in performing calculations for SVMs based on the mean field algorithm which was originally proposed in Statistical Physics of disordered systems. An advantage is that the approach makes a better approximation to the mean and variance of SVM posterior, with respect to previous approaches, which are analytically intractable.
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