arXiv:cond-mat/9808071 Abstract

arXiv:cond-mat/9808071Abstract References Reviews Resources

Mean Field Approximation in Bayesian Variable Selection

Published 1998-08-07Version 1

Variable selection for a multiple regression model (Noisy Linear Perceptron) is studied with a mean field approximation. In our Bayesian framework, variable selection is formulated as estimation of discrete parameters that indicate a subset of the explanatory variables. Then, a mean field approximation is introduced for the calculation of the posterior averages over the discrete parameters. An application to a real world example, Boston housing data, is shown.

Comments: 4 pages, 2 figures(5 ps files), uses epsf.sty, iconip98.sty, to appear in the proceedings of ICONIP'98-Kitakyushu

Categories: cond-mat.dis-nn, cond-mat.stat-mech

Keywords: mean field approximation, bayesian variable selection, discrete parameters, multiple regression model, real world example

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