Mean Field Approximation in Bayesian Variable Selection

Yukito Iba

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arXiv · cond-mat/9808071

Mean Field Approximation in Bayesian Variable Selection

Yukito Iba

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Abstract

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.

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Yukito Iba. 1998-08-07. Mean Field Approximation in Bayesian Variable Selection. https://arxiv.org/abs/cond-mat/9808071

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