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Sensitivity to evidence in Gaussian Bayesian networks using mutual information

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2014

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Elsevier
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Gómez Villegas, M. Á., Main Yaque, P. & Viviani, P. «Sensitivity to Evidence in Gaussian Bayesian Networks Using Mutual Information». Information Sciences, vol. 275, agosto de 2014, pp. 115-26. DOI.org (Crossref), https://doi.org/10.1016/j.ins.2014.02.025.

Abstract

We introduce a methodology for sensitivity analysis of evidence variables in Gaussian Bayesian networks. Knowledge of the posterior probability distribution of the target variable in a Bayesian network, given a set of evidence, is desirable. However, this evidence is not always determined; in fact, additional information might be requested to improve the solution in terms of reducing uncertainty. In this study we develop a procedure, based on Shannon entropy and information theory measures, that allows us to prioritize information according to its utility in yielding a better result. Some examples illustrate the concepts and methods introduced.

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