RT Journal Article
T1 Sensitivity to evidence in Gaussian Bayesian networks using mutual information
A1 Gómez Villegas, Miguel A.
A1 Main Yaque, Paloma
A1 Viviani, Paola
AB 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.
PB Elsevier
SN 0020-0255
YR 2014
FD 2014-08-10
LK https://hdl.handle.net/20.500.14352/33619
UL https://hdl.handle.net/20.500.14352/33619
LA eng
NO Spanish Ministerio de Ciencia e Innovacion
NO Universidad Complutense-Banco Santander
DS Docta Complutense
RD 8 may 2024