Título:
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Sensitivity to evidence in Gaussian Bayesian networks using mutual information
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Autores:
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Gómez Villegas, Miguel A. ;
Main Yaque, Paloma ;
Viviani, Paola
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Tipo de documento:
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texto impreso
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Editorial:
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Elsevier, 2014-08-10
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Dimensiones:
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application/pdf
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Nota general:
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info:eu-repo/semantics/restrictedAccess
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Idiomas:
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Palabras clave:
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Estado = Publicado
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Materia = Ciencias: Matemáticas: Estadística matemática
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Tipo = Artículo
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Resumen:
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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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En línea:
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https://eprints.ucm.es/id/eprint/26447/1/GVillegas200elsevier.pdf
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