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Evaluating The Difference Between Graph Structures In Gaussian Bayesian Networks

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Gómez Villegas, Miguel A. y Main Yaque, Paloma y Navarro Veguillas, Hilario y Susi, Rosario (2011) Evaluating The Difference Between Graph Structures In Gaussian Bayesian Networks. Expert Systems With Applications, 38 (10). pp. 12409-12414. ISSN 0957-4174

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URL Oficial: http://www.sciencedirect.com/science/article/pii/S0957417411005367


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Resumen

In this work, we evaluate the sensitivity of Gaussian Bayesian networks to perturbations or uncertainties in the regression coefficients of the network arcs and the conditional distributions of the variables.
The Kullback–Leibler divergence measure is used to compare the original network to its perturbation.
By setting the regression coefficients to zero or non-zero values, the proposed method can remove or add arcs, making it possible to compare different network structures.
The methodology is implemented with some case studies.


Tipo de documento:Artículo
Palabras clave:Gaussian Bayesian networks; Conditional specification; Sensitivity analysis; Kullback-Leibler divergence measure;Sensitivity-Analysis;Computer Science, Artificial Intelligence; Engineering, Electrical & Electronic; Operations Research & Management
Materias:Ciencias > Matemáticas > Estadística matemática
Código ID:15611
Depositado:13 Jun 2012 08:58
Última Modificación:04 Mar 2016 16:17

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