Abstract
In [2], we introduced the notion of the parental synergy. In the same paper, moreover, an expression was advanced for the prior convergence error (the error which is found in the marginal probabilities computed for a node when the parents of this node are wrongfully assumed to be independent), in which the parental synergy has a key position as weighting factor. This key position suggests that the parental synergy captures a fundamental feature of a Bayesian network. In this paper a proof is provided for the correctness of the conjectured expression of the prior convergence error.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Bolt, J.H., van der Gaag, L.C.: The convergence error in loopy propagation. Paper presented at the International Conference on Advances in Intelligent Systems: Theory and Applications (2004)
Bolt, J.H.: Bayesian networks: the parental synergy. In: Jaeger, M., Nielsen, T.D. (eds.) Proceedings of the Fourth European Workshop on Probabilistic Graphical Models, Hirtshals, pp. 33–40 (2008)
Cooper, G.F.: The computational complexity of probabilistic inference using Bayesian belief networks. Artificial Intelligence 42, 393–405 (1990)
Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann Publishers, Palo Alto (1988)
Wellman, M.P.: Fundamental concepts of qualitative probabilistic networks. Artificial Intelligence 44, 257–303 (1990)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Bolt, J.H. (2014). The General Expression of the Prior Convergence Error: A Proof. In: Laurent, A., Strauss, O., Bouchon-Meunier, B., Yager, R.R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2014. Communications in Computer and Information Science, vol 442. Springer, Cham. https://doi.org/10.1007/978-3-319-08795-5_51
Download citation
DOI: https://doi.org/10.1007/978-3-319-08795-5_51
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08794-8
Online ISBN: 978-3-319-08795-5
eBook Packages: Computer ScienceComputer Science (R0)