Abstract
We present a critical analysis of the maximal prime decomposition of Bayesian networks (BNs). Our analysis suggests that it may be more useful to transform a BN into a hierarchical Markov network.
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
Olesen, K.G. and Madsen, A.L.: Maximal prime subgraph decomposition of Bayesian networks. IEEE Transactions on Systems, Man, and Cybernetics, B, 32(1):21–31, 2002.
Wong, S.K.M., Butz, C.J. and Wu, D.: On the implication problem for probabilistic conditional independency. IEEE Transactions on Systems, Man, and Cybernetics, A, 30(6): 785–805, 2000.
Wong, S.K.M., Butz, C.J. and Wu, D.: On undirected representations of Bayesian networks. ACM SIGIR Workshop on Mathematical/Formal Models in Information Retrieval, 52–59, 2001.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Butz, C.J., Hu, Q., Yang, X.D. (2003). Critical Remarks on the Maximal Prime Decomposition of Bayesian Networks. In: Wang, G., Liu, Q., Yao, Y., Skowron, A. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2003. Lecture Notes in Computer Science(), vol 2639. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39205-X_115
Download citation
DOI: https://doi.org/10.1007/3-540-39205-X_115
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-14040-5
Online ISBN: 978-3-540-39205-7
eBook Packages: Springer Book Archive