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Probabilistic network construction using the minimum description length principle

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Symbolic and Quantitative Approaches to Reasoning and Uncertainty (ECSQARU 1993)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 747))

Abstract

This paper presents a procedure for the construction of probabilistic networks from a database of observations based on the minimum description length principle. On top of the advantages of the Bayesian approach the minimum description length principle offers the advantage that every probabilistic network structure that represents the same set of independencies gets assigned the same quality. This makes it is very suitable for the order optimization procedure as described in [4]. Preliminary test results show that the algorithm performs comparable to the algorithm based on the Bayesian approach [6].

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Author information

Authors and Affiliations

  1. Department of Computer Science, Utrecht University, P.O. Box 80.089, 3508, TB Utrecht, The Netherlands

    Remco R. Bouckaert

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  1. Remco R. Bouckaert
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Editor information

Michael Clarke Rudolf Kruse Serafín Moral

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© 1993 Springer-Verlag Berlin Heidelberg

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Bouckaert, R.R. (1993). Probabilistic network construction using the minimum description length principle. In: Clarke, M., Kruse, R., Moral, S. (eds) Symbolic and Quantitative Approaches to Reasoning and Uncertainty. ECSQARU 1993. Lecture Notes in Computer Science, vol 747. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0028180

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  • DOI: https://doi.org/10.1007/BFb0028180

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-57395-1

  • Online ISBN: 978-3-540-48130-0

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