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Probabilistic network construction using the minimum description length principle

  • Remco R. Bouckaert
Conference paper
Part of the Lecture Notes in Computer Science book series (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].

Keywords

Network Structure Bayesian Approach Directed Acyclic Graph Minimum Description Length Conditional Probability Table 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Remco R. Bouckaert
    • 1
  1. 1.Department of Computer ScienceUtrecht UniversityTB UtrechtThe Netherlands

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