Bayesian networks : a better than frequentist approach for parametrization, and a more accurate structural complexity measure than the number of parameters - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2005

Bayesian networks : a better than frequentist approach for parametrization, and a more accurate structural complexity measure than the number of parameters

Abstract

We propose and justify a better-than-frequentist approach for bayesian network parametrization, and propose a structural entropy term that more precisely quantifies the complexity of a BN than the number of parameters. Algorithms for BN learning are deduced.
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Dates and versions

inria-00000541 , version 1 (31-10-2005)

Identifiers

  • HAL Id : inria-00000541 , version 1

Cite

Sylvain Gelly, Olivier Teytaud. Bayesian networks : a better than frequentist approach for parametrization, and a more accurate structural complexity measure than the number of parameters. CAP, 2005, Nice, 16 p. ⟨inria-00000541⟩
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