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SopLEQ

Context

The SopLEQ search algorithm is based on a global characterization of data and on the exploitation of the equivalence properties of Bayesian networks. Fixed Arcs are treated as normal arcs, but Forbidden Arcs are observed. Temporal Indices are also taken into account.

References

  • L. Jouffe, Nouvelle classe de méthodes d’apprentissage de réseaux bayésiens, Journées francophones d’Extraction et de Gestion des Connaissances (EGC), Montpellier, janvier 2002.

  • P. Munteanu, M. Bendou, The EQ Framework for Learning Equivalence Classes of Bayesian Networks, First IEEE International Conference on Data Mining (IEEE ICDM), San José, novembre 2001.

  • L. Jouffe, P. Munteanu, New Search Strategies for Learning Bayesian Networks, Proceedings of the Tenth International Symposium on Applied Stochastic Models, Data Analysis, Compiègne, juin 2001.

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