Resumen

CARDOZO OJEDA, Erwing Fabián  y  ARGUELLO FUENTES, Henry. A BAYESIAN NETWORKS STRUCTURE LEARNING: A SCORING AND SEARCH BASED APPROACH. Cienc. Ing. Neogranad. [online]. 2011, vol.21, n.1, pp.29-50. ISSN 0124-8170.

One of the most recent knowledge representations under uncertainty are Bayesian Networks whose main captivation is the property to obtain such a representation from a large amount of data. The issue is that getting a network structure is a NP-hard problem -commonly a learning process-, so there has been a lot of learning work where one of the best known methods is called based scoring and search approach. This paper reviews the basic definition of Bayesian networks, the scoring-and-search-based approach and by-products, that is, the hybrid approach and the search for equivalence classes; in addition, describes some algorithms for each approach and gives a summary of results of recent work.

Palabras clave : bayesian networks; scoring and search learning; hybrid learning; equivalence classes learning.

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