Bayesian networks optimization based on induction learning techniques

Título:

Bayesian networks optimization based on induction learning techniques

Autor:

Britos, Paola Verónica

Colaboradores:

; Felgaer, Pablo; García Martinez, Ramón

Temas:

RED BAYESIANAAPRENDIZAJE AUTOMÁTICOÁRBOLESMINERÍA DE DATOS

En:

Artificial Intelligence in Theory and Practice : IFIP 20th World Computer Congress, TC 12: IFIP AI 2008 Stream, September 7-10, 2008, Milano, Italy. Springer, 2008. (IFIP - The International Federation for Information Processing ; 276), pp. 439-443

Resumen:

Obtaining a bayesian network from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper, we define an automatic learning method that optimizes the bayesian networks applied to classification, using a hybrid method of learning that combines the advantages of the induction techniques of the decision trees with those of the bayesian networks.

URL/DOI:

http://dx.doi.org/10.1007/978-0-387-09695-7_44

Medio:

Soporte electrónico

Tipo de documento:

Artículo

Descripción física:

1 archivo (210,4 KB)

Idioma:

Inglés

Publicación:

Springer, 2008

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