Felgaer, PabloBritos, Paola VerónicaGarcía Martínez, Ramón2019-01-242019-01-2420060129-1831http://ri.itba.edu.ar/handle/123456789/1432"A Bayesian network is a directed acyclic graph in which each node represents a variable and each arc a probabilistic dependency; they are used to provide: a compact form to represent the knowledge and exible methods of reasoning. Obtaining it 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 (TDIDT-C4.5) with those of the Bayesian networks. The resulting method is applied to prediction in health domain."enTEORIA BAYESIANA DE DECISIONES ESTADISTICASAPRENDIZAJEPonencias en Congresos