Antonio Fernández

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In this paper we explore the use of Tree Augmented Naive Bayes (TAN) in regression problems where some of the independent variables are continuous and some others are discrete. The proposed solution is based on the approximation of the joint distribution by a Mixture of Truncated Exponentials (MTE). The construction of the TAN structure requires the use of(More)
Bayesian networks with mixtures of truncated exponentials (MTEs) are gaining popularity as a flexible modelling framework for hybrid domains. MTEs support efficient and exact inference algorithms, but estimating an MTE from data has turned out to be a difficult task. Current methods suffer from a considerable computational burden as well as the inability to(More)