Learning naive Bayes regression models with missing data using mixtures of truncated exponentials

Learning naive Bayes regression models with missing data using mixtures of truncated exponentials

In the last years, mixtures of truncated exponentials (MTEs) have received much attention within the context of probabilistic graphical models, as they provide a framework for hybrid Bayesian networks which is compatible with standard inference algorithms and no restriction on the structure of the n...

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Bibliografische gegevens
Hoofdauteurs:	Fernández, Antonio, Nielsen, Jens D., Salmerón Cerdán, Antonio
Formaat:	info:eu-repo/semantics/report
Taal:	English
Gepubliceerd in:	2012
Online toegang:	http://hdl.handle.net/10835/1550

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