Learning hybrid Bayesian networks using mixtures of truncated exponentials

Learning hybrid Bayesian networks using mixtures of truncated exponentials

In this paper we introduce an algorithm for learning hybrid Bayesian networks from data. The result of the algorithm is a network where the conditional distribution for each variable is a mixture of truncated exponentials (MTE), so that no restrictions on the network topology are imposed. The struct...

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Bibliografische gegevens
Hoofdauteurs:	Romero, Vanessa, Rumí, Rafael, Salmerón Cerdán, Antonio
Formaat:	info:eu-repo/semantics/article
Taal:	English
Gepubliceerd in:	2017
Onderwerpen:	Bayesian networks Mixtures of truncated exponentials Continuous variables Parameter learning Kernel Methods Simulated
Online toegang:	http://hdl.handle.net/10835/4898 https://doi.org/10.1016/j.ijar.2005.10.004

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