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...

書目詳細資料
Main Authors:	Romero, Vanessa, Rumí, Rafael, Salmerón Cerdán, Antonio
格式:	info:eu-repo/semantics/article
語言:	English
出版:	2017
主題:	Bayesian networks Mixtures of truncated exponentials Continuous variables Parameter learning Kernel Methods Simulated
在線閱讀:	http://hdl.handle.net/10835/4898 https://doi.org/10.1016/j.ijar.2005.10.004

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