LEARNING BAYESIAN NETWORKS FOR REGRESSION FROM INCOMPLETE DATABASES*

In this paper we address the problem of inducing Bayesian network models for regression from incomplete databases. We use mixtures of truncated exponentials (MTEs) to represent the joint distribution in the induced networks. We consider two particular Bayesian network structures, the so-called na¨ıv...

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书目详细资料
Main Authors: Fernández, Antonio, Nielsen, Jens D., Salmerón Cerdán, Antonio
格式: info:eu-repo/semantics/article
语言:English
出版: 2017
主题:
在线阅读:http://hdl.handle.net/10835/4887
https://doi.org/10.1142/S0218488510006398