Learning Conditional Distributions using Mixtures of Truncated Basis Functions

Learning Conditional Distributions using Mixtures of Truncated Basis Functions

Mixtures of Truncated Basis Functions (MoTBFs) have recently been proposed for modelling univariate and joint distributions in hybrid Bayesian networks. In this paper we analyse the problem of learning conditional MoTBF distributions from data. Our approach utilizes a new technique for learning...

書誌詳細
主要な著者:	Pérez-Bernabé, Inmaculada, Salmerón Cerdán, Antonio, Langseth, Helge
フォーマット:	info:eu-repo/semantics/article
言語:	English
出版事項:	2017
オンライン･アクセス:	http://hdl.handle.net/10835/4859

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