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...
| 主要な著者: | , , |
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| フォーマット: | info:eu-repo/semantics/article |
| 言語: | English |
| 出版事項: |
2017
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| 主題: | |
| オンライン･アクセス: | http://hdl.handle.net/10835/4898 https://doi.org/10.1016/j.ijar.2005.10.004 |