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...
| Huvudupphovsmän: | , , |
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| Materialtyp: | info:eu-repo/semantics/article |
| Språk: | English |
| Publicerad: |
2017
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| Ämnen: | |
| Länkar: | http://hdl.handle.net/10835/4898 https://doi.org/10.1016/j.ijar.2005.10.004 |