Learning naive Bayes regression models with missing data using mixtures of truncated exponentials
In the last years, mixtures of truncated exponentials (MTEs) have received much attention within the context of probabilistic graphical models, as they provide a framework for hybrid Bayesian networks which is compatible with standard inference algorithms and no restriction on the structure of the n...
| Главные авторы: | , , |
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| Формат: | info:eu-repo/semantics/report |
| Язык: | English |
| Опубликовано: |
2012
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| Online-ссылка: | http://hdl.handle.net/10835/1550 |