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...
| 主要な著者: | , , |
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| フォーマット: | info:eu-repo/semantics/report |
| 言語: | English |
| 出版事項: |
2012
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| オンライン･アクセス: | http://hdl.handle.net/10835/1550 |