Tractable Bayesian learning of tree belief networks
نویسندگان
چکیده
منابع مشابه
Tractable Bayesian Learning of Tree Belief Networks
In this paper we present decomposable priors, a family of priors over structure and parameters of tree belief nets for which Bayesian learning with complete observations is tractable, in the sense that the posterior is also decomposable and can be completely determined ana lytically in polynomial time. This fol lows from two main results: First, we show that factored distributions over spanni...
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Bayesian classifiers such as Naive Bayes or Tree Augmented Naive Bayes (TAN) have shown excellent performance given their simplicity and heavy underlying independence assumptions. In this paper we introduce a classifier taking as basis the TAN models and taking into account uncertainty in model selection. To do this we introduce decomposable distributions over TANs and show that the expression ...
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Bayesian classifiers such as Naive Bayes or Tree Augmented Naive Bayes (TAN) have shown excellent performance given their simplicity and heavy underlying independence assumptions. In this paper we introduce a classifier taking as basis the TAN model and taking into account uncertainty in model selection. To do this we introduce decomposable distributions over TANs and show that they allow the e...
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Introduction In modeling real world tasks, one inevitably has to deal with uncertainty. This uncertainty is due to the fact that many facts are unknown and or simply ignored and summarized. Suppose that one morning you find out that your grass is wet. Is it due to rain, or is it due to the sprinkler? If there is no other information, you can only talk in terms of probabilities. In a probabilist...
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ژورنال
عنوان ژورنال: Statistics and Computing
سال: 2006
ISSN: 0960-3174,1573-1375
DOI: 10.1007/s11222-006-5535-3