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Credal networks under maximum entropy (2000).
| Content Provider | CiteSeerX |
|---|---|
| Author | Lukasiewicz, Thomas |
| Abstract | We apply the principle of maximum entropy to select a unique joint probability distribution from the set of all joint probability distributions specified by a credal network. In detail, we start by showing that the unique joint distribution of a Bayesian tree coincides with the maximum entropy model of its conditional distributions. This result, however, does not hold anymore for general Bayesian networks. We thus present a new kind of maximum entropy models, which are computed sequentially. We then show that for all general Bayesian networks, the sequential maximum entropy model coincides with the unique joint distribution. Moreover, we apply the new principle of sequential maximum entropy to interval Bayesian networks and more generally to credal networks. We especially show that this application is equivalent to a number of small local entropy maximizations. |
| File Format | |
| Publisher Date | 2000-01-01 |
| Access Restriction | Open |
| Subject Keyword | Credal Network Maximum Entropy Unique Joint Distribution Maximum Entropy Model General Bayesian Network Bayesian Network Joint Probability Distribution Bayesian Tree Coincides New Principle Sequential Maximum Entropy Model Coincides Small Local Entropy Maximization Conditional Distribution New Kind Sequential Maximum Entropy Unique Joint Probability Distribution |
| Content Type | Text |
