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11 papers · 2 filters
Optimizing Causal Orderings for Generating DAGs from Data
Remco R. Bouckaert
An algorithm for generating the structure of a directed acyclic graph from data using the notion of causal input lists is presented. The algorithm manipulates the ordering of the v…
A Stratified Simulation Scheme for Inference in Bayesian Belief Networks
Remco R. Bouckaert
Simulation schemes for probabilistic inference in Bayesian belief networks offer many advantages over exact algorithms; for example, these schemes have a linear and thus predictabl…
Properties of Bayesian Belief Network Learning Algorithms
Remco R. Bouckaert
Bayesian belief network learning algorithms have three basic components: a measure of a network structure and a database, a search heuristic that chooses network structures to be c…
Elicitation of Probabilities for Belief Networks: Combining Qualitative and Quantitative Information
Marek J. Druzdzel, Linda C. van der Gaag
Although the usefulness of belief networks for reasoning under uncertainty is widely accepted, obtaining numerical probabilities that they require is still perceived a major obstac…
Error Estimation in Approximate Bayesian Belief Network Inference
Enrique F. Castillo, Remco R. Bouckaert, Jose M. Sarabia +1
We can perform inference in Bayesian belief networks by enumerating instantiations with high probability thus approximating the marginals. In this paper, we present a method for de…
How to Elicit Many Probabilities
Linda C. van der Gaag, Silja Renooij, Cilia L. M. Witteman +2
In building Bayesian belief networks, the elicitation of all probabilities required can be a major obstacle. We learned the extent of this often-cited observation in the constructi…