Name
Abstract | ||
|---|---|---|
The present paper introduces a new kind of representation for the potentials in a Bayesian network: Binary Probability Trees. They enable the representation of context-specific independences in more detail than probability trees. This enhanced capability leads to more efficient inference algorithms for some types of Bayesian networks. This paper explains the procedure for building a binary probability tree from a given potential, which is similar to the one employed for building standard probability trees. It also offers a way of pruning a binary tree in order to reduce its size. This allows us to obtain exact or approximate results in inference depending on an input threshold. This paper also provides detailed algorithms for performing the basic operations on potentials (restriction, combination and marginalization) directly to binary trees. Finally, some experiments are described where binary trees are used with the variable elimination algorithm to compare the performance with that obtained for standard probability trees. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1016/j.ijar.2010.05.006 | Int. J. Approx. Reasoning |
Keywords | Field | DocType |
probability tree,binary probability tree,binary tree,bayesian network,probability trees,basic operation,standard probability tree,efficient inference algorithm,present paper,approximate result,approximate inference,deterministic algorithms,approximate computation,bayesian networks inference,variable elimination algorithm,binary probability trees,variable elimination | Geometry of binary search trees,Binary tree,Bayesian network,Artificial intelligence,Weight-balanced tree,Random binary tree,Ternary search tree,Binary expression tree,Machine learning,Mathematics,Binary search tree | Journal |
Volume | Issue | ISSN |
52 | 1 | International Journal of Approximate Reasoning |
Citations | PageRank | References |
9 | 0.52 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrés Cano | 1 | 193 | 20.06 |
| Manuel Gémez-Olmedo | 2 | 9 | 0.52 |
| Serafén Moral | 3 | 9 | 0.52 |