Junction tree algorithm
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The junction tree algorithm is a method used in machine learning for exact marginalization in general graphs. In essence, it entails performing belief propagation on a modified graph called a junction tree. The basic premise is to eliminate cycles by clustering them into single nodes.
Contents |
[edit] Junction Tree Algorithm
[edit] Hugin algorithm
- Moralize the graph
- Introduce the evidence
- Triangulate the graph
- Construct a junction tree from this (form a maximal spanning tree)
- Propagate the probabilities (via belief propagation)
[edit] Shafer-Shenoy algorithm
[edit] References
- ( PDF ) A Short Course on Graphical Models: 3. The Junction Tree Algorithms
- Michael I. Jordan, "An Introduction to Probabilistic Graphical Models" (draft copy)
