Inference Algorithms for Similarity Networks
- Dan Geiger ,
- David Heckerman
MSR-TR-93-09 |
Proceedings of the IEEE International Conference on Data Mining (ICDM)
We examine two types of similarity networks each based on a distinct notion of relevance. For both types of similarity networks we present an efficient inference algorithm that works under the assumption that every event has a nonzero probability of occurrence. Another inference algorithm is developed for type 1 similarity networks that works under no restriction, albeit less efficiently.