The Junction Tree Algorithm
The junction tree algorithm is a message-passing algorithm for inference in graphical models. It is used to find the most probable configuration of hidden variables in a graphical model, given some observed variables.
Areas of application
- Probabilistic graphical models
- Artificial intelligence
- Machine learning
- Data analysis
- Bioinformatics
- Healthcare analytics
- Computational biology
- Computer vision
Example
For example, suppose we have a graphical model representing a set of genetic markers and their relationship to disease status. The junction tree algorithm can be used to infer the most likely genotype of an individual given their phenotype and the distribution of genetic markers in the population.