Nonparametric Bayesian label prediction on a graph

Understand

An implementation of a nonparametric Bayesian approach to solving binary classification problems on graphs is described.

• A hierarchical Bayesian approach with a randomly scaled Gaussian prior is considered.
• The prior uses the graph Laplacian to take into account the underlying geometry of the graph.
• A method based on a theoretically optimal prior and a more flexible variant using partial conjugacy are proposed.