Bayesian Network Structure Learning with Permutation Tests

Abstract

In literature there are several studies on the performance of Bayesian network structure learning algorithms. The focus of these studies is almost always the heuristics the learning algorithms are based on, i.e., the maximization algorithms (in score-based algorithms) or the techniques for learning the dependencies of each variable (in constraint-based algorithms). In this article, we investigate how the use of permutation tests instead of parametric ones affects the performance of Bayesian network structure learning from discrete data. Shrinkage tests are also covered to provide a broad overview of the techniques developed in current literature.

Keywords:

• Bayesian networks
• Conditional independence tests
• Permutation tests
• Shrinkage tests

Mathematics Subject Classification:

• Primary 62H15
• Secondary 62F03, 62G10