A Generalized MDL Criterion and its Apprication to Learning Bayesian Network Structures When Both Discrete and Continuous Data are Present.

摘要

We propose the MDL principle without assuming the source to be discrete. As an application, we consider estimation of Bayesian network structures when both discrete and continuous random variables are presented in the same Bayesian network.