Learning Bayesian Network Structure
贝叶斯网络结构学习分析

In this paper the analysis of principle and process of Bayesian network structure learning is given. Bayesian network structure learning is a process that seeks the best network structure fitting the prior knowledge and data. The computing of posterior can be closed when data are completed and some other conditions are satisfied ,while the computing is not closed when some data are missing. One solution for missing data is fill-in methods,another is to approximate the likelihood of structure,then to compute the probabilities of structure.