Learning Bayesian networks structure based on causal semanitics orienting
Chen Nai-ji · Computer Engineering and Applications Journal · 2007
A new method of learning Bayesian network structure based on basic dependency relationship between variables,basic structure between nodes,d-separation criterion,the idea of dependency analysis and the strategy of mixture orienting is given.This method do not need sorting nodes.It can effectively avoid the exponential complexity of search scoring based methods and a large number of the calculate of high rank conditional probability in existing dependency analysis based methods.