Node order of Bayesian network based on feature selection using Support Vector Machine

At present,the method of search and score is widely used for learning the structure of Bayesian network.The method needs first the node order in the network,which is usually decided according to user's experience,so the strong subjectivity blocks the method's practical application.By measuring every node's influence on the leaf node,feature selection based on support vector machine can learn the node order from data and get rid of the effects of human factors.Experimental results show the proposed method is effective.