A Method for Learning Bayesian Network Structure

Bayesian network structures from data is an NP-hard problem, In this paper, we propose an approach based on mutual information and PC algorithm methods. This algorithm obain the initial undirected graph using mutual information firstly, obtain a PDAG using PC algorithm. Experimental results show that our method outperforms the PC algorithms under the same conditions, Thus the algorithm decreases the running time and the order of CI tests greatly than the PC algorithm.

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