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Issue No.05  May (2008 vol.20)
pp: 628640
ABSTRACT
Structure learning of Bayesian networks is a wellresearched but computationally hard task. We present an algorithm that integrates an information theorybased approach and a scoring functionbased approach for learning structures of Bayesian networks. Our algorithm also makes use of basic Bayesian network concepts like dseparation and Markov independence. We show that the proposed algorithm is capable of handling networks with a large number of variables. We present the applicability of the proposed algorithm on four standard network datasets and also compare its performance and computational efficiency with other standard structure learning methods. The experimental results show that our method can efficiently and accurately identify complex network structures from data.
INDEX TERMS
classification, data mining, Machine learning
CITATION
XueWen Chen, Gopalakrishna Anantha, Xiaotong Lin, "Improving Bayesian Network Structure Learning with Mutual InformationBased Node Ordering in the K2 Algorithm", IEEE Transactions on Knowledge & Data Engineering, vol.20, no. 5, pp. 628640, May 2008, doi:10.1109/TKDE.2007.190732
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