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A review of some Bayesian Belief Network structure learning algorithms

Bayesian Belief Networks (BBNs) are useful in modeling complex situations. Such graphical models help in giving better insight and understanding of the situation. Many algorithms for machine learning of BBN structures have been developed. In this paper six different algorithms have been reviewed by constructing BBN structures for two different datasets using various algorithms. Some inferences have been drawn from the results obtained from the study which may help in decision making.