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Bayesian Belief Network (BBN) is an appealing classification model for learning causal and noncausal dependencies among a set of query variables. It is a challenging task to learning BBN structure from observational data because of pool of large number of candidate network structures. In this study, we have addressed the issue of goodness of data fitting versus model complexity. While doing so, we...
Bayesian network (BN) is used to build a model using a probability distribution over a set of variables. The benefit of BN is the compact representation of complex problem domains. Also, BN provides decision making, smooth, consistent and flexible applicability in the complex domains. On the other hand, association rules are based on antecedent and consequent part which have condition attributes and...
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