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What is Bayesian Network Classifiers in Weka about?

Bayesian network classifiers are implemented in Weka that allow for structure learning using various algorithms like hill climbing and simulated annealing. The networks can be evaluated using local scores like Bayes, BDe, MDL, and entropy, as well as global scores like cross validation. Once a network structure is learned, probability distributions can be estimated for classification. The Weka implementation provides options for structure learning, parameter estimation, and inspecting learned Bayesian netwo

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