Approximate Bayesian Network Classifiers
نویسندگان
چکیده
Bayesian network (BN) is a directed acyclic graph encoding probabilistic independence statements between variables. BN with decision attribute as a root can be applied to classification of new cases, by synthesis of conditional probabilities propagated along the edges. We consider approximate BNs, which almost keep entropy of a decision table. They have usually less edges than classical BNs. They enable to model and extend the well-known Naive Bayes approach. Experiments show that classifiers based on approximate BNs can be very efficient.
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تاریخ انتشار 2002