Learning class-discriminative dynamic Bayesian networks

  title={Learning class-discriminative dynamic Bayesian networks},
  author={John Burge and Terran Lane},
In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a proposed network topology describes a set of data. Many commonly used scores such as BD, BDE, BDEU, etc., are not well suited for class discrimination. Instead, scores such as the class-conditional likelihood (CCL) should be employed. Unfortunately, CCL does not decompose and its application to large domains is not feasible. We… CONTINUE READING


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