Structural learning of Bayesian networks from complete data using the scatter search documents
作者： P.O. Djan-Sampson , F. Sahin
DOI: 10.1109/ICSMC.2004.1400904
关键词:
摘要: Bayesian networks are directed acyclic graphs that model the dependency relationships between variables of interest. These characterized by structure network and conditional probabilities specify dependencies exist variables. In this paper, scatter search optimization algorithm is utilized in learning from complete data. This involves a heuristic for best maximizes scoring function given database cases. The implemented on cases sampled known order to test accuracy structural learning. Empirical results implementations presented paper.
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