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A Scoring Criterion For Learning Chain Graphs
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作者 Zhong Guo ZHENG Jing XU Xing Wei TONG 《Acta Mathematica Sinica,English Series》 SCIE CSCD 2006年第4期1063-1068,共6页
A chain graph allows both directed and undirected edges, and contains the underlying mathematical properties of the two. An important method of learning graphical models is to use scoring criteria to measure how well ... A chain graph allows both directed and undirected edges, and contains the underlying mathematical properties of the two. An important method of learning graphical models is to use scoring criteria to measure how well the graph structures fit the data. In this paper, we present a scoring criterion for learning chain graphs based on the Kullback Leibler distance. It is score equivalent, that is, equivalent chain graphs obtain the same score, so it can be used to perform model selection and model averaging. 展开更多
关键词 Chain graph markov equivalence Scoring criterion
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