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多层贝叶斯网络

多层贝叶斯网络将标准贝叶斯网络扩展至具有层级或分组结构的数据——例如学校中的学生、医院中的病人、受试者内的观测——通过在每个层级放置分离但相互关联的图模型,其中高层参数控制低层节点的条件概率表。其结果是一个原则性的概率框架,能够捕捉组内关系和组间变异。

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来源

  1. Koller, D. & Friedman, N. (2009). Probabilistic Graphical Models: Principles and Techniques. MIT Press. ISBN: 978-0262013192
  2. Getoor, L. & Taskar, B. (Eds.) (2007). Introduction to Statistical Relational Learning. MIT Press. ISBN: 978-0262072885

如何引用本页

ScholarGate. (2026, June 3). Multilevel Bayesian Network. ScholarGate. https://scholargate.app/zh/bayesian/multilevel-bayesian-network

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Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

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ScholarGateMultilevel Bayesian Network (Multilevel Bayesian Network). 于 2026-06-15 检索自 https://scholargate.app/zh/bayesian/multilevel-bayesian-network · 数据集: https://doi.org/10.5281/zenodo.20539026