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LEARNING PARAMETERS OF SPECIAL PROBABILITY STRUCTURES IN BAYESIAN NETWORKS

机译:贝叶斯网络特殊概率结构学习参数

摘要

A computer-implemented method, a computer program product, and a computer system for data processing. An embodiment includes providing a Bayesian network model including a special model structure. The embodiment further includes learning probabilities between at least one node of the Bayesian network model and a parent node of the Bayesian network model, wherein learning the probabilities is performed by assuming no special model structure is included in the Bayesian network model. The embodiment further includes optimizing parameters that describe learned probabilities of the Bayesian network model including the special model structure and updating the Bayesian network model including the special model structure using the optimized parameters.
机译:计算机实现的方法,计算机程序产品和用于数据处理的计算机系统。 一个实施例包括提供包括特殊模型结构的贝叶斯网络模型。 该实施例还包括贝叶斯网络模型的至少一个节点与贝叶斯网络模型的父节点之间的学习概率,其中通过假设贝叶斯网络模型中没有包括特殊模型结构来执行学习概率。 该实施例还包括优化描述贝叶斯网络模型的学习概率的参数,包括特殊模型结构和使用优化参数更新包括特殊模型结构的贝叶斯网络模型。

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