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首页> 外文期刊>Bioinformatics >bnstruct: an R package for Bayesian Network structure learning in the presence of missing data
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bnstruct: an R package for Bayesian Network structure learning in the presence of missing data

机译:Bnstruct:贝叶斯网络结构的R包在缺失数据存在下学习

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摘要

Motivation: A Bayesian Network is a probabilistic graphical model that encodes probabilistic dependencies between a set of random variables. We introduce bnstruct, an open source R package to (i) learn the structure and the parameters of a Bayesian Network from data in the presence of missing values and (ii) perform reasoning and inference on the learned Bayesian Networks. To the best of our knowledge, there is no other open source software that provides methods for all of these tasks, particularly the manipulation of missing data, which is a common situation in practice.
机译:动机:贝叶斯网络是一种概率图形模型,可以在一组随机变量之间编码概率依赖性。 我们介绍Bnstruct,一个开源R包到(i)学习贝叶斯网络的结构和参数从存在缺失值的数据中,(ii)对学习贝叶斯网络执行推理和推理。 据我们所知,没有其他开源软件,为所有这些任务提供了方法,特别是操纵缺失数据,这是实践中的常见情况。

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