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Rezaei Tabar, Vahid. (1402). A Simple Gibbs Sampler for Learning Bayesian Network Structure. سامانه مدیریت نشریات علمی, 1(2), 87-97. doi: 10.22054/jcsm.2021.55657.1022
Vahid Rezaei Tabar. "A Simple Gibbs Sampler for Learning Bayesian Network Structure". سامانه مدیریت نشریات علمی, 1, 2, 1402, 87-97. doi: 10.22054/jcsm.2021.55657.1022
Rezaei Tabar, Vahid. (1402). 'A Simple Gibbs Sampler for Learning Bayesian Network Structure', سامانه مدیریت نشریات علمی, 1(2), pp. 87-97. doi: 10.22054/jcsm.2021.55657.1022
Rezaei Tabar, Vahid. A Simple Gibbs Sampler for Learning Bayesian Network Structure. سامانه مدیریت نشریات علمی, 1402; 1(2): 87-97. doi: 10.22054/jcsm.2021.55657.1022

A Simple Gibbs Sampler for Learning Bayesian Network Structure

Journal of Data Science and Modeling
دوره 1، شماره 2، شهریور 2023، صفحه 87-97    اصل مقاله (386.48 K)
نوع مقاله: Research Manuscript
شناسه دیجیتال (DOI): 10.22054/jcsm.2021.55657.1022
نویسنده
Vahid Rezaei Tabar*
Department of Statistics, Faculty of Statistics, Mathematics and Computer Sciences, Allameh Tabataba'i University, Tehran, Iran
چکیده
The aim of this paper is to learn a Bayesian network structure for discrete variables. For this purpose, we introduce a Gibbs sampler method. Each sample represents a Bayesian network. Thus, in the process of Gibbs sampling, we obtain a set of Bayesian networks. For achieving a single graph that represents the best graph fitted on data, we use the mode of burn-in graphs. This means that the most frequent edges of burn-in graphs are considered to indicate the best single graph. The results on the well-known Bayesian networks show that our method has higher accuracy in the task of learning a Bayesian network structure.
کلیدواژه‌ها
Bayesian Network؛ Gibbs sampling؛ Burn-in graphs
آمار
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