Machine learningNetwork science
贝叶斯随机块模型
贝叶斯随机块模型（Bayesian SBM）是一种用于网络社区检测的基于原理的概率方法。它将群组成员身份视为一个潜在变量，并使用贝叶斯推断同时恢复块结构并选择社区数量，从而避免了困扰基于模块度的方法的分辨率限制偏差。
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来源
- Peixoto, T. P. (2014). Efficient Monte Carlo and greedy heuristic for the inference of stochastic block models. Physical Review E, 89(1), 012804. DOI: 10.1103/PhysRevE.89.012804 ↗
- Nowicki, K., & Snijders, T. A. B. (2001). Estimation and prediction for stochastic blockstructures. Journal of the American Statistical Association, 96(455), 1077–1087. DOI: 10.1198/016214501753208735 ↗
如何引用本页
ScholarGate. (2026, June 3). Bayesian Stochastic Block Model (Bayesian SBM). ScholarGate. https://scholargate.app/zh/network-analysis/bayesian-stochastic-block-model
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