Machine learningNetwork science
贝叶斯社群侦测
贝叶斯社群侦测通过将社群成员身份视为未观测变量，并利用贝叶斯推断（通常通过马尔可夫链蒙特卡洛或变分方法）计算所有可能划分的后验分布，来推断网络中潜在的群组结构。与模块度优化不同，它能从数据中选择社群数量，并为每个节点分配提供原则性的不确定性估计。
阅读完整方法
仅限会员
登录使用免费账户登录即可阅读本节。
Method map
The neighbourhood of related methods — select a node to explore.
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 Community Detection in Networks. ScholarGate. https://scholargate.app/zh/network-analysis/bayesian-community-detection
Which method?
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.
Compare side by side →