Bayesian methods
贝叶斯网络
贝叶斯网络是一种概率图模型，由 Judea Pearl 于 1988 年首次提出，它将一组变量及其条件依赖关系编码在一个有向无环图（DAG）中。每个节点代表一个变量；每条有向边编码一种直接的概率影响。通过将贝叶斯规则与图的条件独立性结构相结合，该模型支持不确定性推理——计算任何变量在给定其他变量的观测证据下的概率。
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Method map
The neighbourhood of related methods — select a node to explore.
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来源
- Pearl, J. (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann. ISBN: 978-1558604797
如何引用本页
ScholarGate. (2026, June 1). Bayesian Network. ScholarGate. https://scholargate.app/zh/bayesian/bayesian-network
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.
- Bayesian Regression贝叶斯↔ compare
- 因果识别（使用do演算）因果推断↔ compare
- 马尔可夫链蒙特卡洛 (MCMC)贝叶斯↔ compare
- 结构方程模型研究统计学↔ compare