Bayesian methods
Bayesian Network
A Bayesian network is a probabilistic graphical model, introduced by Judea Pearl in 1988, that encodes a set of variables and their conditional dependencies as a directed acyclic graph (DAG). Each node represents a variable; each directed edge encodes a direct probabilistic influence. By combining Bayes' rule with the graph's conditional independence structure, the model supports reasoning under uncertainty — computing the probability of any variable given observed evidence about others.
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Sources
- Pearl, J. (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann. ISBN: 978-1558604797
Related methods
Referenced by
Bayesian Dose-Response AnalysisBayesian Factor AnalysisBayesian Knowledge Graph AnalysisBayesian Network with Measurement ErrorDempster-Shafer TheoryDynamic Bayesian NetworkFault Tree AnalysisFCI AlgorithmFuzzy Cognitive MapsGES AlgorithmHierarchical Bayesian NetworkHybrid Fault Tree AnalysisKnowledge TracingMultilevel Bayesian NetworkNOTEARSRobust Bayesian Network