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حوزهبیزیبیزی
خانوادهBayesian methodsBayesian methods
سال پیدایش1988 (Bayesian networks); measurement-error extension: 1990s1988
پدیدآورJudea Pearl (Bayesian networks); measurement-error extension developed in epidemiology and psychometrics through the 1990s–2000sJudea Pearl
نوعProbabilistic graphical model with latent variablesProbabilistic graphical model
منبع بنیادینPearl, J. (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann. ISBN: 978-1558604797Pearl, J. (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann. ISBN: 978-1558604797
نام‌های دیگرBN-ME, errors-in-variables Bayesian network, Bayesian graphical model with measurement error, latent variable Bayesian networkBayes network, belief network, probabilistic graphical model, directed graphical model
مرتبط54
خلاصهA Bayesian network with measurement error is a probabilistic directed acyclic graphical model in which one or more node variables are observed with error rather than exactly. Latent true-value nodes are introduced for mismeasured variables, and the model jointly infers the network's conditional probability parameters and the unobserved true values from the noisy observations.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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ScholarGateمقایسهٔ روش‌ها: Bayesian Network with Measurement Error · Bayesian Network. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare