The Bayes factor is a ratio of two competing statistical models represented by their evidence, and is used to quantify the support for one model over the...

probability theory and statistics, Bayes' theorem (alternatively Bayes' law or Bayes' rule), named after Thomas Bayes, describes the probability of an event...

naive Bayes models are known under a variety of names, including simple Bayes and independence Bayes. All these names reference the use of Bayes' theorem...

formulating a specific case of the theorem that bears his name: Bayes' theorem. Bayes never published what would become his most famous accomplishment;...

high-dimensional. Empirical Bayes methods can be seen as an approximation to a fully Bayesian treatment of a hierarchical Bayes model. In, for example, a...

\{C(X)\neq Y\}.} The Bayes classifier is C Bayes ( x ) = argmax r ∈ { 1 , 2 , … , K } P ⁡ ( Y = r ∣ X = x ) . {\displaystyle C^{\text{Bayes}}(x)={\underset...

particular, differences in BIC should never be treated like transformed Bayes factors. It is important to keep in mind that the BIC can be used to compare...

In estimation theory and decision theory, a Bayes estimator or a Bayes action is an estimator or decision rule that minimizes the posterior expected value...

can be stated schematically as posterior odds = prior odds × Bayes factor Empirical Bayes methods Lindley's paradox Marginal probability Bayesian information...

A Bayesian network (also known as a Bayes network, Bayes net, belief network, or decision network) is a probabilistic graphical model that represents a...