Bayes' Theorem
A mathematical theorem in probability theory that computes a posterior probability from a prior probability and a likelihood function. It is the foundation of Bayesian inference.
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Under the confusion matrix scenario set in the article, the precision calculated by the Bayesian formula is about 42.86%, exactly consistent with the result of the traditional definition TP/(TP+FP).
When both Prevalence and FPR are derived from the same confusion matrix, the Bayesian formula naturally simplifies to TP/(TP+FP).
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Under the confusion matrix scenario set in the article, the precision calculated by the Bayesian formula is about 42.86%, exactly consistent with the result of the traditional definition TP/(TP+FP).
50%UnverifiedWhen both Prevalence and FPR are derived from the same confusion matrix, the Bayesian formula naturally simplifies to TP/(TP+FP).
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