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Version du 28 octobre 2021 à 11:03
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Cromwell’s Rule Cromwell’s rule states that no prior probability distribution should be 100% true or false, since accuracy requires allowing for unknowable “X factors.” With the exception of logic statements that need a definitive true or false decision, such as 1+1=2 or If than And statements, there should not be complete confidence of an outcome when assigning initial probabilities to a model. This rule is applied to both Bayesian and Frequentist approaches by ensuring that the prior probability distribution for any outcome does not equal 0 (will never happen) or 1 (guaranteed to happen).
Contributeurs: Imane Meziani, wiki
