Loi de probabilité a priori


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prior distribution

“In Bayesian inference, we assume that the unknown quantity to be estimated has many plausible values modeled by what's called a prior distribution. Bayesian inference is then using data (that is considered as unchanging) to build a tighter posterior distribution for the unknown quantity.”[zumel] See also Bayes' Theorem

see posterior distribution


Source : Datascience glossary

Contributeurs: Claire Gorjux, wiki