AI engineering glossary · Probability
What is posterior probability?
Posterior probability: The updated probability of an event or parameter after taking the new evidence into account, computed by Bayes' theorem. It combines the prior with the likelihood and becomes the prior for the next round of updating.
Posterior probability: an example
After a transaction is flagged by a fraud rule, the chance it is truly fraudulent rises from the 2% prior to a posterior of, say, 25%.
Related terms
More Probability terms
- Prior probability
- Probability
- Probability axioms
- Probability density function
- Probability distribution
- Probability mass function
- Quantile
- Random experiment
Where you learn it
Posterior probability is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.