Editing Posterior probability (section)

==Classification==

In [[Statistical classification|classification]], posterior probabilities reflect the uncertainty of assessing an observation to particular class, see also [[class-membership probabilities]]. 
While [[statistical classification]] methods by definition generate posterior probabilities, Machine Learners usually supply membership values which do not induce any probabilistic confidence. It is desirable to transform or rescale membership values to class-membership probabilities, since they are comparable and additionally more easily applicable for post-processing.<ref>{{Cite journal |last1=Boedeker |first1=Peter |last2=Kearns |first2=Nathan T. |date=2019-07-09 |title=Linear Discriminant Analysis for Prediction of Group Membership: A User-Friendly Primer |url=http://journals.sagepub.com/doi/10.1177/2515245919849378 |journal=Advances in Methods and Practices in Psychological Science |language=en |volume=2 |issue=3 |pages=250–263 |doi=10.1177/2515245919849378 |s2cid=199007973 |issn=2515-2459|url-access=subscription }}</ref>