Precision
A classification metric that measures the proportion of true positive predictions out of all the positive predictions a machine learning model actually made.
Think of It Like This
Like a sniper's accuracy metric: out of all the shots they actually took, what percentage successfully hit the intended target?
Precision is the metric of choice when the cost of a false positive is extremely high. For example, a spam filter blocking a crucial work email is unacceptable, so the filter must be highly precise. It is almost always evaluated in direct tension with Recall, as maximizing one naturally degrades the other.