When making a binary classification or decision, such as a disease diagnosis, precision is the probability that if we make a positive decision, it turns out out to be correct, for example, if we diagnose a person with the disease they really have it. If a decision has a high precision, then the probability of a false positive is low. Often increasing precision reduces recall; this is called the precision–recall trade-off.
Used on pages 189, 441