is used to measure the quality (that is, the error rate) of the classifier. A true
positive is a case where the prediction was positive, and the person actually had
the disease,while a false positive is a case where the prediction was positive, but
the person did not have the disease. True negative and false negative are defined
similarly for the case where the prediction was negative.