ML Notes : false positive, false negative, true positive, true negative

A good way to think of this is to remember that positive/negative
refers to the classifier's prediction, and true/false refers to
whether the prediction is correct or not. So, a false positive is
something that was incorrectly predicted as positive, and therefore an
actual negative (e.g., a ham email misclassified as spam, or a healthy
patient misclassified as having the disease in
question).

Peter Flach