Example: “Predicting a mail as Spam or Not Spam”
False Positive: Mail is predicted as “spam” but it is “not spam”.
False Negative: Mail is predicted as “not spam” but it is “spam”.
Of course, too many False Negatives will make the spam filter ineffective but False
Positives may cause important mails to be missed and hence Precision is not usable.
Study more about EValuation at Evaluation