There are several concepts for classification performance : precision, negative predictive value, recall, and specificity.
Why do people often choose only precision and recall together ?
Why not negative predictive value or specificity?
Why do they choose F score in addition to precision and recall?
Can precision and recall alone deal with the imbalance problem between sample sizes of different classes?