Precision

In statistics and machine learning, precision is a measure of how often the positives identified by a learning model are true positives. This is a division of true positives (based on the confusion matrix) by all estimated positives (=true positives + false positives). The precision metric is commonly used in conjunction with recall, to evaluate ... Read more

recall

Recall (also known as sensitivity) is the ratio of true positives (based on the confusion matrix) by all positives (=true positives + false negatives). It is commonly used in conjunction with precision and it is needed when we must minimize false negatives. Recall can be considered the opposite metric of specificity. Recall is a measure ... Read more