Recall

Also known as the sensitivity or true positive rate.

Recall should ideally be 1, when $TP=TP+FN$ where $FN=0$ i.e. no false negatives.

In an ideal classifier, precision and recall should be one. Hence, we should find a metric that takes into account both precision and recall.

Essential when missing positive cases has significant consequences.