A binary classifier for spam detection produces 90 true positives, 10 false negatives, 5 false positives, and 895 true negatives. Which metric directly measures the proportion of all actual spam emails that were correctly detected?

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B. Recall (Sensitivity). Recall (also called sensitivity or true positive rate) = TP divided by (TP + FN) = 90 divided by 100 = 90%. It measures the proportion of all actual positive cases that the model correctly identified.

A binary classifier for spam detection produces 90 true positives, 10 false negatives, 5 false positives, and 895 true negatives. Which metric directly measures the proportion of all actual spam emails that were correctly detected?

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