(b) (ii) and (iii)
Recall = TP / (TP + FN). It considers True Positives (ii) and False Negatives (iii), measuring how well the model identifies all actual positives.
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Recall focuses on minimising missed positives (False Negatives). The formula TP/(TP+FN) uses only True Positives and False Negatives — not False Positives or True Negatives. Students often confuse recall with precision (which uses TP and FP), so remember: Recall = catching all actual positives; Precision = correctness of positive predictions.