How is Recall defined in classification, and when is it an important metric to consider?

False Positives / Total predictions
True Negatives / (True Negatives + False Positives)
True Positives / (True Positives + False Negatives)
True Positives / (True Positives + False Positives)

Recall is the ratio of true positive predictions to the sum of true positives and false negatives. It measures the ability to correctly identify all relevant instances and is crucial when the cost of false negatives is high, such as in medical diagnoses.

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