What is the difference between recall and specificity in binary classification evaluation?

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What is the difference between recall and specificity in binary classification evaluation?

Key points

  • Recall focuses on actual positives; specificity focuses on actual negatives
  • Recall = TP/(TP+FN); specificity = TN/(TN+FP)
  • Both metrics contribute to the ROC curve analysis
  • Understanding both metrics is crucial for evaluating model performance

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