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| 재현율 (Recall, 민감도)× | 정밀도(Precision)× | |
|---|---|---|
| 분야 | 모델 평가 | 모델 평가 |
| 계열 | MCDM | MCDM |
| 기원 연도 | 20th century | 20th century |
| 창시자 | Historical statistical foundations | Historical statistical foundations |
| 유형 | Evaluation metric | Evaluation metric |
| 원전 | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗ | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗ |
| 별칭≠ | Sensitivity, True Positive Rate, TPR | Positive Predictive Value, PPV |
| 관련 | 5 | 5 |
| 요약≠ | Recall measures the proportion of actual positive cases that were correctly identified by the classifier. It answers the question: 'Of all the cases that were truly positive, how many did we find?' Recall is critical in scenarios where missing positive cases is costly. | Precision measures the proportion of positive predictions that were actually correct. It answers the question: 'Of all the cases we predicted as positive, how many were truly positive?' Precision is critical in scenarios where false positives are costly. |
| ScholarGate데이터셋 ↗ |
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