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| 혼동 행렬× | 특이도(Specificity)× | |
|---|---|---|
| 분야 | 모델 평가 | 모델 평가 |
| 계열 | MCDM | MCDM |
| 기원 연도 | 20th century | 20th century |
| 창시자≠ | Statistical foundations | Historical statistical foundations |
| 유형≠ | Evaluation visualization | Evaluation metric |
| 원전≠ | Everitt, B. S., & Hothorn, T. (2005). A Handbook of Statistical Analyses Using R. Chapman and Hall/CRC. link ↗ | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗ |
| 별칭 | Error Matrix, Contingency Table | True Negative Rate, TNR |
| 관련 | 5 | 5 |
| 요약≠ | The confusion matrix is a table that displays the counts of true positives, true negatives, false positives, and false negatives. It provides a complete picture of where a classifier makes correct and incorrect predictions, enabling calculation of all other classification metrics. | Specificity measures the proportion of actual negative cases that were correctly identified as negative by the classifier. It answers the question: 'Of all the cases that were truly negative, how many did we correctly reject?' Specificity is complementary to recall and is essential when false positives are costly. |
| ScholarGate데이터셋 ↗ |
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