방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 혼동 행렬× | 매튜 상관 계수× | |
|---|---|---|
| 분야 | 모델 평가 | 모델 평가 |
| 계열 | MCDM | MCDM |
| 기원 연도≠ | 20th century | 1975 |
| 창시자≠ | Statistical foundations | Brian W. Matthews |
| 유형≠ | Evaluation visualization | Evaluation metric |
| 원전≠ | Everitt, B. S., & Hothorn, T. (2005). A Handbook of Statistical Analyses Using R. Chapman and Hall/CRC. link ↗ | Matthews, B. W. (1975). Comparison of predicted and observed secondary structure of T4 phage lysozyme. Biochimica et Biophysica Acta (BBA)-Protein Structure, 405(2), 442-451. DOI ↗ |
| 별칭 | Error Matrix, Contingency Table | Phi Coefficient, Binary Classification Correlation |
| 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. | The Matthews Correlation Coefficient (MCC) is a correlation measure between predicted and actual binary classifications. It ranges from -1 to 1 and is considered one of the most reliable single-score metrics for evaluating binary classifiers, especially on imbalanced datasets. |
| ScholarGate데이터셋 ↗ |
|
|