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| 정확도× | Brier Score× | |
|---|---|---|
| 분야 | 모델 평가 | 모델 평가 |
| 계열 | MCDM | MCDM |
| 기원 연도≠ | 20th century | 1950 |
| 창시자≠ | Historical statistical foundations | Glenn W. Brier |
| 유형≠ | Evaluation metric | Loss function |
| 원전≠ | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗ | Brier, G. W. (1950). Verification of forecasts expressed in terms of probability. Monthly Weather Review, 78(1), 1-3. DOI ↗ |
| 별칭≠ | Overall Accuracy, Correct Classification Rate | Mean Squared Probability Error |
| 관련≠ | 5 | 3 |
| 요약≠ | Accuracy is the proportion of correct predictions among the total number of predictions made by a classification model. It is the most intuitive performance metric and measures how often the classifier makes correct predictions overall, regardless of class. | The Brier score measures the mean squared difference between predicted probabilities and actual binary outcomes. It is a simple, interpretable metric for evaluating the accuracy of probabilistic predictions, particularly in weather forecasting and medical diagnosis. |
| ScholarGate데이터셋 ↗ |
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