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| Dokładność (Accuracy)× | Wynik Brier (Brier Score)× | |
|---|---|---|
| Dziedzina | Ocena modeli | Ocena modeli |
| Rodzina | MCDM | MCDM |
| Rok powstania≠ | 20th century | 1950 |
| Twórca≠ | Historical statistical foundations | Glenn W. Brier |
| Typ≠ | Evaluation metric | Loss function |
| Źródło pierwotne≠ | 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 ↗ |
| Inne nazwy≠ | Overall Accuracy, Correct Classification Rate | Mean Squared Probability Error |
| Pokrewne≠ | 5 | 3 |
| Podsumowanie≠ | 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. |
| ScholarGateZbiór danych ↗ |
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