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| Precyzja× | Wynik F1× | |
|---|---|---|
| Dziedzina | Ocena modeli | Ocena modeli |
| Rodzina | MCDM | MCDM |
| Rok powstania≠ | 20th century | 1979 |
| Twórca≠ | Historical statistical foundations | C. J. van Rijsbergen |
| Typ | Evaluation metric | Evaluation metric |
| Źródło pierwotne≠ | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗ | van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann. link ↗ |
| Inne nazwy | Positive Predictive Value, PPV | F-measure, Harmonic Mean |
| Pokrewne | 5 | 5 |
| Podsumowanie≠ | 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. | The F1-score is the harmonic mean of precision and recall, providing a single metric that balances both concerns. It was introduced by van Rijsbergen in information retrieval and has become a standard metric for evaluating classification models where both precision and recall are important. |
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