方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| F1分数× | 召回率（灵敏度）× | |
|---|---|---|
| 领域 | 模型评估 | 模型评估 |
| 方法族 | MCDM | MCDM |
| 起源年份≠ | 1979 | 20th century |
| 提出者≠ | C. J. van Rijsbergen | Historical statistical foundations |
| 类型 | Evaluation metric | Evaluation metric |
| 开创性文献≠ | van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann. link ↗ | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗ |
| 别名≠ | F-measure, Harmonic Mean | Sensitivity, True Positive Rate, TPR |
| 相关 | 5 | 5 |
| 摘要≠ | 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. | Recall measures the proportion of actual positive cases that were correctly identified by the classifier. It answers the question: 'Of all the cases that were truly positive, how many did we find?' Recall is critical in scenarios where missing positive cases is costly. |
| ScholarGate数据集 ↗ |
|
|