方法对比
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| 平衡准确率× | F1分数× | |
|---|---|---|
| 领域 | 模型评估 | 模型评估 |
| 方法族 | MCDM | MCDM |
| 起源年份≠ | 2010 | 1979 |
| 提出者≠ | Brodersen, Ong, Stephan, and Buhmann | C. J. van Rijsbergen |
| 类型 | Evaluation metric | Evaluation metric |
| 开创性文献≠ | Brodersen, K. H., Ong, C. S., Stephan, K. E., & Buhmann, J. M. (2010). The balanced accuracy and its posterior distribution. 20th International Conference on Pattern Recognition (ICPR), 3121-3124. DOI ↗ | van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann. link ↗ |
| 别名 | Average Recall, Equal-weight Average Sensitivity | F-measure, Harmonic Mean |
| 相关 | 5 | 5 |
| 摘要≠ | Balanced accuracy is the average of recall values computed for each class separately. It corrects for class imbalance by giving equal weight to the performance on each class, regardless of class frequency in the dataset. | 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. |
| ScholarGate数据集 ↗ |
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