Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| F1-novērtējums× | Atcerēšanās (jutība)× | |
|---|---|---|
| Nozare | Modeļu novērtēšana | Modeļu novērtēšana |
| Saime | MCDM | MCDM |
| Izcelsmes gads≠ | 1979 | 20th century |
| Autors≠ | C. J. van Rijsbergen | Historical statistical foundations |
| Tips | Evaluation metric | Evaluation metric |
| Pirmavots≠ | 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 ↗ |
| Citi nosaukumi≠ | F-measure, Harmonic Mean | Sensitivity, True Positive Rate, TPR |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | 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. |
| ScholarGateDatu kopa ↗ |
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