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AUC Precision-Recall×Skor F1×
BidangPenilaian ModelPenilaian Model
KeluargaMCDMMCDM
Tahun asal20061979
PengasasDavis and GoadrichC. J. van Rijsbergen
JenisEvaluation metricEvaluation metric
Sumber perintisDavis, J., & Goadrich, M. (2006). The relationship between precision-recall and ROC curves. Proceedings of the 23rd International Conference on Machine Learning, 233-240. DOI ↗van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann. link ↗
AliasPR AUC, PR CurveF-measure, Harmonic Mean
Berkaitan45
RingkasanThe Precision-Recall Area Under the Curve (PR AUC) is the area under the curve formed by plotting recall on the x-axis and precision on the y-axis. It is particularly useful for evaluating classifiers on imbalanced datasets, where it is often more informative than ROC AUC.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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ScholarGateBandingkan kaedah: Precision-Recall AUC · F1-Score. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare