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Sammenlign metoder

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Log-tap (kryssentropitap)×F1-skår×
FagfeltModellevalueringModellevaluering
FamilieMCDMMCDM
Opprinnelsesår1990s1979
OpphavspersonInformation theory and machine learning literatureC. J. van Rijsbergen
TypeLoss functionEvaluation metric
Opprinnelig kildeGoodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press. link ↗van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann. link ↗
AliasCross-Entropy Loss, LoglossF-measure, Harmonic Mean
Relaterte35
SammendragLog-loss measures the difference between predicted probabilities and actual labels, penalizing confident wrong predictions more than uncertain ones. It is a standard loss function in machine learning optimization and evaluates probabilistic classifier calibration.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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ScholarGateSammenlign metoder: Log-Loss (Cross-Entropy Loss) · F1-Score. Hentet 2026-06-18 fra https://scholargate.app/no/compare