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Comparar métodos

Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.

Perda Logarítmica (Entropia Cruzada)×F1-Score×
ÁreaAvaliação de modelosAvaliação de modelos
FamíliaMCDMMCDM
Ano de origem1990s1979
Autor originalInformation theory and machine learning literatureC. J. van Rijsbergen
TipoLoss functionEvaluation metric
Fonte seminalGoodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press. link ↗van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann. link ↗
Outros nomesCross-Entropy Loss, LoglossF-measure, Harmonic Mean
Relacionados35
ResumoLog-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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ScholarGateComparar métodos: Log-Loss (Cross-Entropy Loss) · F1-Score. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare