Comparar métodos

	Score de Brier	Perda Logarítmica (Entropia Cruzada)
Área	Avaliação de modelos	Avaliação de modelos
Família	MCDM	MCDM
Ano de origem	1950	1990s
Autor original	Glenn W. Brier	Information theory and machine learning literature
Tipo	Loss function	Loss function
Fonte seminal	Brier, G. W. (1950). Verification of forecasts expressed in terms of probability. Monthly Weather Review, 78(1), 1-3.	Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
Outros nomes	Mean Squared Probability Error	Cross-Entropy Loss, Logloss
Relacionados	3	3
Resumo	The Brier score measures the mean squared difference between predicted probabilities and actual binary outcomes. It is a simple, interpretable metric for evaluating the accuracy of probabilistic predictions, particularly in weather forecasting and medical diagnosis.	Log-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.