Sammenlign metoder

	Brier Score	Log-tab (Krydsentropi-tab)
Fagområde	Modelevaluering	Modelevaluering
Familie	MCDM	MCDM
Oprindelsesår	1950	1990s
Ophavsperson	Glenn W. Brier	Information theory and machine learning literature
Type	Loss function	Loss function
Oprindelig kilde	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.
Aliasser	Mean Squared Probability Error	Cross-Entropy Loss, Logloss
Relaterede	3	3
Resumé	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.