Porovnat metody

	Brierovo skóre	Log-Loss (křížová entropie)
Obor	Hodnocení modelů	Hodnocení modelů
Rodina	MCDM	MCDM
Rok vzniku	1950	1990s
Tvůrce	Glenn W. Brier	Information theory and machine learning literature
Typ	Loss function	Loss function
Původní zdroj	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.
Další názvy	Mean Squared Probability Error	Cross-Entropy Loss, Logloss
Příbuzné	3	3
Shrnutí	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.