Linganisha mbinu

	Alama ya Brier	Log-Loss (aucdoti ya msalaba-entropi)
Nyanja	Tathmini ya Modeli	Tathmini ya Modeli
Familia	MCDM	MCDM
Mwaka wa asili	1950	1990s
Mwanzilishi	Glenn W. Brier	Information theory and machine learning literature
Aina	Loss function	Loss function
Chanzo asilia	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.
Majina mbadala	Mean Squared Probability Error	Cross-Entropy Loss, Logloss
Zinazohusiana	3	3
Muhtasari	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.