قارن الطرق

	خسارة اللوغاريتم (خسارة الإنتروبيا المتقاطعة)	درجة برير
المجال	تقييم النماذج	تقييم النماذج
العائلة	MCDM	MCDM
سنة النشأة	1990s	1950
صاحب الطريقة	Information theory and machine learning literature	Glenn W. Brier
النوع	Loss function	Loss function
المصدر التأسيسي	Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.	Brier, G. W. (1950). Verification of forecasts expressed in terms of probability. Monthly Weather Review, 78(1), 1-3.
الأسماء البديلة	Cross-Entropy Loss, Logloss	Mean Squared Probability Error
ذات صلة	3	3
الملخص	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.	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.