مقایسهٔ روش‌ها

	زیان لگاریتمی (زیان آنتروپی متقاطع)	امتیاز بریر
حوزه	ارزیابی مدل	ارزیابی مدل
خانواده	MCDM	MCDM
سال پیدایش	1990s	1950
پدیدآور	Information theory and machine learning literature	Glenn W. Brier
نوع	Loss function	Loss function
منبع بنیادین	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.
نام‌های دیگر	Cross-Entropy Loss, Logloss	Mean Squared Probability Error
مرتبط	3	3
خلاصه	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.