مقایسهٔ روش‌ها

	دقت	زیان لگاریتمی (زیان آنتروپی متقاطع)
حوزه	ارزیابی مدل	ارزیابی مدل
خانواده	MCDM	MCDM
سال پیدایش	20th century	1990s
پدیدآور	Historical statistical foundations	Information theory and machine learning literature
نوع	Evaluation metric	Loss function
منبع بنیادین	Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874.	Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
نام‌های دیگر	Overall Accuracy, Correct Classification Rate	Cross-Entropy Loss, Logloss
مرتبط	5	3
خلاصه	Accuracy is the proportion of correct predictions among the total number of predictions made by a classification model. It is the most intuitive performance metric and measures how often the classifier makes correct predictions overall, regardless of class.	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.