Krahasoni metodat

	Log-Loss (Kryqi i Entropisë Kryqëzuar)	Saktësi
Fusha	Vlerësimi i modeleve	Vlerësimi i modeleve
Familja	MCDM	MCDM
Viti i origjinës	1990s	20th century
Krijuesi	Information theory and machine learning literature	Historical statistical foundations
Lloji	Loss function	Evaluation metric
Burimi themelues	Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.	Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874.
Emërtime të tjera	Cross-Entropy Loss, Logloss	Overall Accuracy, Correct Classification Rate
Të lidhura	3	5
Përmbledhja	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.	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.