Porovnať metódy

	Presnosť	Log-loss (krížová entropia)
Odbor	Hodnotenie modelov	Hodnotenie modelov
Rodina	MCDM	MCDM
Rok vzniku	20th century	1990s
Tvorca	Historical statistical foundations	Information theory and machine learning literature
Typ	Evaluation metric	Loss function
Pôvodný zdroj	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.
Ďalšie názvy	Overall Accuracy, Correct Classification Rate	Cross-Entropy Loss, Logloss
Príbuzné	5	3
Zhrnutie	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.