Uporedite metode

	Matrica konfuzije	Preciznost
Oblast	Evaluacija modela	Evaluacija modela
Porodica	MCDM	MCDM
Godina nastanka	20th century	20th century
Tvorac	Statistical foundations	Historical statistical foundations
Tip	Evaluation visualization	Evaluation metric
Temeljni izvor	Everitt, B. S., & Hothorn, T. (2005). A Handbook of Statistical Analyses Using R. Chapman and Hall/CRC.	Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874.
Drugi nazivi	Error Matrix, Contingency Table	Positive Predictive Value, PPV
Srodne	5	5
Sažetak	The confusion matrix is a table that displays the counts of true positives, true negatives, false positives, and false negatives. It provides a complete picture of where a classifier makes correct and incorrect predictions, enabling calculation of all other classification metrics.	Precision measures the proportion of positive predictions that were actually correct. It answers the question: 'Of all the cases we predicted as positive, how many were truly positive?' Precision is critical in scenarios where false positives are costly.