Σύγκριση μεθόδων

	Πίνακας Σύγχυσης	Ειδικότητα
Πεδίο	Αξιολόγηση Μοντέλων	Αξιολόγηση Μοντέλων
Οικογένεια	MCDM	MCDM
Έτος προέλευσης	20th century	20th century
Δημιουργός	Statistical foundations	Historical statistical foundations
Τύπος	Evaluation visualization	Evaluation metric
Θεμελιώδης πηγή	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.
Εναλλακτικές ονομασίες	Error Matrix, Contingency Table	True Negative Rate, TNR
Συναφείς	5	5
Σύνοψη	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.	Specificity measures the proportion of actual negative cases that were correctly identified as negative by the classifier. It answers the question: 'Of all the cases that were truly negative, how many did we correctly reject?' Specificity is complementary to recall and is essential when false positives are costly.