A table layout that shows the results of a two-class/binary classifier in which columns correspond to the predicted classifications from the model and rows correspond to the observed classifications.
Note: A confusion matrix highlights the numbers of true positives
TP (positives classified as positive), true negatives
TN (negatives classified as negative), false positives
FP (negatives classified as positive) and false negatives
FN (positives classified as negatives).
Source: PAC, 2016,
88, 239. (
Glossary of terms used in computational drug design, part II (IUPAC Recommendations 2015)) on page 244 [
Terms] [
Paper]