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Table 2 Classwise performance measures

From: The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation

Sensitivity, recall, true positive rate

\({= \frac {\text {TP}}{\text {TP}+\text {FN}} = \frac {\text {TP}}{n^{+}}}\)

Specificity, true negative rate

\({= \frac {\text {TN}}{\text {TN}+\text {FP}}= \frac {\text {TN}}{n^{-}}}\)

Positive predictive value, precision

\({= \frac {\text {TP}}{\text {TP}+\text {FP}}}\)

Negative predictive value

\({= \frac {\text {TN}}{\text {TN}+\text {FN}}}\)

False positive rate, fallout

\({= \frac {\text {FP}}{\text {FP}+\text {TN}} = \frac {\text {FP}}{n^{-}}}\)

False discovery rate

\({= \frac {\text {FP}}{\text {FP}+\text {TP}}}\)

  1. TP: true positives. TN: true negatives. FP: false positives. FN: false negatives