Recall

\(\frac{TP}{TP+FN}\)

[31, 35, 36, 38, 39, 42, 45, 48, 51, 57, 58, 60, 78]

13

False positive rate (FPR)

\(\frac{FP}{TN+FP}\)

[31, 33, 38,39,40, 44, 47, 54, 57,58,59, 71]

12

False negative rate (FNR)

\(\frac{FN}{TP+FN}\)

[40, 44, 47, 48, 54, 71]

6

Precision

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

[35, 36, 38, 51, 78]

5

Accuracy

\(\frac{TP+TN}{TP+TN+FP+FN}\)

[37, 48, 51, 79]

4

Fscore

\(2 \times \frac{precision \times recall}{precision + recall}\)

[35, 36]

2

Matthew’s correlation coefficient (MCC)

\(\frac{TP \times TN  FP \times FN}{\sqrt{(TP+FP)(TP+FN)(TN+FP)(TN+FN)}}\)

[65]

1

Regression metrics

Root mean squared error (RMSE)

\(\sqrt{MSE}\)

[46, 62, 64, 66]

4

Mean squared error (MSE)

\(\frac{1}{n}\sum _{i=1}^n(x_i  {\hat{x}}_i)^2\)

[72, 76]

2

Mean absolute error (MAE)

\(\frac{1}{n}\sum _{i=1}^{n}x_i  {\hat{x}}_i\)

[61, 67]

2

Mean relative error (MRE)

\(\frac{1}{n}\sum _{i=1}^{n}\frac{x_i  {\hat{x}}_i}{x_i}\)

[30, 67]

2
