Table 2 Confusion matrix, precision, recall, accuracy and F1 score of the predictions

Support vector machine

Confusion matrix

TN

51

2

17

15

48

5

TP

1

47

7

41

4

28

AUC (95%CI)

0.987(0.964–1.00)

0.721(0.604–0.839)

0.962(0.924–1.00)

Precision

0.959

0.732

0.848

Recall

0.979

0.854

0.875

Accuracy

0.970

0.725

0.894

F1 score

0.970

0.716

0.894

Random forest

Confusion matrix

TN

52

1

23

9

48

5

TP

2

46

8

40

6

26

AUC (95%CI)

0.994(0.979–1.00)

0.866(0.779–0.954)

0.945(0.899–0.992)

Precision

0.979

0.816

0.839

Recall

0.958

0.833

0.812

Accuracy

0.970

0.788

0.870

F1 score

0.970

0.787

0.870

K-nearest neighbor

Confusion matrix

TN

48

5

18

14

50

3

TP

1

47

3

45

5

27

AUC (95%CI)

0.970(0.936–1.00)

0.869(0.783–0.956)

0.940(0.891–0.989)

Precision

0.904

0.763

0.900

Recall

0.979

0.938

0.844

Accuracy

0.940

0.788

0.906

F1 score

0.941

0.776

0.905