Table 9 Effect of data balancing.

From: Predicting drug-target interactions using machine learning with improved data balancing and feature engineering

Dataset

Data Balancing

Model

Accuracy

Precision

Sensitivity

Specificity

F1score

Kappa

MCC

ROC-AUC

MAE

MSE

RMSE

BindingDB_Kd

No

DTC

92.84

92.70

92.84

96.30

92.76

51.91

51.93

76.97

7.16

7.16

26.76

MLP

94.15

93.73

94.15

97.63

93.89

58.10

58.43

88.84

5.85

5.85

24.18

RFC

94.64

94.10

94.64

98.63

94.12

58.17

59.67

93.17

5.36

5.36

23.16

GAN

DTC

96.47

96.47

96.47

96.45

96.47

92.93

92.93

96.66

3.53

3.53

18.80

MLP

97.13

97.14

97.13

97.91

97.13

94.26

94.27

99.15

2.87

2.87

16.95

RFC

97.46

97.49

97.46

98.82

97.46

94.91

94.95

99.42

2.54

2.54

15.95

BindingDB_Ki

No

DTC

84.26

84.24

84.26

89.81

84.25

56.01

56.01

80.51

15.74

15.74

39.67

MLP

84.45

83.73

84.45

92.53

83.90

53.79

54.19

87.68

15.55

15.55

39.44

RFC

87.22

86.86

87.22

93.20

86.97

63.03

63.18

91.49

12.78

12.78

35.75

GAN

DTC

89.68

89.68

89.68

89.92

89.68

79.36

79.36

90.70

10.32

10.32

32.13

MLP

89.61

89.66

89.61

91.35

89.60

79.22

79.27

96.14

10.39

10.39

32.24

RFC

91.69

91.74

91.69

93.40

91.69

83.39

83.44

97.32

8.31

8.31

28.82

BindingDB_IC50

No

DTC

89.74

89.71

89.74

94.14

89.73

55.52

55.52

80.79

10.26

10.26

32.03

MLP

89.94

89.18

89.94

95.78

89.44

52.33

52.79

89.34

10.06

10.06

31.72

RFC

91.99

91.57

91.99

96.54

91.71

63.03

63.30

93.41

8.01

8.01

28.30

GAN

DTC

94.12

94.12

94.12

94.04

94.12

88.23

88.23

94.77

5.88

5.88

24.26

MLP

94.27

94.39

94.27

96.92

94.26

88.53

88.66

98.36

5.73

5.73

23.94

RFC

95.40

95.41

95.40

96.42

95.39

90.79

90.81

98.97

4.60

4.60

21.46