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Table 2 Comparison of performance with different dimensions of hidden states for sub-classifiers \(f_{5}, f_{10}, f_{15}\)

From: Protein–protein interaction prediction based on ordinal regression and recurrent convolutional neural networks

Dimension

Accuracy (%)

Precision (%)

Sensitivity (%)

Specificity (%)

\(F_{1}\)Score (%)

Sub-classifier \(f_{5}\)

10

85.98

92.87

88.78

66.04

90.78

25

88.53

92.60

92.70

74.36

92.63

50

90.35

93.25

94.42

79.61

93.83

75

90.18

94.21

93.10

76.84

93.65

Sub-classifier \(f_{10}\)

10

79.90

82.59

77.56

77.35

80.00

25

85.22

84.22

87.95

86.40

86.05

50

89.15

89.24

89.90

89.05

89.57

75

88.59

88.02

90.27

89.24

89.13

Sub-classifier \(f_{15}\)

10

90.67

87.68

74.42

91.51

80.51

25

94.53

91.11

87.39

95.66

89.21

50

96.17

93.03

92.10

97.25

92.57

75

96.12

92.96

91.99

97.21

92.47

  1. The values in each column represents the experimental results for each criterion of performance. Maximal values in each column is shown in bold