Table 4 The performance comparison between different methods on the Yeast dataset.

Yangs’ work⁴⁰

Cod1

75.08 ± 1.13

75.81 ± 1.20

74.75 ± 1.23

N/A

Cod2

80.04 ± 1.06

76.77 ± 0.69

82.17 ± 1.35

N/A

Cod3

80.41 ± 0.47

78.14 ± 0.90

81.86 ± 0.99

N/A

Cod4

86.15 ± 1.17

81.03 ± 1.74

90.24 ± 0.45

N/A

Zhous’ work⁴¹

SVM + LD

88.56 ± 0.33

87.37 ± 0.22

89.50 ± 0.60

77.15 ± 0.68

Yous’ work⁴²

PCA-EELM

87.00 ± 0.29

86.15 ± 0.43

87.59 ± 0.32

77.36 ± 0.44

Guos’ work³⁰

ACC

89.33 ± 2.67

89.93 ± 3.68

88.87 ± 6.16

N/A

AC

87.36 ± 1.38

87.30 ± 4.68

87.82 ± 4.33

N/A

Wangs’ work⁴³

SAE

96.60 ± 0.22

93.73 ± 0.46

99.36 ± 0.41

93.41 ± 0.41

Dus’ work⁴⁴

DeepPPI

94.43 ± 0.30

N/A

96.65 ± 0.59

88.97 ± 0.62

Zhangs’ work⁴⁵

EnsDNN

95.29 ± 0.43

95.12 ± 0.45

95.45 ± 0.89

90.59 ± 0.86

Patels’ work⁴⁶

DeepInteract

92.67

86.85

98.31

85.96

Our model

CNN-FSRF

97.75 ± 0.54

99.61 ± 0.22

95.89 ± 1.02

96.04 ± 1.05