Table 1 Performance evaluation of XGBoost model using fivefold cross-validation.

From: A hybrid residue based sequential encoding mechanism with XGBoost improved ensemble model for identifying 5-hydroxymethylcytosine modifications

Method

ACC (%)

SN (%)

Precision (%)

SPE (%)

F1 Score (%)

MCC

AUC

Mismatch

82.35

75.21

78.93

82.46

71.34

0.573

0.813

ANF

83.14

68.34

76.83

84.75

73.05

0.612

0.837

PSTNPss

83.57

70.65

79.28

86.08

75.75

0.652

0.855

ASDC

84.26

75.03

82.48

88.85

80.92

0.724

0.884

DAC

85.18

80.72

85.58

90.57

83.32

0.785

0.912

Hybrid feature (before feature selection)

85.61

82.12

87.52

92.75

85.41

0.814

0.932

Hybrid feature (after feature selection)

86.43

82.35

84.31

90.12

86.71

0.821

0.938

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