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Table 4 Performances of the selective voting ensemble classifiers on the main dataset

From: Integrative approach for detecting membrane proteins

Algorithm

Sensitivity

Specificity

Accuracy

MCC

OET-KNN V500

88.99

94.00

91.53

0.8314

OET-KNN V50

86.58

94.43

90.56

0.8133

KNN V500

89.01

93.63

91.35

0.8280

KNN V50

86.55

91.92

89.27

0.7863

SVM

87.12

93.72

90.46

0.8107

GBM

85.30

93.45

89.44

0.7909

RF

80.19

93.71

87.04

0.7468

  1. Selective voting with OET-KNN V500, highlighted in italics, refers to the method that achieved the highest MCC and is the method utilized in TooT-M
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BMC Bioinformatics

ISSN: 1471-2105

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