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Table 3 Performances of the all voting ensemble classifiers on the main dataset

From: Integrative approach for detecting membrane proteins

Algorithm

Sensitivity

Specificity

Accuracy

MCC

OET-KNN V500

85.10

94.51

89.86

0.8004

OET-KNN V50

85.61

93.57

89.64

0.7950

KNN V500

85.50

91.77

88.68

0.7747

KNN V50

86.19

90.40

88.32

0.7669

SVM

86.48

93.72

90.15

0.8047

GBM

84.52

93.32

88.98

0.7820

RF

79.38

93.95

86.76

0.7423

  1. all voting with OET-KNN V500, highlighted in italics, reflects the LOOCV performance of the MemType-2L method on DS-M
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BMC Bioinformatics

ISSN: 1471-2105

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