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Table 14 Classification results on ISBI 2017 dataset

From: An implementation of normal distribution based segmentation and entropy controlled features selection for skin lesion detection and classification

Method

Sensitivity (%)

Precision (%)

Specificity (%)

FNR (%)

FPR

Accuracy (%)

AUC

DT

74.5

75.0

77

25.5

0.255

74.8

0.77

QDA

77.5

78.0

81

22.5

0.254

77.6

0.78

Q-SVM

86.5

86.5

87

13.8

0.135

86.2

0.92

LR

84.5

84.5

86

15.4

0.135

84.6

0.92

NB

79.5

80.0

83

21.5

0.212

79.5

0.80

W-KNN

87.5

88.0

88

12.2

0.125

87.8

0.92

EBT

86.0

83.5

92

14.2

0.140

85.8

0.91

ESDA

83.5

83.5

87.0

16.5

0.165

83.5

0.90

Proposed

88.5

88.0

91.0

11.8

0.120

88.2

0.93

  1. Data in bold are significant