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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