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Table 13 Classification results on ISBI 2016 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 63.0 62.0 79.0 28.5 0.370 71.5 0.63
QDA 68.0 65.5 79.0 26.4 0.320 73.6 0.74
Q-SVM 68.5 78.5 95.0 17.7 0.315 82.3 0.81
LR 67.0 65.0 79.0 26.1 0.330 72.9 0.69
NB 74.5 77.0 91.5 17.1 0.255 82.9 0.84
W-KNN 70.5 75.0 91.0 18.7 0.295 81.3 0.83
EBT 66.0 80.0 97.0 18.3 0.034 81.7 0.79
ESDA 72.5 55.0 90.0 18.5 0.275 81.5 0.83
Proposed 75.5 78.0 93.0 16.8 0.270 83.2 0.85
  1. Data in bold are significant