Table 4 Results of individual extracted set of features using PH2 dataset
Name | Features | Performance measures | |||||||
|---|---|---|---|---|---|---|---|---|---|
Classification Method | Harlick | HOG | Color | Sensitivity (%) | Precision (%) | Specificity (%) | FNR (%) | FPR | Accuracy (%) |
Decision tree | ✓ | 67.53 | 67.50 | 70.05 | 31.50 | 0.16 | 68.5 | ||
✓ | 71.67 | 72.1 | 85.0 | 23.0 | 0.11 | 77.0 | |||
✓ | 87.93 | 86.93 | 86.9 | 12.5 | 0.06 | 87.5 | |||
Quadratic discriminant analysis | ✓ | 70.0 | 68.43 | 70.0 | 30.0 | 0.14 | 70.0 | ||
✓ | 74.60 | 75.83 | 88.15 | 20.0 | 0.09 | 80.0 | |||
✓ | 84.6 | 81.9 | 80.65 | 17.0 | 0.08 | 83.0 | |||
Quadratic SVM | ✓ | 68.33 | 70.27 | 76.25 | 28.5 | 0.14 | 71.5 | ||
✓ | 82.5 | 83.37 | 92.7 | 13.5 | 0.06 | 86.5 | |||
✓ | 93.77 | 93.33 | 94.44 | 6.0 | 0.03 | 94.0 | |||
Logistic regression | ✓ | 63.36 | 64.06 | 70.05 | 34.0 | 0.17 | 66.0 | ||
✓ | 86.27 | 85.83 | 91.9 | 11.5 | 0.09 | 88.5 | |||
✓ | 89.2 | 90.43 | 92.55 | 9.5 | 0.04 | 90.5 | |||
Naive bayes | ✓ | 62.9 | 62.9 | 66.85 | 35.5 | 0.18 | 64.5 | ||
✓ | 81.25 | 81.93 | 90.65 | 15.0 | 0.07 | 85.0 | |||
✓ | 87.93 | 87.63 | 90.65 | 11.0 | 0.06 | 89.0 | |||
Weighted KNN | ✓ | 66.67 | 67.5 | 72.5 | 31.0 | 0.16 | 69.0 | ||
✓ | 81.67 | 83.27 | 92.5 | 14.0 | 0.06 | 86.0 | |||
✓ | 90.87 | 90.83 | 92.55 | 8.5 | 0.03 | 91.5 | |||
Ensemble boosted tree | ✓ | 68.33 | 67.77 | 68.75 | 31.5 | 0.16 | 68.5 | ||
✓ | 80.67 | 82.57 | 91.3 | 15.0 | 0.07 | 85.0 | |||
✓ | 88.37 | 89.47 | 91.3 | 10.5 | 0.04 | 89.5 | |||
Ensemble subspace discriminant | ✓ | 68.76 | 68.4 | 71.9 | 30.0 | 0.15 | 70.0 | ||
✓ | 87.1 | 87.03 | 91.9 | 11.0 | 0.05 | 89.0 | |||
✓ | 92.9 | 94.7 | 96.9 | 5.5 | 0.03 | 94.1 | |||
Cubic KNN | ✓ | 65.43 | 66.4 | 71.9 | 32.0 | 0.16 | 68.0 | ||
✓ | 80.4 | 80.8 | 89.4 | 16.0 | 0.07 | 84.0 | |||
✓ | 90.3 | 89.83 | 91.7 | 9.5 | 0.04 | 90.5 | |||
Proposed | ✓ | 69.6 | 72.23 | 75.65 | 28.0 | 0.14 | 72.0 | ||
✓ | 86.27 | 87.37 | 94.4 | 10.5 | 0.02 | 89.5 | |||
✓ | 94.6 | 93.97 | 94.4 | 5.5 | 0.02 | 94.5 | |||