Table 2.
Melanoma detection performance using the augmented ISIC 2017 dataset. Performance is shown for seven classifiers and two feature types (conventional features (Conv) [36], and the best combination of conventional and unweighted graph features (Graph+Conv)). Performance metrics are the accuracy (AC), sensitivity (SN) and specificity (SP)
| SVM | SVM | SVM | KNN | MLP | RF | ||
|---|---|---|---|---|---|---|---|
| (RBF) | (Sigmoid) | (Poly) | |||||
| AC | 84.12 | 70.09 | 82.71 | 78.94 | 85.70 | 89.30 | |
| Conv | AUC | 96.44 | 55.30 | 89.85 | 91.67 | 97.38 | 96.81 |
| SN | 100.0 | 99.38 | 100.0 | 98.14 | 80.95 | 88.00 | |
| SP | 71.75 | 58.96 | 75.81 | 63.01 | 74.20 | 89.70 | |
| AC | 88.41 | 74.05 | 94.29 | 83.91 | 89.45 | 97.95 | |
| Graph | AUC | 97.90 | 79.84 | 79.84 | 94.41 | 98.37 | 99.89 |
| +Conv | SP | 99.31 | 84.43 | 93.77 | 98.27 | 98.62 | 99.31 |
| SN | 78.20 | 65.05 | 95.16 | 70.24 | 81.66 | 97.23 |