Table 5.
Before Feature Selection | ||||||
---|---|---|---|---|---|---|
Parameter | Model | No. of Features | AUROC | Accuracy | Sensitivity | Specificity |
Vascular | S-IT SVM | 1 | 0.72 0.06 | 0.58 0.09 | 0.58 0.09 | 0.86 0.04 |
S-IT RF | 1 | 0.70 0.06 | 0.55 0.09 | 0.55 0.09 | 0.84 0.04 | |
S-IT xGB | 1 | 0.72 0.06 | 0.58 0.09 | 0.58 0.09 | 0.85 0.04 | |
MLS SVM | 42 | 0.67 0.06 | 0.51 0.09 | 0.51 0.09 | 0.83 0.04 | |
MLS RF | 42 | 0.72 0.06 | 0.60 0.09 | 0.60 0.09 | 0.85 0.04 | |
MLS xGB | 42 | 0.72 0.06 | 0.59 0.09 | 0.59 0.09 | 0.85 0.04 | |
Structural | RNFL SVM | 1 | 0.60 0.06 | 0.40 0.09 | 0.40 0.09 | 0.79 0.04 |
RNFL RF | 1 | 0.59 0.06 | 0.39 0.09 | 0.39 0.09 | 0.80 0.03 | |
RNFL xGB | 1 | 0.67 0.06 | 0.53 0.09 | 0.53 0.09 | 0.82 0.04 | |
After Feature Selection | ||||||
Vascular | MLS SVM | 21 | 0.74 0.06 | 0.60 0.09 | 0.60 0.09 | 0.87 0.04 |
MLS RF | 24 | 0.69 0.06 | 0.55 0.09 | 0.55 0.09 | 0.84 0.04 | |
MLS xGB | 39 | 0.76 0.06 | 0.64 0.08 | 0.64 0.08 | 0.87 0.04 |
The highest mean value per metric is highlighted in bold.