Table 6 Performance evaluation for ML classifiers
Technique(s) | Parameter | MLP-NN | SVM | RF |
|---|---|---|---|---|
Without data modeling (Only eight features) | Accuracy (%) | 75.32 | 76.62 | 73.37 |
Precision (%) | 74.81 | 76.41 | 72.84 | |
Recall (%) | 75.33 | 76.66 | 73.42 | |
F-Measure (%) | 75.0 | 75.36 | 72.91 | |
ROC Area | 0.784 | 0.705 | 0.786 | |
With data modeling (enhanced features) | Accuracy (%) | 79.87 | 80.52 | 82.82 |
Precision (%) | 79.37 | 80.0 | 81.59 | |
Recall (%) | 79.99 | 80.55 | 81.88 | |
F-Measure (%) | 79.41 | 79.97 | 81.65 | |
ROC Area | 0.845 | 0.783 | 0.855 |