Table 22 ANOVA for classifier, RUS, hyperparameters and FST as factors of performance in terms of AUC
From: IoT information theft prediction using ensemble feature selection
| Â | Df | Sum Sq | Mean Sq | F value | Pr(>F) |
|---|---|---|---|---|---|
Classifier | 7 | 137.67 | 19.67 | 3564.07 | 0.0000 |
RUS | 3 | 4.05 | 1.35 | 244.86 | 0.0000 |
Hyperparameters | 1 | 0.95 | 0.95 | 171.29 | 0.0000 |
FST | 4 | 0.48 | 0.12 | 21.65 | 0.0000 |
Residuals | 15984 | 88.20 | 0.01 | Â | Â |