Table 37 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 | 1.64 | 0.23 | 6477.60 | 0.0000 |
RUS | 2 | 0.01 | 0.01 | 172.54 | 0.0000 |
Hyperparameters | 1 | 0.01 | 0.01 | 164.64 | 0.0000 |
FST | 4 | 0.00 | 0.00 | 33.30 | 0.0000 |
Residuals | 11985 | 0.43 | 0.00 | Â | Â |