Table 38 ANOVA for classifier, RUS, hperparameters and FST as factors of performance in terms of AUPRC
From: IoT information theft prediction using ensemble feature selection
| Â | Df | Sum Sq | Mean Sq | F value | Pr(>F) |
|---|---|---|---|---|---|
Classifier | 7 | 9.21 | 1.32 | 7851.99 | 0.0000 |
RUS | 2 | 0.07 | 0.03 | 203.36 | 0.0000 |
Hyperparameters | 1 | 0.00 | 0.00 | 0.06 | 0.8137 |
FST | 4 | 0.08 | 0.02 | 126.09 | 0.0000 |
Residuals | 11985 | 2.01 | 0.00 | Â | Â |