From: IoT information theft prediction using ensemble feature selection
Experiment name | Mean | SD | Mean | SD |
---|---|---|---|---|
AUC | AUC | AUPRC | AUPRC | |
CatBoost Tuned RUS 1:9 | 0.99281 | 0.00986 | 0.99292 | 0.01192 |
CatBoost Tuned RUS 1:3 | 0.98816 | 0.01388 | 0.98791 | 0.01652 |
CatBoost Tuned RUS 1:1 | 0.98728 | 0.01193 | 0.98444 | 0.01864 |
DT Tuned RUS 1:9 | 0.96722 | 0.03625 | 0.91543 | 0.07238 |
DT Tuned RUS 1:3 | 0.96993 | 0.03208 | 0.84267 | 0.08491 |
DT Tuned RUS 1:1 | 0.97706 | 0.01870 | 0.74923 | 0.08163 |
Light GBM Tuned RUS 1:9 | 0.98769 | 0.01770 | 0.98951 | 0.01959 |
Light GBM Tuned RUS 1:3 | 0.98960 | 0.01336 | 0.95978 | 0.08703 |
Light GBM Tuned RUS 1:1 | 0.98446 | 0.01508 | 0.91785 | 0.09834 |
LR Tuned RUS 1:9 | 0.95866 | 0.03334 | 0.90807 | 0.10925 |
LR Tuned RUS 1:3 | 0.96372 | 0.03201 | 0.81231 | 0.15087 |
LR Tuned RUS 1:1 | 0.96302 | 0.02723 | 0.67686 | 0.15659 |
MLP Tuned RUS 1:9 | 0.87040 | 0.11157 | 0.93840 | 0.07158 |
MLP Tuned RUS 1:3 | 0.95885 | 0.03652 | 0.85402 | 0.14352 |
MLP Tuned RUS 1:1 | 0.96377 | 0.02815 | 0.72101 | 0.15642 |
NB Tuned RUS 1:9 | 0.97481 | 0.02199 | 0.81701 | 0.05655 |
NB Tuned RUS 1:3 | 0.97188 | 0.02087 | 0.70621 | 0.06589 |
NB Tuned RUS 1:1 | 0.96574 | 0.02068 | 0.64355 | 0.06437 |
RF Tuned RUS 1:9 | 0.98592 | 0.01871 | 0.98808 | 0.01699 |
RF Tuned RUS 1:3 | 0.98663 | 0.01519 | 0.98461 | 0.01831 |
RF Tuned RUS 1:1 | 0.98708 | 0.01384 | 0.97930 | 0.02606 |
XGBoost Tuned RUS 1:9 | 0.98292 | 0.02143 | 0.98610 | 0.02217 |
XGBoost Tuned RUS 1:3 | 0.98713 | 0.01487 | 0.97596 | 0.03204 |
XGBoost Tuned RUS 1:1 | 0.98634 | 0.01371 | 0.93328 | 0.08744 |