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Table 19 Classification results for the data exfiltration dataset with sampling and tuned hyperparameters experiments; mean and standard deviations of AUC and AUPRC, (10 iterations of 5-fold cross-validation)

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