Table 6 Maximum AUPRC by classifier for the information theft attack type; mean and standard deviations of AUPRC, (10 iterations of 5-fold cross-validation)
From: IoT information theft prediction using ensemble feature selection
Experiment name | Mean | SD |
|---|---|---|
AUPRC | AUPRC | |
LR Tuned RUS 1:3 5 Agree | 0.99872 | 0.00082 |
CatBoost Tuned 7 Agree | 0.99986 | 0.00019 |
DT Tuned 6 Agree | 0.99733 | 0.00169 |
Light GBM Tuned 7 Agree | 0.99956 | 0.00058 |
RF RUS 1:3 6 Agree | 0.99976 | 0.00042 |
MLP Tuned 7 Agree | 0.99908 | 0.00108 |
NB Tuned RUS 1:1 7 Agree | 0.97858 | 0.00625 |
XGBoost RUS 1:3 7 Agree | 0.99964 | 0.00050 |