## 6 Experimental Setup
### Experimental Runs of the Hybrid Methods  
We applied two hybrid methods SMOTEEN and SMOTETomek, to train and evaluate the two AMiDS models. As a result, the hybrid method sub-experiment consisted of two experimental runs for each model. In the first experimental run, we applied the SMOTEEN method to the PCA- and oSVM-based AMiDS. We denote the experiments as ER-SMTEN\({}_{p}\) and ER-SMTEN\({}_{O}\), respectively. Similarly, we applied the SMOTETomek method to design two experimental runs. We named the runs using the ER-SMTEK\({}_{P}\) and ER-SMTEK\({}_{O}\) notations to distinguish the PCA-based AMiDS experiment from the oSVM-based AMiDS experiment. We applied the methods after normalizing and encoding the PiB dataset, as was also performed for the oversampling categories of the methods. After applying the sampling methods, the resulting PiB data included 2992 samples for the PCA-based methods, with normal and anomalous examples being equally distributed (1496 each). However, for the oSVM-based methods, the resulting PiB data included 2393 samples with normal and anomalous examples being almost equally distributed (1193 normal and 1200 anomalous for ER-SMTEK\({}_{O}\), and 1206 normal and 1187 anomalous for ER-SMTEK\({}_{O}\)). Tables 16-21 show the evaluation results for the two AMiDS models for the training and testing phases. Figure 9 shows the ROC curves and AUC values. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Method** & **A** & **P** & **R** & **F** & **AUC** & \begin{tabular}{c} **Training** \\ **Time (s)** \\ \end{tabular} & \
\begin{tabular}{c} **Inference** \\ **Time (s)** \\ \end{tabular} &
\begin{tabular}{c} **No. of** \\ **Examples** \\ \end{tabular} \\ \hline ER-SMTEN\({}_{p}\) & 0.77 & 0.84 & 0.77 & 0.76 & 0.77 & 1.9796 &... & 2992 \\ ER-SMTEK\({}_{p}\) & 0.77 & 0.84 & 0.77 & 0.76 & 0.77 & 1.7714 &... & 2992 \\ ER-SMTEN\({}_{O}\) & 0.62 & 0.62 & 0.62 & 0.62 & 0.62 & 0.536 &... & 2393 \\ ER-SMTEK\({}_{O}\) & 0.76 & 0.76 & 0.76 & 0.76 & 0.476 &... & 2393 \\ \hline \hline \end{tabular}
\end{table} 
Table 16: Trained PCA-based and oSVM-based AMiDS evaluation results for the hybrid methods based on the weighted average. Figure 8: Receiver operating characteristic (ROC) curves for the trained and scored oSVM-based AMiDS using oversampling methods based on the five experimental runs, respectively: (**a**) ER-KMS, (**b**) ER-LRS, (**c**) ER-ROS, (**d**) ER-SMT, and (**e**) ER-SVMSMT. Summary of the AUC values based on the experimental runs according to the applied methods is shown in (**f**). \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Method** & **A** & **P** & **R** & **F** & **AUC** & \begin{tabular}{c} **Training** \\ **Time (s)** \\ \end{tabular} & \
\begin{tabular}{c} **Inference** \\ **Time (s)** \\ \end{tabular} &
\begin{tabular}{c} **No. of** \\ **Examples** \\ \end{tabular} \\ \hline ER-SMTEN\({}_{p}\) &... & 1.0 & 0.54 & 0.70 &... &... &... & 1496 \\ ER-SMTEK\({}_{p}\) &... & 1.0 & 0.54 & 0.70 &... &... &... & 1496 \\ ER-SMTEN\({}_{\rm O}\) &... & 0.61 & 0.65 & 0.63 &... &... &... & 1193 \\ ER-SMTEK\({}_{\rm O}\) &... & 0.78 & 0.74 & 0.76 &... &... &... & 1206 \\ \hline \hline \end{tabular}
\end{table} 
Table 17: Trained PCA-based and oSVM-based AMiDS evaluation results for the hybrid methods based on the normal case. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Method** & **A** & **P** & **R** & **F** & **AUC** & \begin{tabular}{c} **Training** \\ **Time (s)** \\ \end{tabular} & \
\begin{tabular}{c} **Inference** \\ **Time (s)** \\ \end{tabular} &
\begin{tabular}{c} **No. of** \\ **Examples** \\ \end{tabular} \\ \hline ER-SMTEN\({}_{p}\) &... & 0.97 & 1.0 & 0.99 &... &... &... & 378 \\ ER-SMTEK\({}_{p}\) &... & 0.97 & 1.0 & 0.99 &... &... &... & 378 \\ ER-SMTEN\({}_{\rm O}\) &... & 0.93 & 0.60 & 0.73 &... &... &... & 378 \\ ER-SMTEK\({}_{\rm O}\) &... & 0.96 & 0.82 & 0.88 &... &... &... & 378 \\ \hline \hline \end{tabular}
\end{table}