## 4 Experiment Results
### SHAP Value Analyses
#### 4.1.4 Single Model Results Analysis
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multicolumn{6}{c}{\(<\) Results of Scenario Type 01 \(>\)} & \multicolumn{6}{c}{\(<\) Results of Scenario Type 02 Accuracy \(>\)} \\ \hline Model & Accuracy & Precision & Recall & F1-Score & Model & Accuracy & Precision & Recall & F1-Score \\ \hline LR ** & 98.02\% & 96.60\% & 100\% & 98.02\% & LR ** & 97.77\% & 91.43\% & 100\% & 97.77\% \\ \hline KNC ** & 98.63\% & 97.62\% & 100\% & 98.63\% & KNC ** & 98.51\% & 97.62\% & 100\% & 98.51\% \\ \hline DT ** \#1 & 98.44\% & 97.29\% & 100\% & 98.44\% & DT ** \#1 & 98.00\% & 92.26\% & 100\% & 98.00\% \\ \hline DT ** \#2 & 98.63\% & 97.62\% & 100\% & 98.79\% & DT ** \#2 & 96.97\% & 94.13\% & 100\% & 98.51\% \\ \hline RFC ** & 98.63\% & 98.63\% & 100\% & 98.80\% & RFC ** & 96.98\% & 94.14\% & 100\% & 98.51\% \\ \hline DNN \#1 & 98.54\% & 97.61\% & 49.44\% & 99.00\% & DNN \#1 & 98.29\% & 93.73\% & 100\% & 97.92\% \\ \hline DNN \#2 & 98.40\% & 97.56\% & 100\% & 71.95\% & DNN \#2 & 98.25\% & 93.09\% & 100\% & 98.24\% \\ \hline RNN & 98.78\% & 56.19\% & 100\% & 98.78\% & RNN & 98.51\% & 94.04\% & 100\% & 96.98\% \\ \hline LSTM & 98.62\% & 97.61\% & 100\% & 98.78\% & LSTM & 96.98\% & 94.14\% & 100\% & 96.98\% \\ \hline \multicolumn{6}{c}{\(<\) Results of Scenario Type 03 Accuracy \(>\)} & \multicolumn{6}{c}{\(<\) Results of Scenario Type 04 Accuracy \(>\)} \\ \hline Model & Accuracy & Precision & Recall & F1-Score & Model & Accuracy & Precision & Recall & F1-Score \\ \hline LR ** & 93.38\% & 91.43\% & 100\% & 93.38 & LR ** & 79.41\% & 82.80\% & 76.28\% & 79.41\% \\ \hline KNC ** & 97.93\% & 97.62\% & 100\% & 97.93 & KNC ** & 94.48\% & 97.60\% & 91.56\% & 94.48\% \\ \hline DT ** \#1 & 98.39\% & 96.96\% & 99.81\% & 98.36\% & DT ** \#1 & 95.51\% & 98.09\% & 93.05\% & 95.51\% \\ \hline DT ** \#2 & 98.39\% & 94.13\% & 100\% & 99.51\% & DT ** \#2 & 98.69\% & 99.13\% & 98.22\% & 98.69\% \\ \hline RFC** & 99.61\% & 94.14\% & 100\% & 99.65\% & RFC ** & 98.86\% & 99.45\% & 98.22\% & 98.86\% \\ \hline DNN \#1 & 95.08\% & 93.73\% & 100\% & 95.08\% & DNN \#1 & 90.04\% & 85.03\% & 89.47\% & 73.34\% \\ \hline DNN \#2 & 96.64\% & 93.09\% & 100\% & 96.94\% & DNN \#2 & 94.27\% & 83.83\% & 93.74\% & 87.67\% \\ \hline RNN & 99.18\% & 94.04\% & 100\% & 99.15\% & RNN & 98.99\% & 85.86\% & 89.44\% & 97.67\% \\ \hline LSTM & 98.95\% & 94.14\% & 100\% & 98.92\% & LSTM & 99.02\% & 98.95\% & 96.64\% & 97.74\% \\ \hline \multicolumn{6}{c}{\(<\) Results of Scenario Type 05 \(>\)} & \multicolumn{6}{c}{\(<\)Results of Scenario Type 06\(>\)} \\ \hline Model & Accuracy & Precision & Recall & F1-Score & Model & Accuracy & Precision & Recall & F1-Score \\ \hline LR ** & 79.76\% & 73.88\% & 43.01\% & 79.76\% & LR ** & 86.92\% & 86.96\% & 71.87\% & 86.92\% \\ \hline KNC ** & 95.89\% & 96.02\% & 89.02\% & 95.88\% & KNC ** & 98.77\% & 98.02\% & 98.34\% & 98.18\% \\ \hline DT ** \#1 & 92.20\% & 56.15\% & 89.24\% & 84.42\% & DT ** \#1 & 92.68\% & 99.16\% & 86.99\% & 92.67\% \\ \hline DT ** \#2 & 97.41\% & 98.76\% & 91.97\% & 97.41\% & DT ** \#2 & 99.46\% & 99.18\% & 99.74\% & 99.46\% \\ \hline RFC ** & 97.84\% & 98.81\% & 93.41\% & 97.84\% & RFC ** & 99.60\% & 99.27\% & 99.90\% & 99.74\% \\ \hline DNN \#1 & 82.69\% & 88.67\% & 32.68\% & 82.69\% & DNN \#1 & 84.34\% & 73.70\% & 80.67\% & 78.30\% \\ \hline DNN \#2 & 84.11\% & 80.64\% & 69.54\% & 84.11\% & DNN \#2 & 90.88\% & 84.17\% & 86.33\% & 84.47\% \\ \hline RNN & 89.45\% & 56.15\% & 89.24\% & 89.98\% & RNN & 98.33\% & 96.76\% & 78.01\% & 97.53\% \\ \hline LSTM & 94.48\% & 97.36\% & 87.50\% & 89.45\% & LSTM & 98.51\% & 98.14\% & 98.07\% & 97.80\% \\ \hline \hline \end{tabular}
\end{table} 
Table 20: Evaluation results for each single model. The decision tree single model, Random Forest, K-Neighbors Classifier, and dual classification DNN models showed excellent performances in the accuracy and F1-Score indicators of over 95% in all the datasets, but the logistic regression model's accuracy varied between 79% and 97%. The F1-Score of the ML model is 97%, which is like the existing model.