## 6 RANs Applicability and Observations
\begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline
**Data** & **Algo** & **Precision (\%)** & **Recall (\%)** & **F1-Score (\%)** & **Accuracy (\%)** & **Data** & **Algo** & **Precision (\%)** & **Recall (\%)** & **F1-Score (\%)** & **Accuracy (\%)** \\ \hline \multirow{6}{*}{**RBM+**} & RRM+ & 43.45\(\pm\)44.07 & 53.50 \(\pm\) 38.23 & 45.46 \(\pm\) 43.36 & 53.50 \(\pm\) 38.23 & \multirow{6}{*}{**Data**} & RRM+ & 93.60 \(\pm\) 2.69 & 93.51 \(\pm\) 2.77 & 93.46 \(\pm\) 2.86 & 93.51 \(\pm\) 2.77 \\ \cline{3-10}  & KNN & 98.63 \(\pm\) 3.97 & 98.34 \(\pm\) 4.84 & 98.07 \(\pm\) 5.65 & 98.34 \(\pm\) 4.84 & \multirow{6}{*}{**Data**} & KNN & 99.80 \(\pm\) 0.59 & 99.79 \(\pm\) 0.62 & 99.78 \(\pm\) 0.63 & 99.79 \(\pm\) 0.62 \\ \cline{3-10}  & LR & 98.99 \(\pm\) 1.94 & 98.28 \(\pm\) 3.38 & 98.14 \(\pm\) 3.71 & 98.28 \(\pm\) 3.38 & \multirow{6}{*}{**Data**} & LR & 99.89 \(\pm\) 0.07 & 99.89 \(\pm\) 0.07 & 99.89 \(\pm\) 0.07 \\ \cline{3-10}  & MLP & 98.54 \(\pm\) 2.19 & 98.23 \(\pm\) 2.71 & 97.83 \(\pm\) 3.34 & 98.23 \(\pm\) 2.71 & \multirow{6}{*}{**Data**} & MLP & 98.67 \(\pm\) 0.94 & 98.65 \(\pm\) 0.96 & 98.64 \(\pm\) 0.96 & 99.89 \(\pm\) 0.07 \\ \cline{3-10}  & RAN & 99.98 \(\pm\) 0.06 & 99.97 \(\pm\) 0.06 & 99.89 \(\pm\) 0.06 & 99.97 \(\pm\) 0.06 & \multirow{6}{*}{**Data**} & RAN & 93.17 \(\pm\) 0.36 & 92.97 \(\pm\) 0.36 & 92.87 \(\pm\) 0.42 & 92.97 \(\pm\) 0.36 \\ \cline{3-10}  & SGD & 99.91 \(\pm\) 1.84 & 98.68 \(\pm\) 2.46 & 98.68 \(\pm\) 2.81 & 98.84 \(\pm\) 2.46 & \multirow{2}{*}{**SGD**} & 99.87 \(\pm\) 0.13 & 99.85 \(\pm\) 0.18 & 99.83 \(\pm\) 0.20 & 99.85 \(\pm\) 0.18 \\ \cline{3-10}  & RBM+ & 95.27 \(\pm\) 3.62 & 96.34 \(\pm\) 4.60 & 96.15 \(\pm\) 5.16 & 95.34 \(\pm\) 4.60 & \multirow{2}{*}{**RBM+**} & 97.64 \(\pm\) 41.25 & 57.63 \(\pm\) 21.98 & 97.40 \(\pm\) 14.59 & 75.63 \(\pm\) 12.98 \\ \cline{3-10}  & KNN & 99.46 \(\pm\) 0.88 & 99.44 \(\pm\) 0.93 & 99.43 \(\pm\) 0.94 & 99.44 \(\pm\) 0.93 & \multirow{6}{*}{**Data**} & KNN & 95.48 \(\pm\) 0.16 & 95.46 \(\pm\) 0.17 & 95.46 \(\pm\) 0.17 & 95.46 \(\pm\) 0.17 \\ \cline{3-10}  & LR & 99.16 \(\pm\) 0.17 & 99.14 \(\pm\) 0.17 & 99.15 \(\pm\) 0.17 & 99.14 \(\pm\) 0.17 & \multirow{6}{*}{**Data**} & LR & 95.06 \(\pm\) 0.38 & 95.04 \(\pm\) 0.39 & 95.04 \(\pm\) 0.39 \\ \cline{3-10}  & MLP & 98.96 \(\pm\) 0.76 & 98.95 \(\pm\) 0.76 & 98.95 \(\pm\) 0.76 & 98.95 \(\pm\) 0.76 & \multirow{6}{*}{**Data**} & MLP & 98.02 \(\pm\) 1.32 & 98.00 \(\pm\) 1.34 & 97.99 \(\pm\) 1.34 & 98.00 \(\pm\) 1.34 \\ \cline{3-10}  & RAN & 95.18 \(\pm\) 0.25 & 96.15 \(\pm\) 0.24 & 96.11 \(\pm\) 0.25 & 95.15 \(\pm\) 0.24 & \multirow{6}{*}{**Data**} & RAN & 80.67 \(\pm\) 1.37 & 79.58 \(\pm\) 1.05 & 79.66 \(\pm\) 1.13 & 79.58 \(\pm\) 1.05 \\ \cline{3-10}  & SGD & 99.88 \(\pm\) 0.16 & 99.88 \(\pm\) 0.16 & 99.18 \(\pm\) 0.16 & 99.88 \(\pm\) 0.16 & \multirow{6}{*}{**Data**} & SGD & 99.77 \(\pm\) 0.39 & 99.75 \(\pm\) 0.40 & 99.75 \(\pm\) 0.40 \\ \cline{3-10}  & RBM+ & 82.58 \(\pm\) 10.29 & 84.19 \(\pm\) 4.90 & 80.61 \(\pm\) 8.42 & 84.19 \(\pm\) 4.50 & \multirow{6}{*}{**Data**} & RBM+ & 84.85 \(\pm\) 16.54 & 85.18 \(\pm\) 14.98 & 82.42 \(\pm\) 20.30 & 85.18 \(\pm\) 14.98 \\ \cline{3-10}  & KNN & 94.08 \(\pm\) 12.12 & 95.97 \(\pm\) 7.32 & 94.82 \(\pm\) 10.59 & 95.97 \(\pm\) 7.32 & \multirow{6}{*}{**Data**} & KNN & 99.65 \(\pm\) 0.88 & 99.64 \(\pm\) 0.89 & 99.64 \(\pm\) 0.89 & 99.64 \(\pm\) 0.89 \\ \cline{3-10}  & LR & 99.52 \(\pm\) 0.18 & 99.49 \(\pm\) 0.18 & 99.49 \(\pm\) 0.18 & 99.49 \(\pm\) 0.18 & \multirow{6}{*}{**Data**} & LR & 99.41 \(\pm\) 0.30 & 99.40 \(\pm\) 0.30 & 99.40 \(\pm\) 0.30 & 99.40 \(\pm\) 0.30 \\ \cline{3-10}  & MLP & 93.78 \(\pm\) 1.4