Table 3.
Comparative results of six different ML algorithms using classification accuracy ± standard deviation.
| A1 | A2 | A3 | A4 | A5 | Avg. | ||
|---|---|---|---|---|---|---|---|
| Scheme | Lin. | RBF | |||||
| Sp | 0.99 ± 0.00 | 0.96 ± 0.01 | 0.97 ± 0.00 | 0.81 ± 0.07 | 0.92 ± 0.01 | 0.95 ± 0.02 | 0.93 |
| St | 0.99 ± 0.00 | 0.92 ± 0.01 | 0.96 ± 0.01 | 0.75 ± 0.10 | 0.93 ± 0.01 | 0.92 ± 0.01 | 0.91 |
| Ind | 0.99 ± 0.00 | 0.94 ± 0.01 | 0.95 ± 0.01 | 0.92 ± 0.02 | 0.93 ± 0.01 | 0.94 ± 0.00 | 0.94 |
| Sp+St | 0.99 ± 0.00 | 0.97 ± 0.00 | 0.97 ± 0.01 | 0.83 ± 0.07 | 0.93 ± 0.01 | 0.95 ± 0.00 | 0.94 |
| Sp+Ind | 0.99 ± 0.00 | 0.96 ± 0.01 | 0.98 ± 0.00 | 0.77 ± 0.01 | 0.95 ± 0.01 | 0.96 ± 0.00 | 0.93 |
| St+Ind | 0.99 ± 0.00 | 0.95 ± 0.00 | 0.97 ± 0.00 | 0.77 ± 0.10 | 0.94 ± 0.01 | 0.97 ± 0.00 | 0.93 |
| Sp+St+Ind | 0.99 ± 0.00 | 0.97 ± 0.00 | 0.98 ± 0.00 | 0.87 ± 0.10 | 0.95 ± 0.01 | 0.96 ± 0.00 | 0.95 |
Note that A1, A2, A3, A4, and A5 denote RF, SVM with Linear kernel, SVM with RBF kernel, ANN, NB, and GLM algorithms, respectively. Significant values are in bold.