Table 12. Comparison of our study with state-of-the-art works.
| Algorithms | Study | Accuracy | AUC | MCC | Precision | Recall | F1 score |
|---|---|---|---|---|---|---|---|
| Support vector machine | This study | 1 | 1 | 1 | 1 | 1 | 1 |
| Pei et al. (2019) | 0.908 | 0.763 | NA | 0.903 | 0.908 | 0.905 | |
| Talaei-Khoei & Wilson (2018) | NA | 0.831 | 0.922 | NA | 0.683 | NA | |
| Kagawa et al. (2017) | NA | NA | NA | 0.8 | 0.909 | NA | |
| Neural network | This study | 0.788 | 0.986 | 0.566 | 0.910 | 0.620 | 0.684 |
| Talaei-Khoei & Wilson (2018) | NA | 0.663 | 0.007 | NA | 0.41 | NA | |
| Nilashi et al. (2017) | 0.923 | NA | NA | NA | NA | NA | |
| Esteban et al. (2017) | NA | NA | NA | 0.930 | 0.960 | 0.940 | |
| Random forest | This study | 1 | 1 | 1 | 1 | 1 | 1 |
| Alghamdi et al. (2017) | 0.840 | NA | NA | 0.844 | 0.994 | 0.913 |
Note:
AUC, area under receiver operating characteristic; MCC, Matthew correlation coefficient; NA, not available.