Table 1.
Results on the SM T miRNA datasets.
| Method | AUC | AUPR |
|---|---|---|
| RLSMDA | 0.7715 ± 0.027 | 0.0321 ± 0.004 |
| HGIMDA | 0.7040 ± 0.025 | 0.0402 ± 0.006 |
| NCPMDA | 0.7760 ± 0.012 | 0.0578 ± 0.006 |
| PBMDA | 0.8194 ± 0.032 | 0.2106 ± 0.017 |
| RKNNMDA | 0.5678 ± 0.016 | 0.1581 ± 0.038 |
| DeepMDA | 0.9126* ± 0.004 | 0.2297* ± 0.040 |
| SAE + ADA | 0.8996 ± 0.010 | 0.1859 ± 0.026 |
| RAW + DNN | 0.9102 ± 0.007 | 0.1991 ± 0.028 |
The AUC and AUPR scores are listed above. The * indicates the highest AUC/AUPR score. Generally, the three deep learning models performed better than other five models.