Dataset | Method | Accuracy | Sensitivity | Specificity | Precision | MCC | AUC |
---|---|---|---|---|---|---|---|
RPI2241 | IPMiner | 0.824 | 0.833 | 0.812 | 0.836 | 0.650 | 0.906 |
 | SDA-RF | 0.648 | 0.653 | 0.630 | 0.665 | 0.296 | 0.687 |
 | SDA-FT-RF | 0.783 | 0.890 | 0.645 | 0.920 | 0.592 | 0.898 |
 | RPISeq-RF | 0.646 | 0.652 | 0.630 | 0.663 | 0.293 | 0.690 |
 | lncPro | 0.654 | 0.659 | 0.640 | 0.669 | 0.310 | 0.722 |
RPI369 | IPMiner | 0.752 | 0.735 | 0.791 | 0.713 | 0.507 | 0.773 |
 | SDA-RF | 0.707 | 0.699 | 0.727 | 0.689 | 0.416 | 0.754 |
 | SDA-FT-RF | 0.693 | 0.664 | 0.784 | 0.602 | 0.396 | 0.728 |
 | RPISeq-RF | 0.704 | 0.705 | 0.702 | 0.707 | 0.409 | 0.767 |
 | lncPro | 0.704 | 0.708 | 0.696 | 0.713 | 0.409 | 0.740 |
RPI1807 | IPMiner | 0.986 | 0.982 | 0.993 | 0.978 | 0.972 | 0.998 |
 | SDA-RF | 0.972 | 0.970 | 0.981 | 0.962 | 0.944 | 0.995 |
 | SDA-FT-RF | 0.972 | 0.955 | 0.997 | 0.940 | 0.944 | 0.995 |
 | RPISeq-RF | 0.973 | 0.968 | 0.984 | 0.960 | 0.946 | 0.996 |
 | lncPro | 0.969 | 0.965 | 0.981 | 0.955 | 0.938 | 0.994 |