TABLE 3.
Model | TP | FP | TN | FN | Accuracy | Sensitivity | Specificity | Precision | F1 |
---|---|---|---|---|---|---|---|---|---|
Xlnc1DCNN | 20,895 | 1,204 | 14,087 | 821 | 94.53 | 96.22 | 92.13 | 94.55 | 95.38 |
CPC2 | 21,023 | 6,457 | 8,834 | 693 | 80.68 | 96.81 | 57.77 | 76.50 | 85.47 |
CNIT | 21,307 | 3,580 | 11,711 | 409 | 89.22 | 98.12 | 76.59 | 85.61 | 91.44 |
PLEK | 20,704 | 6,665 | 8,626 | 1,012 | 79.26 | 95.34 | 56.41 | 75.65 | 84.36 |
CPAT | 20,646 | 2,597 | 12,694 | 1,070 | 90.09 | 95.07 | 83.02 | 88.83 | 91.84 |
FEELNC | 20,023 | 1,182 | 14,109 | 1,693 | 92.23 | 92.20 | 92.27 | 94.43 | 93.30 |
RNASAMBA | 20,998 | 1,795 | 13,496 | 718 | 93.21 | 96.69 | 88.26 | 92.12 | 94.35 |
lncRNA_Mdeep | 20,813 | 1,799 | 13,492 | 903 | 92.70 | 95.84 | 88.23 | 92.04 | 93.90 |
LncADeep | 20,232 | 1,113 | 14,178 | 1,484 | 92.98 | 93.17 | 92.72 | 94.79 | 93.97 |
The bold values indicate the highest value within each column.