Table 4 Classification results of the random forest model.
From: ViralmiR: a support-vector-machine-based method for predicting viral microRNA precursors
Negative dataset | TP | TN | FP | FN | SN | SP | ACC |
|---|---|---|---|---|---|---|---|
Virus genome | 215 | 669 | 120 | 48 | 81.74% | 84.79% | 84.03% |
Pseudo-8494 | 198 | 8306 | 188 | 65 | 75.28% | 97.78% | 97.11% |
Human pre-miRNA | 203 | 1464 | 136 | 60 | 77.18% | 91.50% | 89.47% |