Table 6 Classification results of the random forest model using the 40 features with the highest F-scores.
From: ViralmiR: a support-vector-machine-based method for predicting viral microRNA precursors
Negative dataset | TP | TN | FP | FN | SN | SP | ACC |
|---|---|---|---|---|---|---|---|
Virus genome | 219 | 686 | 103 | 44 | 83.26% | 86.94% | 86.02% |
Pseudo-8494 | 201 | 8368 | 126 | 62 | 76.42% | 98.51% | 97.85% |
Human pre-miRNA | 208 | 1473 | 127 | 55 | 79.08% | 92.06% | 90.23% |