Table 5 Classification results of the SVM 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 | 224 | 690 | 99 | 39 | 85.17% | 87.45% | 86.88% |
Pseudo-8494 | 207 | 8389 | 105 | 56 | 78.70% | 98.76% | 98.16% |
Human pre-miRNA | 211 | 1487 | 113 | 52 | 80.22% | 92.93% | 91.14% |