Table 12 Comparison of results for different classifiers in lncRNA-miRNA prediction.
From: Predicting noncoding RNA and disease associations using multigraph contrastive learning
 | Accuracy | Precision | Recall | F1-score | AUC |
---|---|---|---|---|---|
DT | 0.9137 | 0.8922 | 0.9421 | 0.9161 | 0.9486 |
LR | 0.7889 | 0.8064 | 0.7625 | 0.7834 | 0.9027 |
MLP | 0.8738 | 0.8753 | 0.8722 | 0.8729 | 0.9451 |
SVM | 0.8478 | 0.8169 | 0.8972 | 0.8549 | 0.9300 |
Adaboost | 0.9142 | 0.9061 | 0.9251 | 0.9250 | 0.9637 |
XGboost | 0.9286 | 0.9198 | 0.9391 | 0.9294 | 0.9687 |