Table 1 Comparison of AUC values of different miRNA-disease association prediction models
From: An improved random forest-based computational model for predicting novel miRNA-disease associations
No. | Algorithm | AUC value | ||
|---|---|---|---|---|
Global LOOCV | Local LOOCV | 5-fold CV | ||
1 | HGIMDA | 0.8781 | 0.8077 | – |
2 | MCMDA | 0.8749 | 0.7718 | 0.8767 |
3 | MaxFlow | 0.8624 | 0.7774 | 0.8579 |
4 | RLSMDA | 0.8426 | 0.6953 | 0.8569 |
5 | HDMP | 0.8366 | 0.7702 | 0.8432 |
6 | WBSMDA | 0.8030 | 0.8031 | 0.8185 |
7 | MIDP | – | 0.8196 | – |
8 | MiRAI | – | 0.6299 | – |
9 | RWRMDA | – | 0.7891 | – |
10 | RFMDA | 0.8891 | 0.8323 | 0.8818 |
11 | KBMF-MDI | – | – | 0.8815 |
12 | LPLNS | – | – | 0.9127 |
13 | IRFMDA-878 | – | – | 0.7713 |
14 | IRFMDA-100 | 0.9398 | 0.8728 | 0.9363 |