Advances, Systems and Applications
Table 1 Performance of RNA-RBP interactions prediction
From: RNA-RBP interactions recognition using multi-label learning and feature attention allocation
|  | Model | Weighted-AUC↑ | Weighted-F1↑ | Exact Match Rate↑ | One Error↓ |
|---|---|---|---|---|---|
Single-view Model | \({X}_{o}^{1}\)(CNN) | 0.8843 | 0.6489 | 0.2923 | 0.3922 |
\({X}_{o}^{2}\)(CNN) | 0.8864 | 0.6667 | 0.3179 | 0.3633 | |
\({X}_{o}^{3}\)(CNN) | 0.9129 | 0.6901 | 0.2983 | 0.3131 | |
Double-view Model | \({X}_{o}^{1}+{X}_{o}^{2}\)(CNN+MMFA) | 0.8968 | 0.6672 | 0.3057 | 0.3389 |
\({X}_{o}^{1}+{X}_{o}^{3}\)(CNN+MMFA) | 0.9147 | 0.6993 | 0.3605 | 0.3016 | |
\({X}_{o}^{2}+{X}_{o}^{3}\)(CNN+MMFA) | 0.9167 | 0.6967 | 0.3662 | 0.2923 | |
Triple-view Model | \({X}_{o}^{1}+{X}_{o}^{2}+{X}_{o}^{3}\)(CNN+MMFA) | 0.9195 | 0.7104 | 0.3738 | 0.2803 |