Table 1 Cross-validation performance comparison of different MultiLoc architectures trained using the BaCelLo and the Höglund datasets
Dataset | Method | Animals | Fungi | Plants | |||
|---|---|---|---|---|---|---|---|
| Â | Â | AVG | ACC | AVG | ACC | AVG | ACC |
BaCelLo | Â | Â | Â | Â | Â | Â | Â |
|  | MultiLoc | 77.3 (± 2.9) | 75.7 (± 3.1) | 78.4 (± 2.7) | 71.0 (± 2.6) | 71.4 (± 6.8) | 67.8 (± 3.8) |
|  | + PhyloLoc | 80.1 (± 2.4) | 78.2 (± 2.9) | 80.0 (± 2.5) | 73.6 (± 0.9) | 78.6 (± 3.6) | 77.4 (± 1.9) |
|  | + GOLoc | 84.0 (± 1.7) | 82.8 (± 2.0) | 81.1 (± 0.5) | 75.5 (± 1.1) | 80.9 (± 4.4) | 77.6 (± 3.5) |
|  | MultiLoc2-LowRes | 86.1 (± 1.4) | 84.0 (± 1.7) | 82.8 (± 2.2) | 77.9 (± 0.5) | 81.9 (± 4.1) | 80.2 (± 3.5) |
Höglund |  |  |  |  |  |  |  |
|  | MultiLoc | 78.6 (± 1.2) | 76.4 (± 1.2) | 78.0 (± 1.3) | 76.6 (± 1.2) | 78.0 (± 1.8) | 76.4 (± 1.7) |
|  | + PhyloLoc | 84.6 (± 0.7) | 84.0 (± 0.6) | 84.7 (± 1.4) | 84.4 (± 0.9) | 86.5 (± 1.5) | 84.3 (± 0.7) |
|  | + GOLoc | 87.3 (± 1.8) | 86.7 (± 1.0) | 87.1 (± 0.9) | 86.9 (± 0.8) | 86.9 (± 1.4) | 86.3 (± 1.1) |
|  | MultiLoc2-HighRes | 89.3 (± 1.4) | 88.6 (± 1.0) | 89.2 (± 1.1) | 88.9 (± 1.2) | 89.4 (± 0.8) | 88.7 (± 0.9) |