Table 1.
Statistical evaluations of ML predictions for the 9 individual predictors and for four possible definitions of the Vox Machinarum classifier over our internal validation set of 36 compounds
| Method | RMSE | AAE | R 2 | Err < 0.5 | Err < 1.0 |
|---|---|---|---|---|---|
| Extra Trees | 0.766 | 0.582 | 0.789 | 18 (50%) | 30 (83%) |
| Random Forest | 0.766 | 0.607 | 0.792 | 17 (47%) | 29 (81%) |
| Bagging | 0.827 | 0.659 | 0.737 | 16 (44%) | 26 (72%) |
| MLP | 1.017 | 0.804 | 0.597 | 16 (44%) | 24 (67%) |
| kNN man unw k4 | 1.034 | 0.792 | 0.579 | 18 (50%) | 26 (72%) |
| kNN eu exp k6 | 1.054 | 0.818 | 0.573 | 14 (39%) | 25 (69%) |
| kNN man exp k4 | 1.062 | 0.791 | 0.548 | 18 (50%) | 25 (69%) |
| RVM | 1.121 | 0.820 | 0.509 | 16 (44%) | 25 (69%) |
| kNN eu unw k6 | 1.122 | 0.906 | 0.528 | 12 (33%) | 22 (61%) |
| Vox Machinarum (3) | 0.760 | 0.602 | 0.797 | 17 (47%) | 29 (81%) |
| Vox Machinarum (5) | 0.787 | 0.627 | 0.771 | 17 (47%) | 29 (81%) |
| Vox Machinarum (7) | 0.891 | 0.695 | 0.695 | 16 (44%) | 29 (81%) |
| Vox Machinarum (9) | 0.944 | 0.728 | 0.660 | 16 (44%) | 28 (78%) |