Table 3 Performance of the DRD2 activity model
From: Molecular de-novo design through deep reinforcement learning
| Set | Training | Validation | Test |
|---|---|---|---|
| Accuracy | 1.00 | 0.98 | 0.98 |
| ROC-AUC | 1.00 | 0.99 | 1.00 |
| Precision | 1.00 | 0.96 | 0.97 |
| Recall | 1.00 | 0.73 | 0.82 |
From: Molecular de-novo design through deep reinforcement learning
| Set | Training | Validation | Test |
|---|---|---|---|
| Accuracy | 1.00 | 0.98 | 0.98 |
| ROC-AUC | 1.00 | 0.99 | 1.00 |
| Precision | 1.00 | 0.96 | 0.97 |
| Recall | 1.00 | 0.73 | 0.82 |
