From: Molecular optimization by capturing chemist’s intuition using deep neural networks
LogD | Solubility | HLM CLint | |
---|---|---|---|
Train size | 170,337 | 184,883 | 144,300 |
Train RMSE | 0.304 | 0.485 | 0.264 |
Train NRMSE | 0.041 | 0.079 | 0.083 |
Train \(R^2\) | 0.935 | 0.774 | 0.749 |
Test size | 18,927 | 20,543 | 16,034 |
Test RMSE | 0.395 | 0.602 | 0.350 |
Test NRMSE | 0.054 | 0.104 | 0.113 |
Test \(R^2\) | 0.892 | 0.658 | 0.557 |