Skip to main content

Table 1 Property prediction model performance

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