Journal of Cheminformatics

Table 3 Predictive performance of the SVM models

From: Memory-assisted reinforcement learning for diverse molecular de novo design

Target	Set	Bal. ACC	ROC AUC	F1	MCC
HTR1A	Training	0.98	0.99	0.77	0.78
	Validation	0.96	0.99	0.75	0.75
	Test	0.96	0.99	0.75	0.75
DRD2	Training	0.99	0.99	0.77	0.79
	Validation	0.93	0.98	0.70	0.71
	Test	0.95	0.99	0.71	0.72

The SVM model was trained on the training set and the hyperparameters c, the choice of the kernel, and the class weight were optimized towards a high F1 score on the validation set. The test set was used to estimate the predictive performance of unknown compounds. “bal” stands for balanced

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ISSN: 1758-2946

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