Belfield, S. J.; Cronin, M. T. D.; Enoch, S. J.; Firman, J. W. Guidance for Good Practice in the Application of Machine Learning in Development of Toxicological Quantitative Structure-Activity Relationships (QSARs). PLOS ONE, 2023, 18, e0282924.

Compound

	ID:	1817
	Name:	2-bromo-1-(naphthalen-2-yl)ethan-1-one
	Description:
	Labels:	Neutral
	CAS:	613-54-7
	InChi Code:	InChI=1/C12H9BrO/c13-8-12(14)11-6-5-9-3-1-2-4-10(9)7-11/h1-7H,8H2

pIGC50: 40-h Tetrahymena toxicity as log(1/IGC50) [log(L/mmol)] i

Value	Source or prediction
2.96	experimental value
2.56	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (Training set)
2.03	RF: QSAR model for Tetrahymena pyriformis growth inhibition using the RF algorithm (10-fold cross-validation)
2.95	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (Training set)
2.19	SVM: QSAR model for Tetrahymena pyriformis growth inhibition using the SVM algorithm (10-fold cross-validation)
1.79	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (Training set)
1.32	KNN: QSAR model for Tetrahymena pyriformis growth inhibition using the KNN algorithm (10-fold cross-validation)
2.92	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (Training set)
2.35	XGB: QSAR model for Tetrahymena pyriformis growth inhibition using the XGB algorithm (10-fold cross-validation)
2.81	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (Training set)
2.34	SNN: QSAR model for Tetrahymena pyriformis growth inhibition using the SNN algorithm (10-fold cross-validation)
3.05	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (Training set)
1.94	DNN: QSAR model for Tetrahymena pyriformis growth inhibition using the DNN algorithm (10-fold cross-validation)