An investigation into pharmaceutically relevant mutagenicity data and the influence on Ames predictive potential

Table 6 Performance of PLS and random forest models on the aryl-amine sets.

		Set A, Training	Set A, Test	Set B, Training	Set B, Test
PLS with NitFormE	PC1	0.76 ± 0.02	0.63 ± 0.08	0.80 ± 0.02	0.78 ± 0.05
PLS with 9 descriptors	PC1	0.68 ± 0.03	0.66 ± 0.08	0.77 ± 0.02	0.76 ± 0.04
Random Forest With NitFormE			0.62 ± 0.01		0.855 ± 0.003
Random Forest With 9 descriptors			0.682 ± 0.008		0.844 ± 0.004
Nitrenium Formation Energy		0.72 ± 0.04	0.71 ± 0.09	0.78 ± 0.02	0.77 ± 0.05

The performance of statistical models for Set A and Set B, over 100 random samples of the data. For the random forest model, the performance is for the data when it was out-of-bag in the construction of the trees and for PLS, it is for a 30% test sample when the model is trained with the other 70%.

ISSN: 1758-2946