Table 2.

Statistical results of individual classification models and the two consensus models on the training set of 1667 chemicals. True Positives (TP) indicates the number of correctly classified positive chemicals, False Negatives (FN) indicates the number of misclassified positive chemicals, True Negative (TN) is the number of correctly classified positive chemicals, False positive (FP) refers to the misclassified experimentally negative chemicals. False rate is the fraction of incorrect predictions. Statistical parameters are the same as reported in Table 1.

	SVM	ANN	DT	SARpy1	SARpy2	Consensus I	Consensus II
TP	128	174	167	154	154	106	165
FN	68	22	31	44	44	11	32
FP	9	111	281	59	141	7	52
TN	1436	1334	1188	1410	1328	1113	1418
Total	1641	1641	1667	1667	1667	1237	1667
accuracy	0.95	0.92	0.81	0.94	0.89	0.99	0.95
specificity	0.99	0.92	0.81	0.96	0.90	0.99	0.96
sensitivity	0.65	0.89	0.84	0.78	0.78	0.91	0.84
MCC	0.76	0.69	0.48	0.71	0.58	0.91	0.77
BA	0.82	0.91	0.83	0.87	0.84	0.95	0.90
False rate	0.05	0.08	0.19	0.06	0.11	0.01	0.05
Youden	0.65	0.81	0.65	0.74	0.68	0.90	0.80