Table 8.

Overall performance of the final non-linear models for case study 4

Classification b	RF (without HPOc/QSAR-Co)d			RF (with HPO/QSAR-Co-X)			GB (with HPO/QSAR-Co-X)
	Str(tenfold CV)e	Tsf	Vdg	Str(tenfold CV)e	Tsf	Vd g	Str (tenfold CV)e	Tsf	Vdg
TP	994	431	341	969	433	343	996	443	346
TN	953	405	317	936	405	316	949	406	318
FP	46	17	10	63	17	11	50	16	9
FN	44	20	14	69	18	12	42	8	9
Sn (%)	95.76	95.57	96.06	93.35	95.97	96.64	95.95	96.21	97.46
Sp (%)	95.4	95.97	96.94	93.69	96.01	96.62	94.99	98.22	97.25
Acc (%)	95.58	91.52	96.48	93.52	95.99	96.63	95.48	97.25	97.36
MCCh	0.912	0.915	0.93	0.884	0.920	0.932	0.91	0.945	0.947

^aThe most significant results are highlighted in bold. QSAR-Co-X were generated using random state 1 in Module 2 of the toolkit

^bTP: True positive, TN: True negative, FP: False positive, FN: False negative, Sn: Sensitivity, Sp: Specificity, Acc: Accuracy

^cHPO: Hyperparameter optimisation

^dModel previously reported in [15]

^eSub-training set

^fTest set

^gValidation set

^hMatthews correlation coefficient