Table 3.

Performance of single classification models for the training set (5-fold cross-validation result) and the test set (validation result using external test set) using different combinations of molecular properties.

No.	Model	Descriptors	5-fold cross-validation result				Validation result using external test set
			SE	SP	PPV	MCC	SE	SP	PPV	MCC
1	RF-a1	32	0.682	0.970	0.912	0.750	0.675	0.975	0.915	0.718
2	RF-b1	53	0.621	0.973	0.903	0.750	0.650	0.981	0.915	0.716
3	RF-c1	79	0.667	0.992	0.927	0.823	0.690	0.980	0.922	0.742
4	K-NN-a1	32	0.682	0.905	0.861	0.710	0.695	0.926	0.880	0.622
5	K-NN-b1	53	0.621	0.936	0.873	0.710	0.599	0.931	0.865	0.557
6	K-NN-c1	79	0.636	0.936	0.876	0.760	0.609	0.931	0.867	0.565
7	Tree-a1	32	0.621	0.943	0.879	0.680	0.635	0.942	0.881	0.609
8	Tree-b1	53	0.667	0.939	0.885	0.566	0.624	0.914	0.856	0.545
9	Tree-c1	79	0.682	0.947	0.894	0.780	0.711	0.943	0.897	0.670
10	AB-a1	32	0.682	0.920	0.873	0.659	0.731	0.900	0.867	0.603
11	AB-b1	53	0.667	0.936	0.882	0.741	0.695	0.902	0.860	0.578
12	AB-c1	79	0.621	0.928	0.867	0.824	0.741	0.941	0.901	0.687
13	NB-a1	32	0.766	0.795	0.790	0.483	0.758	0.746	0.748	0.421
14	NB-b1	53	0.777	0.904	0.879	0.644	0.682	0.894	0.852	0.555
15	NB-c1	79	0.761	0.908	0.879	0.640	0.712	0.905	0.867	0.598
16	RF-a2	26	0.805	0.994	0.956	0.860	0.655	0.991	0.924	0.710
17	RF-b2	50	0.839	0.994	0.963	0.882	0.690	0.983	0.924	0.675
18	RF-c2	65	0.747	0.997	0.947	0.830	0.724	1.000	0.945	0.761
19	K-NN-a2	26	0.793	0.960	0.926	0.766	0.724	0.957	0.910	0.574
20	K-NN-b2	50	0.747	0.945	0.906	0.702	0.724	0.957	0.910	0.585
21	K-NN-c2	65	0.782	0.951	0.917	0.739	0.793	0.957	0.924	0.597
22	Tree-a2	26	0.759	0.971	0.929	0.769	0.655	0.966	0.903	0.601
23	Tree-b2	50	0.805	0.937	0.910	0.726	0.448	0.983	0.876	0.629
24	Tree-c2	65	0.782	0.963	0.926	0.765	0.793	0.966	0.931	0.656
25	AB-a2	26	0.805	0.937	0.910	0.726	0.655	0.957	0.897	0.602
26	AB-b2	50	0.828	0.931	0.910	0.732	0.793	0.948	0.917	0.621
27	AB-c2	65	0.851	0.951	0.931	0.788	0.828	0.974	0.945	0.570
28	NB-a2	26	0.839	0.951	0.929	0.780	0.724	0.871	0.841	0.551
29	NB-b2	50	0.816	0.966	0.936	0.796	0.621	0.914	0.855	0.542
30	NB-c2	65	0.885	0.943	0.931	0.795	0.712	0.905	0.867	0.598

1-15: neuroprotective models against hypoxia-induced neurotoxicity (NIN models).

16-30: neuroprotective models against H₂O₂-induced neurotoxicity (NHN models).

a: models built by DS_2D descriptors.

b: models built by MOE_2D descriptors.

c: models built by DS_MOE 2D descriptors.