Comparison of various methods for validity evaluation of QSAR models

Shayanfar, Shadi; Shayanfar, Ali

doi:10.1186/s13065-022-00856-4

BMC Chemistry

Table 1 The numerical values of statistical parameters which need to calculate mentioned criteria for external validation for 44 developed QSAR models

From: Comparison of various methods for validity evaluation of QSAR models

No.	Number of compounds in training set	Number of compounds in test set	r² > 0.6	\(r_{0}^{2}\)(Eq. 3)	\({\text{r}}_{{0}}^{{^{\prime}2}}\)(Eq. 4)	\({\text{r}}_{{0}}^{{2}} = {\text{r}}_{{0}}^{{^{\prime}2}}\)(Eq. 5)	AEE ± SD Training set	AEE ± SD Test set	Training set range	Refs.
1	39	10	0.917	0.909	0.917	0.999	0.161 ± 0.114	0.221 ± 0.110	4.07	[23]
2	39	10	0.880	0.879	0.857	0.999	0.237 ± 0.234	0.318 ± 0.150	4.07	[23]
3	31	10	0.715	0.715	0.617	0.997	0.167 ± 0.171	0.266 ± 0.244	1.72	[24]
4	26	11	0.725	0.310	0.691	0.997	0.233 ± 0.167	0.354 ± 0.301	2.74	[25]
5	40	10	0.906	0.904	0.904	0.999	0.121 ± 0.091	0.206 ± 0.095	2.68	[26]
6	40	10	0.892	0.879	0.892	0.999	0.122 ± 0.087	0.195 ± 0.146	2.68	[26]
7	68	17	0.261	0.012	0.052	0.957	0.503 ± 0.435	1.165 ± 0.715	5.00	[27]
8	68	17	0.444	0.220	0.404	0.977	0.331 ± 0.674	0.435 ± 0.326	4.60	[27]
9	42	11	0.834	0.823	0.818	0.824	0.872 ± 0.678	1.630 ± 1.256	14.46	[28]
10	42	9	0.588	0.552	0.511	0.999	0.040 ± 0.035	0.169 ± 0.124	1.85	[29]
11	42	9	0.748	0.496	0.730	0.999	0.053 ± 0.043	0.133 ± 0.077	1.85	[29]
12	20	6	0.963	0.962	0.983	0.787	0.052 ± 0.043	0.035 ± 0.035	0.91	[30]
13	90	22	0.372	0.376	-0.292	0.950	0.432 ± 0.648	0.538 ± 0.647	6.95	[31]
14	68	17	0.382	0.136	0.309	0.975	0.364 ± 0.324	0.457 ± 0.356	4.90	[31]
15	27	5	0.088	− 2.263	− 1.129	0.995	0.074 ± 0.094	0.315 ± 0.135	0.40	[32]
16	27	7	0.818	− 1.721	0.563	0.993	0.412 ± 0.352	0.645 ± 0.489	3.76	[33]
17	27	7	0.763	− 4.030	0.462	0.992	0.359 ± 0.290	0.729 ± 0.511	3.76	[33]
18	89	19	0.932	0.932	0.928	0.998	0.187 ± 0.151	0.246 ± 0.204	3.95	[34]
19	89	19	0.821	0.813	0.811	0.995	0.255 ± 0.186	0.339 ± 0.368	3.95	[34]
20	66	16	0.703	0.514	0.914	0.984	0.444 ± 0.338	0.678 ± 0.411	5.45	[35]
21	66	16	0.671	0.475	0.700	0.983	0.384 ± 0.324	0.706 ± 0.461	5.45	[35]
22	66	16	0.914	0.908	0.670	0.995	0.288 ± 0.232	0.297 ± 0.307	5.45	[35]
23	32	11	0.790	0.006	0.683	0.993	0.120 ± 0.094	0.501 ± 0.249	4.68	[47]
24	40	12	0.876	0.875	0.845	0.999	0.090 ± 0.079	0.238 ± 0.088	3.35	[36]
25	40	12	0.866	0.814	0.861	0.999	0.079 ± 0.084	0.205 ± 0.140	3.35	[36]
26	63	16	0.999	0.999	0.999	1.000	0.011 ± 0.006	0.011 ± 0.006	3.76	[37]
27	40	4	0.960	0.693	0.863	1.000	0.155 ± 0.118	0.178 ± 0.105	4.25	[38]
28	22	7	0.995	0.995	0.995	1.000	0.043 ± 0.064	0.046 ± 0.032	2.56	[39]
29	22	7	0.971	0.971	0.971	0.999	0.101 ± 0.127	0.097 ± 0.097	2.56	[39]
30	50	18	0.914	0.796	0.879	1.000	0.041 ± 0.038	0.068 ± 0.134	2.35	[40]
31	50	18	0.994	0.993	0.992	1.000	0.031 ± 0.028	0.026 ± 0.028	2.35	[40]
32	52	12	0.815	0.686	0.801	0.983	0.340 ± 0.269	0.297 ± 0.261	3.32	[41]
33	58	6	0.964	0.949	0.958	1.000	0.051 ± 0.048	0.127 ± 0.117	2.90	[42]
34	58	6	0.966	0.965	0.962	1.000	0.066 ± 0.052	0.105 ± 0.076	2.90	[42]
35	47	16	0.899	0.878	0.898	0.999	0.195 ± 0.117	0.186 ± 0.153	2.16	[43]
36	52	20	0.533	0.367	0.511	0.995	0.566 ± 0.378	0.383 ± 0.314	4.28	[44]
37	52	20	0.659	0.533	0.657	0.997	0.554 ± 0.521	0.327 ± 0.230	4.28	[44]
38	52	20	0.744	0.714	0.733	0.998	0.355 ± 0.343	0.282 ± 0.213	4.28	[44]
39	52	20	0.815	0.785	0.814	0.998	0.290 ± 0.358	0.246 ± 0.181	4.28	[44]
40	31	10	0.658	0.475	0.658	0.995	0.097 ± 0.064	0.272 ± 0.202	2.17	[45]
41	68	8	0.898	0.865	0.935	0.999	0.125 ± 0.110	0.204 ± 0.151	4.03	[46]
42	68	8	0.855	0.702	0.828	0.998	0.199 ± 0.115	0.270 ± 0.148	4.03	[46]
43	53	18	0.806	0.678	0.795	0.996	0.122 ± 0.118	0.279 ± 0.203	3.78	[48]
44	53	18	0.676	0.109	0.640	0.993	0.329 ± 0.271	0.362 ± 0.276	3.78	[48]

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