Skip to main content

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]