Table 3.
Molecular descriptors and forward selection statistics for linear (MLR) and non-linear (SVM) QSAR dataset 2 (16 Compounds).
| Model | Descriptors | Variables | R2 | Max. Abs. Error | Mean Abs. Error | R2CV (N-Fold) |
|---|---|---|---|---|---|---|
|
Linear (MLR) |
H0m | 1 | 0.4827 | 1.1753 | 0.4315 | 0.2908 |
| H0m, C-025 | 2 | 0.7114 | 1.0899 | 0.3089 | 0.5508 | |
| H0m, C-025, nBnz | 3 | 0.8670 | 0.5661 | 0.2180 | 0.7736 | |
| H0m, C-025, nBnz, Mor17m | 4 | 0.9274 | 0.4868 | 0.1542 | 0.8547 | |
|
Non-linear (SVM) |
GGI9 | 1 | 0.6459 | 1.1049 | 0.3207 | 0.4738 |
| GGI9, R7v+ | 2 | 0.7902 | 0.7553 | 0.2370 | 0.6831 | |
| GGI9, R7v+, G(O..S) | 3 | 0.8970 | 0.7558 | 0.1135 | 0.7834 | |
| GGI9, R7v+, G(O..S), HATSe | 4 | 0.8803 | 0.7725 | 0.1255 | 0.8155 |
Statistical fitness derived from various statistical parameters of linear and non-linear QSAR models show that models were acceptable in the current form. R2 values indicate a strong confidence level even in bi-variable linear (R2=0.8634) and non-linear (R2=0.9747) QSAR models. R2CV values further confirm the stability of QSAR models