Table III.
Cross Validation and Test Set Performance, and Parameter Values of the Selected Models
| Cross validation | Test set | Selected parameters | ||||||
|---|---|---|---|---|---|---|---|---|
| Correlation, median | Correlation, MAD | Correlation | AUC | Number of features | Gamma | Cost | Epsilon | |
| Tm1 | 0.376 | 0.193 | 0.267 | 0.738 | 100 | 0.25 | 1 | 0.01 |
| Tm2 | 0.36 | 0.209 | 0.0741 | 0.786 | 45 | 0.0156 | 0.5 | 0.001 |
| Tm3 | 0.562 | 0.144 | 0.211 | 0.725 | 45 | 0.0625 | 4 | 0.01 |
| T1% | 0.471 | 0.13 | 0.0938 | 0.306 | 100 | 0.0625 | 1 | 0.001 |
| pH50 | 0.676 | 0.226 | 0.639 | 0.762 | 20 | 0.125 | 4 | 0.01 |
The cross-validation performance is given by the Pearson correlation coefficient between the predicted and actual values of the stability measures. Models yielding a high median and a low median absolute deviation (MAD) correlation coefficient are favored in the model selection. Performance on the test set is measured by the correlation of the predicted and actual stability measures, as well as the AUC (area under the receiver operating characteristic (ROC) curve) found by dichotomizing the stability measures into the two classes above and below the training set median.