In addition to assessing classification accuracy, the performance of the classifiers was also evaluated using receiver operating characteristic (ROC) curves and corresponding areas under the curve (AUCs). The final correlation coefficient for SVR was statistically significant and corrected for multiple comparisons (permutation test, n = 2000). The predictive power of SVR was evaluated by calculating the squared prediction-outcome correlation (R2) and mean absolute error (MAE). The resulting ten P-values were adjusted for FWE P < 0.05.
