Fig. 1: Performance for multi-site classification using different algorithms and cross-validation schemes.

Boxplots summarize AUC scores obtained across CV-folds; dashed line represents chance-level performance and asterisks indicate scores significantly different from chance (Mann–Whitney-U statistic; p < 0.05 Bonferroni corrected (10 classifiers × 3 CV types), see Supplement for details). SVM Support Vector Machine, PCA Principal Component Analysis, RBF Radial Basis Function, LR Logistic Regression, GPC Gaussian Processes Classification, RFC Random Forest Classifier, XGB XGBoost, NN Neural Network.