Figure 1.

Linear two‐class SVM nested 10‐fold cross‐validation scheme. Illustration of a SVM example for classification of the SCZ sample based on the EmoSF network. As input variables (DATA) (= features) served the subjects' RSFCs of all edges of every network. The inner loop was performed in a 10‐fold manner with 10 repetitions conducted as parameter setting optimization on a training sample. The outer loop was performed in a 10‐fold manner with 25 repetitions conducted as classification accuracy testing on an unseen test set. Classification performance measures are computed based on the confusion matrix. Acc., accuracy; Sens., sensitivity; Spec., specificity; AUC, area under the ROC curve and d' (see “Materials and Methods” section for explanation). [Color figure can be viewed at http://wileyonlinelibrary.com]