Figure 2 .

The leave-one-out cross-validation classification flowchart. MAD was employed to eliminate RSFC features with outlier values. On the training loop, the LOOCV split dataset into a training set and testing set. The training set was used for feature selection and transformation (the dash line), and to train the Siamese-KNN classifier (the dash-dotted line). Next, the built classifier was used to predict the label of the testing subject. After all loops, the average accuracy for all subjects was then calculated. Abbreviations: MAD, median absolute deviation; LOOCV, leave-one-out cross-validation; PCA, principal component analysis; KNN, K-nearest neighbor.