five bins, with four of these used at any one time as a training set and the remaining bin used as a test set. Edge connectivity selection (based on the correlation test) in each of the training sets was performed separately in order to avoid biasing the results. Thus, each of the four datasets led to cross-validated estimates of the classification accuracy (percentage of subjects correctly classified). The four cross-validated estimates were averaged to arrive at a final unbiased estimate of the classification accuracy. Results of supervised clustering based on the most significant edges that defined the nearest centroid predictor of group membership were displayed in a hierarchical cluster tree map.
