Fig. 4: Convolutional Neural Networks (CNNs) outperform classical methods.

Violin plots showing CNN and Support Vector Machine (SVM) performance across 20 repeats of the nested cross-validation scheme. Performance is presented in terms of individual class accuracies (severe and nonsevere accuracy), weighted accuracy (average across the two classes), F1 scores, precision, and recall. Violin plot colors correspond to different performance measures which are additionally separated by horizontal lines. Within each performance measure, the first or topmost violin shows the performance of a SVM combined with an ICA preprocessing step, the following violin plot shows the performance of a SVM combined with a PCA preprocessing step, the penultimate violin plot shows the performance of a SVM without dimensionality reduction as a preprocessing step, and the final violin plot depicts CNN performance as a baseline (i.e., from Fig. 2). See previous figure for information represented in each violin plot.