Fig 12. Classification accuracies generated by multi-class classifiers on grey matter VBM using the one-vs-one approach.

All algorithms were used (except the regularized discriminant function analysis, which did not report reliable class probabilites). Overall accuracies are plotted together with accuracies for the three groups separately. Green line: mean accuracy for the 10 test samples; blue lines: approximate 95% confidence intervals for the mean accuracy; red line: highest and lowest accuracy values. ridge: Ridge regression, lasso: Lasso regression, elastic: Elastic net regularization, L0-norm: L0-norm regularization, SVC: Support vector classifier, GPC: Gaussian process classifier, RF: Random forest.