Fig. 2.

illustrates computational approaches used for treatment outcome prediction on the group level. In particular, (a) illustrates the LMM regression approach and is taken from [18]. (b) depicts an application of support vector classification for a hypothetical classification task in which a classifier has to learn the differences between voxel GM patterns belonging to very successful dieters and less successful dieters in the training stage. In the next step, the classification boundary estimated from the training data is used to predict the class of an unknown test person based on their GM pattern. (b) is derived from Weygandt et al. [172]. Finally, (c) shows a hypothetical structural equation model (in part derived from [169])