Figure 4.

Schematic overview of a double cross-validation procedure. The samples are split into a training and test set to evaluate the prediction accuracy in the outer cross-validation (CV) loop. The training set is subsequently split into a training and validation set to optimize the parameter specific for a classifier in the inner cross-validation loop.