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Predictive accuracy as a function of the number of brain regions/clusters included in the classification process. Small number of regions is insufficient, whereas more than 30 regions result in insufficient training of the classifier, as we had 30 samples; this is the well-known “curse of dimensionality” in machine learning, and indicates that more extensive image databases might ultimately improve classification accuracy.
