We introduce the Generalized Discrimination Value (GDV) that measures, in a non-invasive manner, how well different data classes separate each given layer of an artificial neural network. It turns out that, at end training period, GDV L attains highly reproducible value, irrespective initialization network’s connection weights. In case multi-layer perceptrons trained with error backpropagation,...