BACKPROPAGATION NEURAL NETS WITH ONE AND 2 HIDDEN LAYERS

The differences in classification and training performance of three and four layer (one and two hidden layer) fully interconnected feedforward neural nets are investigated. To obtain results which do not merely reflect performance on a particular data set, the networks are trained on various distributions, which are themselves drawn from a ''distribution of distributions.'' Experimental results indicate that four-layered networks are more prone to fall into bad local minima, but that three- and four-layered networks perform similarly in all other respects.