Exploitation of Contributions to Information Gain, from Learning Analysis to Architecture Synthesis

We introduce a new analysis tool able to test the learning distribution inside an MLP network. This tool is based on the exploitation of specific indicators which measure the contribution of any interconnection graph subset to the information gain evolution. We present an application of this method to an efficient architecture synthesis algorithm.