Intelligent classification through exclusion/inclusion relationship

The paper introduces an exclusion/inclusion fuzzy classification (EFC) neural network. The network is based on our general fuzzy min-max algorithm (GFMM [13]) and it allows for two distinct types of hyperboxes to be created: inclusion hyperboxes, that corresponds directly to those considered in GFMM, and exclusion hyperboxes that represent contentious areas of the patter space. The subtraction of the exclusion hyperboxes from the inclusion hyperboxes, implemented by EFC, provides for a more efficient coverage of complex topologies of data clusters