Koniocortex-like network unsupervised learning surpasses supervised results on WBCD breast cancer database

Abstract

Koniocortex-Like Network is a novel category of Bio-Inspired Neural Networks whose architecture and properties are inspired in the biological koniocortex, the ?rst layer of the cortex that receives information from the thalamus. In the Koniocortex-Like Network competition and pattern classi?cation emerges naturally due to the interplay of inhibitory interneurons, metaplasticity and intrinsic plasticity. Recently proposed, it has shown a big potential for complex tasks with unsupervised learning. Now for the ?rst time, its competitive results are proved in a relevant standard real application that is the objective of state-ofthe-art research: the diagnosis of breast cancer data from the Wisconsin Breast Cancer Database