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Koniocortex-Like Network Unsupervised Learning Surpasses Supervised Results on WBCD Breast Cancer Database

  • J. FombellidaEmail author
  • F. J. Ropero-Peláez
  • D. Andina
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10338)

Abstract

Koniocortex-Like Network is a novel category of Bio-Inspired Neural Networks whose architecture and properties are inspired in the biological koniocortex, the first layer of the cortex that receives information from the thalamus. In the Koniocortex-Like Network competition and pattern classification 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 first time, its competitive results are proved in a relevant standard real application that is the objective of state-of-the-art research: the diagnosis of breast cancer data from the Wisconsin Breast Cancer Database.

Keywords

Metaplasticity Koniocortex Plasticity KLN WBCD Feature extraction Competition 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Group for Automation in Signals and CommunicationsUniversidad Politécnica de MadridMadridSpain
  2. 2.Center of Mathematics, Computation and CognitionUniversidade Federal do ABCSanto AndréBrazil

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