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

Fombellida Vetas, Juan, Andina de la Fuente, Diego ORCID: https://orcid.org/0000-0001-7036-2646 and Ropero-peláez, Francisco (2017). Koniocortex-like network unsupervised learning surpasses supervised results on WBCD breast cancer database. "Lecture Notes in Computer Science", v. 10338 (n. II); pp. 32-41. ISSN 0302-9743. https://doi.org/10.1007/978-3-319-59773-7_4.

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Title: Koniocortex-like network unsupervised learning surpasses supervised results on WBCD breast cancer database
Author/s:
Item Type: Article
Título de Revista/Publicación: Lecture Notes in Computer Science
Date: 2017
ISSN: 0302-9743
Volume: 10338
Subjects:
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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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

More information

Item ID: 50146
DC Identifier: https://oa.upm.es/50146/
OAI Identifier: oai:oa.upm.es:50146
DOI: 10.1007/978-3-319-59773-7_4
Official URL: https://link.springer.com/chapter/10.1007/978-3-31...
Deposited by: Memoria Investigacion
Deposited on: 12 Apr 2018 11:10
Last Modified: 28 Feb 2023 18:58
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