WiSARD is a weightless neural model which essentially uses look up tables to store the function computed by each neuron rather than storing it in weights of neuron connections. Although WiSARD was originally conceived as a pattern recognition device mainly focusing on image processing, in this work we show how it is possible to build a multi-class classifier method in Machine Learning (ML) domain based on WiSARD that shows equivalent performances to ML state-of-the-art methods.

The WiSARD classifier

De Gregorio M;Giordano M
2016

Abstract

WiSARD is a weightless neural model which essentially uses look up tables to store the function computed by each neuron rather than storing it in weights of neuron connections. Although WiSARD was originally conceived as a pattern recognition device mainly focusing on image processing, in this work we show how it is possible to build a multi-class classifier method in Machine Learning (ML) domain based on WiSARD that shows equivalent performances to ML state-of-the-art methods.
2016
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
Istituto di Scienze Applicate e Sistemi Intelligenti "Eduardo Caianiello" - ISASI
Inglese
24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
447
452
978-2-87587-027-8
http://www.scopus.com/record/display.url?eid=2-s2.0-84994165233&origin=inward
Sì, ma tipo non specificato
27/04/2016, 29/04/2016
Bruges (Belgium)
Weightless neural systems
machine learning
classification
2
none
De Gregorio M.; Giordano M.
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/322182
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