Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloAn experimental evaluation of weightless neural networks for multi-class classification
Anno di pubblicazione2018
Autore/iDe Gregorio, Massimo; Giordano, Maurizio
Affiliazioni autoriCNR; CNR
Autori CNR e affiliazioni
  • inglese
AbstractWiSARD belongs to the class of weightless neural networks, and it is based on a neural model which uses lookup tables to store the function computed by each neuron rather than storing it in weights of neuron connections. WiSARD is characterised by a simple implementation and a fast learning phase due to one-way RAM access/lookup mechanism. WiSARD was originally conceived as a pattern recognition device mainly focusing on image processing. In this work we present a multi-class classification method in machine learning domain based on WiSARD, called WiSARD Classifier. The method uses the same binary encoding scheme to transform multivariable data in the domain of real numbers into binary patterns which are the input to WiSARD. The main contribution of this work is an extensive experimental evaluation of WiSARD's classification capability in comparison to methods from the state-of-the-art. For the purpose we conducted many experiments applying nine well known machine learning methods (including the WiSARD Classifier) to seventy classification problems. Cross-validation accuracies were collected and compared by means of a statistical analysis based on nonparametric tests (Friedman, Friedman Aligned Rank, and Quade test) to prove how the WiSARD Classifier is very close in performance to the best methods available in most popular machine learning libraries. (C) 2018 Elsevier B.V. All rights reserved.
Lingua abstractinglese
Altro abstract-
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Pagine da338
Pagine a354
Pagine totali17
RivistaApplied soft computing (Print)
Attiva dal 2001
Editore: Elsevier Science - [S.l.]
Paese di pubblicazione: Paesi Bassi
Lingua: inglese
ISSN: 1568-4946
Titolo chiave: Applied soft computing (Print)
Titolo proprio: Applied soft computing. (Print)
Numero volume della rivista72
Fascicolo della rivista-
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • ISI Web of Science (WOS) (Codice:000448813100024)
  • Scopus (Codice:2-s2.0-85052139837)
Parole chiaveWeightless neural network, WiSARD, Machine learning
Link (URL, URI)-
Titolo parallelo-
Scadenza embargo-
Data di accettazione-
Note/Altre informazioni-
Strutture CNR
  • ICAR — Istituto di calcolo e reti ad alte prestazioni
  • ISASI — Istituto di Scienze Applicate e Sistemi Intelligenti "Eduardo Caianiello"
Moduli/Attività/Sottoprogetti CNR
  • DIT.AD022.055.001 : Intelligenza Computazionale
Progetti Europei-
An experimental evaluation of weightless neural networks for multi-class classification (documento privato )
Descrizione: Reprint
Tipo documento: application/pdf