Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Breast Cancer Classification Applying Artificial Metaplasticity
Year:2009
Research Areas
  • Automatic,
  • Processing and signal analysis
Information
Abstract
In this paper we are apply Artificial Metaplasticity MLP (MMLPs) to Breast Cancer Classification. Artificial Metaplasticity is a novel ANN training algorithm that gives more relevance to less frequent training patterns and subtract relevance to the frequent ones during training phase, achieving a much more efficient training, while at least maintaining the Multilayer Perceptron performance. Wisconsin Breast Cancer Database (WBCD) was used to train and test MMLPs. WBCD is a well-used database in machine learning, neural networks and signal processing. Experimental results show that MMLPs reach better accuracy than any other recent results
International
Si
Congress
IWINAC 2009
960
Place
Santiago de Compostela
Reviewers
Si
ISBN/ISSN
978-3-642-02266-1
10.1007/978-3-642-02267-8_20
Start Date
22/06/2009
End Date
26/06/2009
From page
48
To page
54
Bioinspired Applications in Artificial and Natural Computation (IWINAC 039;09). LNCS 5602
Participants
  • Autor: Fulgencio S Buendía
  • Autor: Diego Andina De la Fuente (UPM)
  • Autor: Alexis Enrique Marcano Cedeño (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Automatización en Señal y Comunicaciones (GASC)
  • Departamento: Señales, Sistemas y Radiocomunicaciones
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