Breast Cancer Classification Applying Artificial Metaplasticity

  • Alexis Marcano-Cedeño
  • Fulgencio S. Buendía-Buendía
  • Diego Andina
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5602)


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.


Breast Cancer Association Rule Hide Layer Neuron Synaptic Change Multilayer Perceptron Neural Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Alexis Marcano-Cedeño
    • 1
  • Fulgencio S. Buendía-Buendía
    • 1
  • Diego Andina
    • 1
  1. 1.Universidad Politécnica de MadridSpain

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