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Classification with Reject Option Using the Self-Organizing Map

  • Ricardo Sousa
  • Ajalmar R. da Rocha Neto
  • Jaime S. Cardoso
  • Guilherme A. Barreto
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8681)

Abstract

Reject option is a technique used to improve classifier’s reliability in decision support systems. It consists on withholding the automatic classification of an item, if the decision is considered not sufficiently reliable. The rejected item is then handled by a different classifier or by a human expert. The vast majority of the works on this issue have been concerned with implementing a reject option by endowing a supervised learning scheme (e.g., Multilayer Perceptron, Learning Vector Quantization or Support Vector Machines) with a reject mechanism. In this paper we introduce variants of the Self-Organizing Map (SOM), originally an unsupervised learning scheme, to act as supervised classifiers with reject option, and compare their performances with that of the MLP classifier.

Keywords

Self-Organizing Maps Reject Option Robust Classification Prototype-based Classifiers Neuron Labeling 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ricardo Sousa
    • 1
  • Ajalmar R. da Rocha Neto
    • 3
  • Jaime S. Cardoso
    • 4
  • Guilherme A. Barreto
    • 2
  1. 1.INEB - Instituto de Engenharia BiomédicaUniversidade PortoPortugal
  2. 2.Departamento Engenharia de TeleinformáticaUniversidade Federal do Ceará (UFC)Brazil
  3. 3.Departamento de TelemáticaInstituto Federal do Ceará (IFCE)Brazil
  4. 4.INESC Porto, FEUPUniversidade PortoPortugal

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