Prototype Selection for Nearest Neighbor Classification: Taxonomy and Empirical Study

@article{Garca2012PrototypeSF,
  title={Prototype Selection for Nearest Neighbor Classification: Taxonomy and Empirical Study},
  author={Salvador Garc{\'i}a and Joaqu{\'i}n Derrac and Jos{\'e} Ram{\'o}n Cano and Francisco Herrera},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2012},
  volume={34},
  pages={417-435}
}
The nearest neighbor classifier is one of the most used and well-known techniques for performing recognition tasks. It has also demonstrated itself to be one of the most useful algorithms in data mining in spite of its simplicity. However, the nearest neighbor classifier suffers from several drawbacks such as high storage requirements, low efficiency in classification response, and low noise tolerance. These weaknesses have been the subject of study for many researchers and many solutions have… CONTINUE READING
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UCI Machine Learning Repository,

  • A. Asuncion, D. Newman
  • http://www.ics.uci.edu/mlearn/MLRepository.html,
  • 2007
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, and N . Garcı́a - Pedrajas , “ Democratic Instance Selection : A Linear Complexity Instance Selection Algorithm Based on Classifier Ensemble Concepts

  • G. Folino
  • Artificial Intelligence
  • 2010

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