Enhancing prototype reduction schemes with recursion: a method applicable for "large" data sets

@article{Kim2004EnhancingPR,
  title={Enhancing prototype reduction schemes with recursion: a method applicable for "large" data sets},
  author={Sang-Woon Kim and B. John Oommen},
  journal={IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)},
  year={2004},
  volume={34},
  pages={1384-1397}
}
Most of the prototype reduction schemes (PRS), which have been reported in the literature, process the data in its entirety to yield a subset of prototypes that are useful in nearest-neighbor-like classification. Foremost among these are the prototypes for nearest neighbor classifiers, the vector quantization technique, and the support vector machines. These methods suffer from a major disadvantage, namely, that of the excessive computational burden encountered by processing all the data. In… CONTINUE READING

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