Experimental study on prototype optimisation algorithms for prototype-based classification in vector spaces

@article{Lozano2006ExperimentalSO,
  title={Experimental study on prototype optimisation algorithms for prototype-based classification in vector spaces},
  author={M. Lozano and Jos{\'e} Mart{\'i}nez Sotoca and Jos{\'e} Salvador S{\'a}nchez and Filiberto Pla and Elzbieta Pekalska and Robert P. W. Duin},
  journal={Pattern Recognition},
  year={2006},
  volume={39},
  pages={1827-1838}
}
Prototype-based classification relies on the distances between the examples to be classified and carefully chosen prototypes. A small set of prototypes is of interest to keep the computational complexity low, while maintaining high classification accuracy. An experimental study of some old and new prototype optimisation techniques is presented, in which the prototypes are either selected or generated from the given data. These condensing techniques are evaluated on real data, represented in… CONTINUE READING
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LVQ_PAK: the learning vector quantization program package

  • T. Kohonen, J. Hynninen, J. Kangas, J. Laarksonen, K. Torkkola
  • 1838 M. Lozano et al. / Pattern Recognition 39
  • 2006
Highly Influential
4 Excerpts

PR-tools, a Matlab toolbox for pattern recognition, 2004 〈http://www.prtools.org

  • R.P.W. Duin, P. Juszczak, D. de Ridder, P. Paclík, E. PeRkalska, D.M.J. Tax
  • 2004
Highly Influential
3 Excerpts

Classifying spectral data using relational representation

  • P. Paclík, R.P.W. Duin
  • Spectral Imaging Workshop, Graz, Austria
  • 2003
1 Excerpt

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