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On the generalization ability of prototype-based classifiers with local relevance determination (2005)  (Make Corrections)  
Barbara Hammer, et al.



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Abstract: We extend a recent variant of the prototype-based classifier learning vector quantization to a scheme which locally adapts relevance terms during learning. We derive explicit dimensionality-independent large-margin generalization bounds for this classifier and show that the method can be seen as margin maximizer. (Update)

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BibTeX entry:   (Update)

@misc{ hammer-generalization,
  author = "Barbara Hammer and et al.",
  title = "On the generalization ability of prototype-based classifiers with local
    relevance determination",
  url = "citeseer.ist.psu.edu/article/hammer05generalization.html" }
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