Discriminant analysis via support vectors

Neurocomputing, pp. 1669-1675, 2010.

Cited by: 22|Bibtex|Views8|DOI:https://doi.org/10.1016/j.neucom.2009.09.021
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Other Links: dblp.uni-trier.de|dl.acm.org|academic.microsoft.com|www.sciencedirect.com

Abstract:

In this paper, we show how support vector machine (SVM) can be employed as a powerful tool for k-nearest neighbor (kNN) classifier. A novel multi-class dimensionality reduction approach, discriminant analysis via support vectors (SVDA), is proposed. First, the SVM is employed to compute an optimal direction to discriminant each two classe...More

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