1. Dissimilarity representations allow for building good classifiers
- Author
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Pękalska, Elżbieta and Duin, Robert P.W.
- Subjects
- *
REPRESENTATIONS of graphs , *DENSITY functionals - Abstract
In this paper, a classification task on dissimilarity representations is considered. A traditional way to discriminate between objects represented by dissimilarities is the nearest neighbor method. It suffers, however, from a number of limitations, i.e., high computational complexity, a potential loss of accuracy when a small set of prototypes is used and sensitivity to noise. To overcome these shortcomings, we propose to use a normal density-based classifier constructed on the same representation. We show that such a classifier, based on a weighted combination of dissimilarities, can significantly improve the nearest neighbor rule with respect to the recognition accuracy and computational effort. [Copyright &y& Elsevier]
- Published
- 2002