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Dissimilarity representations allow for building good classifiers
- Source :
-
Pattern Recognition Letters . Jun2002, Vol. 23 Issue 8, p943. 14p. - Publication Year :
- 2002
-
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]
- Subjects :
- *REPRESENTATIONS of graphs
*DENSITY functionals
Subjects
Details
- Language :
- English
- ISSN :
- 01678655
- Volume :
- 23
- Issue :
- 8
- Database :
- Academic Search Index
- Journal :
- Pattern Recognition Letters
- Publication Type :
- Academic Journal
- Accession number :
- 7772941