A novel neuralnet-based method of constructing optimized prototypes for nearest-neighbor classiÿers is proposed. Based on an e ective classiÿcation oriented error function containing class classiÿcation and class separation components, the corresponding prototype and feature weight update rules are
Boosted discriminant projections for nearest neighbor classification
✍ Scribed by David Masip; Jordi Vitrià
- Publisher
- Elsevier Science
- Year
- 2006
- Tongue
- English
- Weight
- 388 KB
- Volume
- 39
- Category
- Article
- ISSN
- 0031-3203
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