A Study of the Robustness of KNN Classifiers Trained Using Soft Labels-Reference-Cited by-同舟云学术

A Study of the Robustness of KNN Classifiers Trained Using Soft Labels

Published:2006 Issue: Volume: Page:67-80
ISSN:0302-9743
Container-title:Artificial Neural Networks in Pattern Recognition
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Author:

El Gayar Neamat,Schwenker Friedhelm,Palm Günther

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/11829898_7

Reference24 articles.

1. El Gayar, N.F.: Fuzzy Neural Network Models for Unsupervised and Confidence-Based Learning. PhD thesis, University of Alexandria, Dept. of Comp. Sc. (1999)

2. Kuncheva, L.: Fuzzy classifier design. Physica-Verlag (2000)

3. Bezdek, J., Pal, N.: Two soft relatives of learning vector quantization. Neural Networks 8(5), 729–743 (1995)

4. Villmann, T., Hammer, B., Schleif, F.M., Geweniger, T.: Fuzzy labeled neural gas for fuzzy classification. In: Proceedings of WSOM 2005, pp. 283–290 (2005)

5. Pal, S., Mitra, S.: Multilayer perceptron, fuzzy sets and classification. IEEE Transactions on Neural Networks 3, 683–697 (1992)

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