A Hausdorff Distance Between Hyper-Rectangles for Clustering Interval Data-Reference-Cited by-同舟云学术

A Hausdorff Distance Between Hyper-Rectangles for Clustering Interval Data

Published:2004 Issue: Volume: Page:333-339
ISSN:
Container-title:Classification, Clustering, and Data Mining Applications
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Author:

Chavent Marie

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-17103-1_32.pdf

Reference10 articles.

1. Bock, H.-H. (2001). “Clustering Algorithms and Kohonen Maps for Symbolic Data,” in ICNCB Proceedings, Springer: Heidelberg, pp. 203–215.

2. Bock, H.-H., and Diday, E. (2000). Analysis of Symbolic Data: Exploratory Methods for Extracting Statistical Information from Complex Data, Studies in Classification, Data Analysis, and Knowledge Organisation, Springer-Ver lag, Heidelberg.

3. Celeux, G., Diday, E., Govaert, G., Lechevallier, Y., and Ralambondrainy, H. (1989). Classification Automatique des Données. Dunod, Paris.

4. Chavent, M., and Lechevallier, Y. (2002). “Dynamical Clustering of Interval Data: Optimization of an Adequacy Criterion Based on Hausdorff Distance,” in Classification, Clustering, and Data Analysis, eds. K. Jajuga, A. Sokolowski, and H.-H. Bock, Berlin: Springer-Verlag, pp. 53–60.

5. Diday, E. (1988). “The Symbolic Approach in Clustering and Related Methods of Data Analysis: The Basic Choices,” in Classification and Related Methods of Data Analysis, ed. H.-H. Bock, Amsterdam: North Holland, pp. 673–684

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