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Proceedings Paper

Clustering With The Relational C-Means Algorithms Using Different Measures Of Pairwise Distance
Author(s): Richard J. Hathaway; John W. Davenport; James C. Bezdek
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Paper Abstract

In this note we review the object and relational c-means algorithms, and the theory asserting their duality in case the relational data corresponds to an inner-product induced measure of distance between each pair of corresponding object data. Past numerical results are given here along with new extensions in order to study the effect of the choice of pairwise distance measure on the relational partition obtained.

Paper Details

Date Published: 22 August 1988
PDF: 10 pages
Proc. SPIE 0938, Digital and Optical Shape Representation and Pattern Recognition, (22 August 1988); doi: 10.1117/12.976609
Show Author Affiliations
Richard J. Hathaway, Georgia Southern College (United States)
John W. Davenport, Georgia Southern College (United States)
James C. Bezdek, Boeing Electronics (United States)

Published in SPIE Proceedings Vol. 0938:
Digital and Optical Shape Representation and Pattern Recognition
Richard D. Juday, Editor(s)

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