22 August 1988 Clustering With The Relational C-Means Algorithms Using Different Measures Of Pairwise Distance
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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.
© (1988) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Richard J. Hathaway, John W. Davenport, James C. Bezdek, "Clustering With The Relational C-Means Algorithms Using Different Measures Of Pairwise Distance", Proc. SPIE 0938, Digital and Optical Shape Representation and Pattern Recognition, (22 August 1988); doi: 10.1117/12.976609; https://doi.org/10.1117/12.976609
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