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Min and Max Hierarchical Clustering using Asymmetric Similarity Measures

Published online by Cambridge University Press:  01 January 2025

Lawrence Hubert
Lawrence Hubert*
Affiliation:
The University of Wisconsin
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Abstract

The min and the max hierarchical clustering methods discussed by Johnson are extended to include the use of asymmetric similarity values. The first part of the paper presents the basic min and max procedures but in the context of graph theory; this description is then generalized to directed graphs as a way of introducing the less restrictive characterization of the original clustering techniques.

Type
Original Paper
Information
Psychometrika , Volume 38 , Issue 1 , March 1973 , pp. 63 - 72
Copyright
Copyright © 1973 The Psychometric Society

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References

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