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2018 | OriginalPaper | Chapter

Empirical Comparison of Distances for Agglomerative Hierarchical Clustering

Authors : Shusaku Tsumoto, Tomohiro Kimura, Haruko Iwata, Shoji Hirano

Published in: Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations

Publisher: Springer International Publishing

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Abstract

This paper proposes a method for empirical comparison of distances for agglomerative hierarchical clustering based on rough set-based approximation. When a set of target is given, a level of clustering tree where one branch includes all the targets can be traced with the number of elements included. The pair \((\#clusters of a level, \#elements of a cluster) \) can be viewed as indices-pair for a given clustering tree.

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Metadata
Title
Empirical Comparison of Distances for Agglomerative Hierarchical Clustering
Authors
Shusaku Tsumoto
Tomohiro Kimura
Haruko Iwata
Shoji Hirano
Copyright Year
2018
DOI
https://doi.org/10.1007/978-3-319-91476-3_45

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