JACIII Vol.16 No.7 pp. 807-813
doi: 10.20965/jaciii.2012.p0807


Agglomerative Hierarchical Clustering Without Reversals on Dendrograms Using Asymmetric Similarity Measures

Satoshi Takumi and Sadaaki Miyamoto

Department of Risk Engineering, School of Systems and Information Engineering, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan

November 29, 2011
September 25, 2012
November 20, 2012
agglomerative clustering, asymmetric similarity, asymmetric dendrogram

Algorithms of agglomerative hierarchical clustering using asymmetric similarity measures are studied. Two different measures between two clusters are proposed, one of which generalizes the average linkage for symmetric similarity measures. Asymmetric dendrogram representation is considered after foregoing studies. It is proved that the proposed linkage methods for asymmetric measures have no reversals in the dendrograms. Examples based on real data show how the methods work.

Cite this article as:
S. Takumi and S. Miyamoto, “Agglomerative Hierarchical Clustering Without Reversals on Dendrograms Using Asymmetric Similarity Measures,” J. Adv. Comput. Intell. Intell. Inform., Vol.16, No.7, pp. 807-813, 2012.
Data files:
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Last updated on Jan. 21, 2019