55 research outputs found
Solving non-uniqueness in agglomerative hierarchical clustering using multidendrograms
In agglomerative hierarchical clustering, pair-group methods suffer from a
problem of non-uniqueness when two or more distances between different clusters
coincide during the amalgamation process. The traditional approach for solving
this drawback has been to take any arbitrary criterion in order to break ties
between distances, which results in different hierarchical classifications
depending on the criterion followed. In this article we propose a
variable-group algorithm that consists in grouping more than two clusters at
the same time when ties occur. We give a tree representation for the results of
the algorithm, which we call a multidendrogram, as well as a generalization of
the Lance and Williams' formula which enables the implementation of the
algorithm in a recursive way.Comment: Free Software for Agglomerative Hierarchical Clustering using
Multidendrograms available at
http://deim.urv.cat/~sgomez/multidendrograms.ph
Morphological phenotypic dispersion of garlic cultivars by cluster analysis and multidimensional scaling
The analysis of aquatic vegetation on the Atherton Tableland, north-east Queensland, Australia
An analysis of the vegetation pattern in a semi-arid Eucalyptus populnea woodland in north-west New South Wales
Susceptibility of winter and summer crops to root and crown infection by Bipolaris sorokiniana
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