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MultiDendrograms: Variable-Group Agglomerative Hierarchical Clusterings

Information Retrieval 2015-03-20 v2 Statistics Theory Computational Physics Data Analysis, Statistics and Probability Computational Finance Computation Statistics Theory

Abstract

MultiDendrograms is a Java-written application that computes agglomerative hierarchical clusterings of data. Starting from a distances (or weights) matrix, MultiDendrograms is able to calculate its dendrograms using the most common agglomerative hierarchical clustering methods. The application implements a variable-group algorithm that solves the non-uniqueness problem found in the standard pair-group algorithm. This problem arises when two or more minimum distances between different clusters are equal during the agglomerative process, because then different output clusterings are possible depending on the criterion used to break ties between distances. MultiDendrograms solves this problem implementing a variable-group algorithm that groups more than two clusters at the same time when ties occur.

Keywords

Cite

@article{arxiv.1201.1623,
  title  = {MultiDendrograms: Variable-Group Agglomerative Hierarchical Clusterings},
  author = {Sergio Gomez and Justo Montiel and David Torres and Alberto Fernandez},
  journal= {arXiv preprint arXiv:1201.1623},
  year   = {2015}
}

Comments

Article upgraded to MultiDendrograms 3.0. Software available at http://deim.urv.cat/~sgomez/multidendrograms.php

R2 v1 2026-06-21T20:01:44.783Z