A novel approach to the problem of non-uniqueness of the solution in hierarchical clustering

Isabella Cattinelli, Giorgio Valentini, Eraldo Paulesu, Nunzio Alberto Borghese

Research output: Contribution to journalArticlepeer-review

Abstract

The existence of multiple solutions in clustering, and in hierarchical clustering in particular, is often ignored in practical applications. However, this is a non-trivial problem, as different data orderings can result in different cluster sets that, in turns, may lead to different interpretations of the same data. The method presented here offers a solution to this issue. It is based on the definition of an equivalence relation over dendrograms that allows developing all and only the significantly different dendrograms for the same dataset, thus reducing the computational complexity to polynomial from the exponential obtained when all possible dendrograms are considered. Experimental results in the neuroimaging and bioinformatics domains show the effectiveness of the proposed method.

Original languageEnglish
Article number6497531
Pages (from-to)1166-1173
Number of pages8
JournalIEEE Transactions on Neural Networks and Learning Systems
Volume24
Issue number7
DOIs
Publication statusPublished - 2013

Keywords

  • Bioinformatics
  • dendrogram equivalence relation
  • hierarchical clustering (HC)
  • neuroimaging

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Software

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