Solving Non-Uniqueness in Agglomerative Hierarchical Clustering Using Multidendrograms
Abstract 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...
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Gespeichert in:
| Autor*in: |
Fernández, Alberto [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2008 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media, LLC 2008 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of classification - Springer-Verlag, 1984, 25(2008), 1 vom: Juni, Seite 43-65 |
|---|---|
| Übergeordnetes Werk: |
volume:25 ; year:2008 ; number:1 ; month:06 ; pages:43-65 |
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| DOI / URN: |
10.1007/s00357-008-9004-x |
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OLC2062462824 |
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| 520 | |a Abstract 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 andWilliams’ formula which enables the implementation of the algorithm in a recursive way. | ||
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Solving Non-Uniqueness in Agglomerative Hierarchical Clustering Using Multidendrograms |
| abstract |
Abstract 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 andWilliams’ formula which enables the implementation of the algorithm in a recursive way. © Springer Science+Business Media, LLC 2008 |
| abstractGer |
Abstract 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 andWilliams’ formula which enables the implementation of the algorithm in a recursive way. © Springer Science+Business Media, LLC 2008 |
| abstract_unstemmed |
Abstract 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 andWilliams’ formula which enables the implementation of the algorithm in a recursive way. © Springer Science+Business Media, LLC 2008 |
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| title_short |
Solving Non-Uniqueness in Agglomerative Hierarchical Clustering Using Multidendrograms |
| url |
https://doi.org/10.1007/s00357-008-9004-x |
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| author2 |
Gómez, Sergio |
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Gómez, Sergio |
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10.1007/s00357-008-9004-x |
| up_date |
2024-07-03T15:09:32.377Z |
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