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    A New Flexible Dendrogram Seriation Algorithm for Data Visualisation


    Earle, Denise and Hurley, Catherine B. (2011) A New Flexible Dendrogram Seriation Algorithm for Data Visualisation. In: Bulletin of the International Statistical Institute Proceedings of the 58th World Statistics Congress 2011, Dublin. International Statistical Institute, pp. 3284-3293. ISBN 978-90-73592-33-9

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    Abstract

    Seriation is a data analytic tool for obtaining a permutation of a set of objects with the goal of revealing structural information within the set of objects. Seriating variables, cases or categories generally improves visualisations of statistical data, for example, by revealing hidden patterns in data or by making large datasets easier to understand. In this paper we present a new algorithm for seriation based on dendrograms. Dendrogram seriation algorithms rearrange the nodes in a dendrogram in order to obtain a permutation of the leaves (i.e. objects) that optimises a given criterion. Our algorithm is more flexible than currently available seriation algorithms because it allows the user to either choose from a variety of seriation criteria or to input their own criteria. This choice of seriation criteria is an important feature because different criteria are suitable for different visualisation settings. Common seriation criteria include measurements of the path length through a set of objects and measurements of anti-Robinson form in a symmetric matrix. We propose new seriation criteria called lazy path length and banded anti-Robinson form, and demonstrate their effectiveness in a variety of visualisation settings.

    Item Type: Book Section
    Additional Information: Both authors supported by a Research Frontiers Grant from Science Foundation Ireland.
    Keywords: Visualisation; Seriation; Hierarchical clustering;
    Academic Unit: Faculty of Science and Engineering > Mathematics and Statistics
    Item ID: 5553
    Depositing User: Dr. Catherine Hurley
    Date Deposited: 17 Nov 2014 15:25
    Publisher: International Statistical Institute
    Refereed: No
    Funders: Science Foundation Ireland
    URI:

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