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Some Thoughts about Classification

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Classification, Clustering, and Data Analysis

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Abstract

The paper contains some general remarks on the high art of data analysis, some philosophical thoughts about classification, a partial review of outliers and robustness from the point of view of applications, including a discussion of the problem of model choice, and a review of several aspects of robust estimation of covariance matrices, including the pragmatic choice of a weight function based on empirical and theoretical evidence. Several sections contain new (or at least original) ideas: There are some proposals for incorporating robustness into Bayesian practice and theory, including weighted log likelihoods and Bayes’ theorem for weighted data. Some small ideas refer to artificial classification in a continuum, to a “robust” (Prohorov-type) metric for high-dimensional data, and to the use of multiple minimum spanning trees. A promising but difficult research idea for clustering on the real line, based on a new smoothing method, concludes the paper.

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Author information

Authors and Affiliations

  1. Seminar for Statistics of ETH, Swiss Federal Institute of Technology, Leonhardstrasse 27, LEO D2, CH-8092, Zurich, Switzerland

    Frank Hampel

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  1. Frank Hampel
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Editors and Affiliations

  1. Wroclaw University of Economics, ul. Komandorska 118/120, 53-345, Wroclaw, Poland

    Krzysztof Jajuga

  2. Department of Statistics, Cracow University of Economics, ul. Rakowicka 27, 31-510, Cracow, Poland

    Andrzej Sokołowski

  3. Institute of Statistics, Technical University of Aachen, Wuellnerstrasse 3, 52056, Aachen, Germany

    Hans-Hermann Bock

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Hampel, F. (2002). Some Thoughts about Classification. In: Jajuga, K., Sokołowski, A., Bock, HH. (eds) Classification, Clustering, and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-56181-8_1

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  • DOI: https://doi.org/10.1007/978-3-642-56181-8_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43691-1

  • Online ISBN: 978-3-642-56181-8

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