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Data Analysis, Classification, and Related Methods

  • Conference proceedings
  • © 2000

Overview

Editors:
  1. Henk A. L. Kiers

    1. University of Groningen Heymans Institute (PA), Groningen, The Netherlands

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  2. Jean-Paul Rasson

    1. Facultés Universitaires Notre-Dame de la Paix, University of Namur, Namur, Belgium

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  3. Patrick J. F. Groenen

    1. Data Theory Group Department of Education, Leiden University, Leiden, The Netherlands

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  4. Martin Schader

    1. Lehrstuhl für Wirtschaftsinformatik III Schloß, University of Mannheim, Mannheim, Germany

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Table of contents (65 papers)

  1. Front Matter

    Pages I-XIII
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  2. Cluster Analysis

    1. Front Matter

      Pages 1-1
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    2. Cluster Analysis and Mixture Models

      1. Classifier Probabilities
        • J. A. Hartigan
        Pages 3-15
      2. Cluster Analysis Based on Data Depth
        • Richard Hoberg
        Pages 17-22
      3. An Autonomous Clustering Technique
        • Yoshiharu Sato
        Pages 23-28
      4. Unsupervised Non-hierarchical Entropy-based Clustering
        • M. Jardino
        Pages 29-34
      5. Improving the Additive Tree Representation of a Dissimilarity Matrix Using Reticulations
        • Vladimir Makarenkov, Pierre Legendre
        Pages 35-40
      6. Double Versus Optimal Grade Clusterings
        • Alicja Ciok
        Pages 41-46
      7. The Effects of Initial Values and the Covariance Structure on the Recovery of some Clustering Methods
        • Istvan Hajnal, Geert Loosveldt
        Pages 47-52
      8. What Clusters Are Generated by Normal Mixtures?
        • Christian Hennig
        Pages 53-58
      9. A Bootstrap Procedure for Mixture Models
        • Suzanne Winsberg, Geert deSoete
        Pages 59-62

    3. Fuzzy Clustering

      1. A New Criterion for Obtaining a Fuzzy Partition from a Hybrid Fuzzy/Hierarchical Clustering Method
        • Arnaud Devillez, Patrice Billaudel, Gérard Villermain Lecolier
        Pages 63-68
      2. Application of Fuzzy Mathematical Morphology for Unsupervised Color Pixels Classification
        • A. Gillet, C. Botte-Lecocq, L. Macaire, J.-G. Postaire
        Pages 69-75
      3. A Hyperbolic Fuzzt <i>k</i>-Means Clustering and Algorithm for Neural Networks
        • Norio Watenable, Tadashi Imaizumi, Toshiko Kikuchi
        Pages 77-82

    4. Special Purpose Classification Procedures and Applications

      1. A Toolkit for Development of the Domain-Oriented Dictionaries for Structuring Document Flows
        • Pavel P. Makagonov, Mikhail A. Alexandrov, Konstantin Sboychakov
        Pages 83-88
      2. Classification of Single Malt Whiskies
        • David Wishart
        Pages 89-94
      3. Robust Approach in Hierarchical Clustering: Application to the Sectorisation of an Oil Field
        • Jean-Paul Valois
        Pages 95-100
      4. A Minimax Solution for Sequential Classification Problems
        • Hans J. Vos
        Pages 101-106

    5. Verification and Comparison of Clusterings

      1. Comparison of Ultrametrics Obtained With Real Data, Using the <i>P</i> <sub> <i>L</i> </sub> and <i>VAL</i> <sub> <i>Aw</i> </sub> Coefficients
        • Isabel Pinto Doria, Georges Le Calvé, Helena Bacelar-Nicolau
        Pages 107-112
      2. Numerical Comparisons of two Spectral Decompositions for Vertex Clustering
        • P. Kuntz, F. Henaux
        Pages 113-118
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Keywords

About this book

This volume contains a selection of papers presented at the Seven~h Confer­ ence of the International Federation of Classification Societies (IFCS-2000), which was held in Namur, Belgium, July 11-14,2000. From the originally sub­ mitted papers, a careful review process involving two reviewers per paper, led to the selection of 65 papers that were considered suitable for publication in this book. The present book contains original research contributions, innovative ap­ plications and overview papers in various fields within data analysis, classifi­ cation, and related methods. Given the fast publication process, the research results are still up-to-date and coincide with their actual presentation at the IFCS-2000 conference. The topics captured are: • Cluster analysis • Comparison of clusterings • Fuzzy clustering • Discriminant analysis • Mixture models • Analysis of relationships data • Symbolic data analysis • Regression trees • Data mining and neural networks • Pattern recognition • Multivariate data analysis • Robust data analysis • Data science and sampling The IFCS (International Federation of Classification Societies) The IFCS promotes the dissemination of technical and scientific information data analysis, classification, related methods, and their applica­ concerning tions.

Editors and Affiliations

  • University of Groningen Heymans Institute (PA), Groningen, The Netherlands

    Henk A. L. Kiers

  • Facultés Universitaires Notre-Dame de la Paix, University of Namur, Namur, Belgium

    Jean-Paul Rasson

  • Data Theory Group Department of Education, Leiden University, Leiden, The Netherlands

    Patrick J. F. Groenen

  • Lehrstuhl für Wirtschaftsinformatik III Schloß, University of Mannheim, Mannheim, Germany

    Martin Schader

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