Algorithms from and for Nature and Life

Classification and Data Analysis

  • Berthold Lausen
  • Dirk Van den Poel
  • Alfred Ultsch

Table of contents

  1. Front Matter
    Pages i-xx
  2. Invited

    1. Front Matter
      Pages 1-1
    2. Andrea Cerioli, Marco Riani, Francesca Torti
      Pages 3-17
    3. Willem J. Heiser, Antonio D’Ambrosio
      Pages 19-31
  3. Clustering and Unsupervised Learning

    1. Front Matter
      Pages 47-47
    2. Grigory Alexandrovich, Hajo Holzmann, Surajit Ray
      Pages 49-57
    3. Florent Domenach, Ali Tayari
      Pages 59-67
    4. Wolfgang Gaul, Rebecca Klages
      Pages 79-86
    5. Jan Hendrik Kobarg, Theodore Alexandrov
      Pages 95-103
    6. Akinori Okada, Satoru Yokoyama
      Pages 105-113
    7. Cristina Tortora, Mireille Gettler Summa, Francesco Palumbo
      Pages 115-123
  4. Statistical Data Analysis, Visualization and Scaling

    1. Front Matter
      Pages 125-125
    2. Damien McParland, Isobel Claire Gormley
      Pages 127-135
    3. Michael Salter-Townshend, Thomas Brendan Murphy
      Pages 137-145
    4. Ulas Akkucuk, J. Douglas Carroll, Stephen L. France
      Pages 147-154

About these proceedings

Introduction

This volume provides approaches and solutions to challenges occurring at the interface of research fields such as, e.g., data analysis, data mining and knowledge discovery, computer science, operations research, and statistics. In addition to theory-oriented contributions various application areas are included. Moreover, traditional classification research directions concerning network data, graphs, and social relationships as well as statistical musicology describe examples for current interest fields tackled by the authors. The book comprises a total of 55 selected papers presented at the Joint Conference of the German Classification Society (GfKl), the German Association for Pattern Recognition (DAGM), and the Symposium of the International Federation of Classification Societies (IFCS) in 2011.​

Keywords

Applied Statistics Classification Clustering Data Analysis Statistical Methodology

Editors and affiliations

  • Berthold Lausen
    • 1
  • Dirk Van den Poel
    • 2
  • Alfred Ultsch
    • 3
  1. 1.University of Essex Department of Mathematical SciencesColchesterUnited Kingdom
  2. 2.Ghent University Department of MarketingGhentBelgium
  3. 3.University of Marburg Databionics, FB 12MarburgGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-00035-0
  • Copyright Information Springer International Publishing Switzerland 2013
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-00034-3
  • Online ISBN 978-3-319-00035-0
  • Series Print ISSN 1431-8814
  • About this book
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