Data Analysis, Machine Learning and Knowledge Discovery

  • Myra Spiliopoulou
  • Lars Schmidt-Thieme
  • Ruth Janning
Conference proceedings

Table of contents

  1. Front Matter
    Pages i-xxi
  2. AREA Statistics and Data Analysis: Classification, Cluster Analysis, Factor Analysis and Model Selection

    1. Front Matter
      Pages 1-1
    2. Udo Bankhofer, Dieter William Joenssen
      Pages 3-11
    3. Tim Beige, Thomas Terhorst, Claus Weihs, Holger Wormer
      Pages 13-21
    4. Bernd Bischl, Julia Schiffner, Claus Weihs
      Pages 23-31
    5. Nguyen Hoang Huy, Stefan Frenzel, Christoph Bandt
      Pages 51-59
    6. Florian Klapproth, Sabine Krolak-Schwerdt, Thomas Hörstermann, Romain Martin
      Pages 61-69
    7. Tatjana Lange, Karl Mosler, Pavlo Mozharovskyi
      Pages 71-78
    8. Oliver Meyer, Bernd Bischl, Claus Weihs
      Pages 87-95
    9. Hans-Joachim Mucha, Hans-Georg Bartel, Jens Dolata
      Pages 105-113
    10. Tobias Voigt, Roland Fried, Michael Backes, Wolfgang Rhode
      Pages 115-124
  3. AREA Machine Learning and Knowledge Discovery: Clustering, Classifiers, Streams and Social Networks

    1. Front Matter
      Pages 125-125
    2. Maheen Bakhtyar, Nam Dang, Katsumi Inoue, Lena Wiese
      Pages 127-134
    3. Matthew Bolaños, John Forrest, Michael Hahsler
      Pages 135-143
    4. Krisztian Buza
      Pages 145-152
    5. Sandrine Mouysset, Joseph Noailles, Daniel Ruiz, Clovis Tauber
      Pages 153-162
    6. Robin Senge, Juan José del Coz, Eyke Hüllermeier
      Pages 163-170
    7. Igor Vatolkin, Bernd Bischl, Günter Rudolph, Claus Weihs
      Pages 171-178
  4. AREA Data Analysis and Classification in Marketing

  5. AREA Data Analysis in Finance

  6. AREA Data Analysis in Biostatistics and Bioinformatics

    1. Front Matter
      Pages 283-283
    2. Andre Burkovski, Ludwig Lausser, Johann M. Kraus, Hans A. Kestler
      Pages 285-293
    3. Dominik Heider, Christoph Bartenhagen, J. Nikolaj Dybowski, Sascha Hauke, Martin Pyka, Daniel Hoffmann
      Pages 295-302
    4. Florian Schmid, Ludwig Lausser, Hans A. Kestler
      Pages 303-311
  7. AREA Interdisciplinary Domains: Data Analysis in Music, Education and Psychology

    1. Front Matter
      Pages 313-313
    2. Nadja Bauer, Klaus Friedrichs, Dominik Kirchhoff, Julia Schiffner, Claus Weihs
      Pages 315-324
    3. Andre Busche, Ruth Janning, Tomáš Horváth, Lars Schmidt-Thieme
      Pages 325-332
    4. Markus Eichhoff, Claus Weihs
      Pages 333-341
    5. Kay F. Hildebrand
      Pages 359-367
    6. Ruben Hillewaere, Bernard Manderick, Darrell Conklin
      Pages 369-377
    7. Daniel Kasper, Ali Ünlü, Bernhard Gschrey
      Pages 389-396

About these proceedings


Data analysis, machine learning and knowledge discovery are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medicine, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and knowledge discovery presented during the 36th annual conference of the German Classification Society (GfKl). The conference was held at the University of Hildesheim (Germany) in August 2012. ​


Applied Statistics Classification Clustering Data Analysis Prediction

Editors and affiliations

  • Myra Spiliopoulou
    • 1
  • Lars Schmidt-Thieme
    • 2
  • Ruth Janning
    • 3
  1. 1.Faculty of Computer ScienceOtto-von-Guericke-Universität MagdeburgMagdeburgGermany
  2. 2.Institute of Computer ScienceUniversity of HildesheimHildesheimGermany
  3. 3.Institute of Computer ScienceUniversity of HildesheimHildesheimGermany

Bibliographic information

Industry Sectors
Finance, Business & Banking
IT & Software
Consumer Packaged Goods
Oil, Gas & Geosciences