Data Analytics

Models and Algorithms for Intelligent Data Analysis

  • Thomas A. Runkler

Table of contents

  1. Front Matter
    Pages i-ix
  2. Thomas A. Runkler
    Pages 1-3
  3. Thomas A. Runkler
    Pages 5-20
  4. Thomas A. Runkler
    Pages 21-34
  5. Thomas A. Runkler
    Pages 35-54
  6. Thomas A. Runkler
    Pages 55-61
  7. Thomas A. Runkler
    Pages 63-78
  8. Thomas A. Runkler
    Pages 79-83
  9. Thomas A. Runkler
    Pages 85-101
  10. Thomas A. Runkler
    Pages 103-122
  11. Thomas A. Runkler
    Pages 123-126
  12. Thomas A. Runkler
    Pages 127-129
  13. Back Matter
    Pages 131-137

About this book


This book is a comprehensive introduction to the methods and algorithms and approaches of modern data analytics. It provides a sound mathematical basis, discusses advantages and drawbacks of different approaches, and enables the reader to design and implement data analytics solutions for real-world applications. This book has been used for more than ten years in numerous courses at the Technical University of Munich, in short courses at several other universities, and in tutorials at scientific conferences. Much of the content is based on the results of industrial research and development projects at Siemens.


Data Analytics - Data and Relations - Data Preprocessing - Data Visualization - Correlation - Regression - Forecasting - Classification - Clustering

Target Groups

Students of data analytics for engineering, computer science and math 

Practitioners working on data analytics projects

The Author

Thomas Runkler is doing research at Siemens Corporate Technology in Munich and teaching data analytics and machine learning at the Technical University of Munich.


Classification business intelligence data mining knowledge discovery machine learning

Authors and affiliations

  • Thomas A. Runkler
    • 1
  1. 1.MünchenGermany

Bibliographic information

  • DOI
  • Copyright Information Vieweg+Teubner Verlag | Springer Fachmedien Wiesbaden 2012
  • Publisher Name Vieweg+Teubner Verlag, Wiesbaden
  • eBook Packages Computer Science
  • Print ISBN 978-3-8348-2588-9
  • Online ISBN 978-3-8348-2589-6
  • Buy this book on publisher's site
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