Studies in Classification, Data Analysis, and Knowledge Organization

Data Analysis, Machine Learning and Knowledge Discovery

Editors: Spiliopoulou, Myra, Schmidt-Thieme, Lars, Janning, Ruth (Eds.)

  • Focus on the commonalities concerning data analysis in computer science and in statistics
  • Emphasis on both methods (statistical analysis and machine learning) and applications (marketing, finance, bioinformatics, musicology, psychology)
  • Presentation of general methods and techniques that can be applied to a variety of fields​
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  • ISBN 978-3-319-01595-8
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About this book

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. ​

Reviews

From the book reviews:

“The book is organized in seven parts … . The book is a very interesting collection of papers describing various approaches of data mining and machine learning on aspects from bioinformatics to music classification. It is an excellent addition to the field and it can be used as starting point for projects from undergraduate to post-graduate level.” (Irina Ioana Mohorianu, zbMATH, Vol. 1301, 2015)

Table of contents (49 chapters)

  • On Limiting Donor Usage for Imputation of Missing Data via Hot Deck Methods

    Bankhofer, Udo (et al.)

    Pages 3-11

  • The Most Dangerous Districts of Dortmund

    Beige, Tim (et al.)

    Pages 13-21

  • Benchmarking Classification Algorithms on High-Performance Computing Clusters

    Bischl, Bernd (et al.)

    Pages 23-31

  • Visual Models for Categorical Data in Economic Research

    Brzezińska, Justyna

    Pages 33-40

  • How Many Bee Species? A Case Study in Determining the Number of Clusters

    Hennig, Christian

    Pages 41-49

Buy this book

eBook $99.00
price for USA (gross)
  • ISBN 978-3-319-01595-8
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $129.00
price for USA
  • ISBN 978-3-319-01594-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
Data Analysis, Machine Learning and Knowledge Discovery
Editors
  • Myra Spiliopoulou
  • Lars Schmidt-Thieme
  • Ruth Janning
Series Title
Studies in Classification, Data Analysis, and Knowledge Organization
Copyright
2014
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing Switzerland
eBook ISBN
978-3-319-01595-8
DOI
10.1007/978-3-319-01595-8
Softcover ISBN
978-3-319-01594-1
Series ISSN
1431-8814
Edition Number
1
Number of Pages
XXI, 470
Number of Illustrations and Tables
88 b/w illustrations, 32 illustrations in colour
Topics