Editors:
- 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?
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Classification, Data Analysis, and Knowledge Organization (STUDIES CLASS)
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Table of contents (49 papers)
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Front Matter
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AREA Statistics and Data Analysis: Classification, Cluster Analysis, Factor Analysis and Model Selection
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Front Matter
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AREA Machine Learning and Knowledge Discovery: Clustering, Classifiers, Streams and Social Networks
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Front Matter
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About this book
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)Editors and Affiliations
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Faculty of Computer Science, Otto-von-Guericke-Universität Magdeburg, Magdeburg, Germany
Myra Spiliopoulou
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Institute of Computer Science, University of Hildesheim, Hildesheim, Germany
Lars Schmidt-Thieme, Ruth Janning
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
DOI: https://doi.org/10.1007/978-3-319-01595-8
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Softcover ISBN: 978-3-319-01594-1Published: 09 December 2013
eBook ISBN: 978-3-319-01595-8Published: 26 November 2013
Series ISSN: 1431-8814
Series E-ISSN: 2198-3321
Edition Number: 1
Number of Pages: XXI, 470
Number of Illustrations: 88 b/w illustrations, 32 illustrations in colour
Topics: Statistics and Computing/Statistics Programs, Data Mining and Knowledge Discovery, Marketing, Finance, general, Biostatistics, General Psychology