Overview
- Presents a broad-range of perspectives on data analysis, providing readers with a comprehensive account of the field
- Focuses on the practical aspects as well as presenting the theory comprehensively
- A special emphasis is given to put on pointing out the pitfalls that lead to wrong or insufficient analysis of results
- Hands-on examples are given to provide readers with further insight into the topic
- Includes supplementary material: sn.pub/extras
Part of the book series: Texts in Computer Science (TCS)
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Table of contents (10 chapters)
Keywords
About this book
Reviews
From the reviews:
“The authors, leading scholars in the field based in Germany and Spain, seek to offer a hands-on instructional approach to basic data analysis techniques and consider their use in solving problems. The reader is taken through the process, following the interlinked steps of project understanding, data understanding, data preparation, modelling, and deployment and monitoring. The text reviews the basics of classical statistics that support and justify many data analysis methods, and includes a glossary of statistical terms.” (Times Higher Education, 26 May 2011)
“The clear and complete exposition of arguments, along with the attention to formalization and the balanced number of bibliographic references, make this book a bright introduction to intelligent data analysis. It is an excellent choice for graduate or advanced undergraduate courses, as well as for researchers and professionals who want get acquainted with this field of study. … Overall, the authors hit their target producing a textbook that aids in understanding the basic processes, methods, and issues for intelligent data analysis.” (Corrado Mencar, ACM Computing Reviews, April, 2011)
“The book provides a thorough introduction to data mining that covers theoretical background as well as the use of tools (KNIME and R). The book is intended as a textbook for a broad audience from graduate and advanced undergraduate students to professional data analysts. … each chapter ends with a list of references to identify relevant research. Hence, I recommend this book as an introductory text on data analysis for the intended target audience.” (Gottfried Vossen, Zentralblatt MATH, Vol. 1210, 2011)
Authors and Affiliations
Bibliographic Information
Book Title: Guide to Intelligent Data Analysis
Book Subtitle: How to Intelligently Make Sense of Real Data
Authors: Michael R. Berthold, Christian Borgelt, Frank Höppner, Frank Klawonn
Series Title: Texts in Computer Science
DOI: https://doi.org/10.1007/978-1-84882-260-3
Publisher: Springer London
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag London Limited 2010
Softcover ISBN: 978-1-4471-2572-3Published: 05 September 2012
eBook ISBN: 978-1-84882-260-3Published: 23 June 2010
Series ISSN: 1868-0941
Series E-ISSN: 1868-095X
Edition Number: 1
Number of Pages: XIII, 394
Number of Illustrations: 63 b/w illustrations, 78 illustrations in colour
Topics: Artificial Intelligence