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Guide to intelligent data analysis

how to intelligently make sense of real data
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Year: 2010
Publisher: London, Springer
Media group: Ausleihbestand
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Branch: Hauptstelle Locations: MA-20 452 Status: available Reservations: 0 Due date: Barcode: 00264458 Floor plans: Floor plan Lending note:

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Each passing year bears witness to the development of ever more powerful computers, increasingly fast and cheap storage media, and even higher bandwidth data connections. This makes it easy to believe that we can now – at least in principle - solve any problem we are faced with so long as we only have enough data.
 
Yet this is not the case. Although large databases allow us to retrieve many different single pieces of information and to compute simple aggregations, general patterns and regularities often go undetected. Furthermore, it is exactly these patterns, regularities and trends that are often most valuable.
 
To avoid the danger of "drowning in information, but starving for knowledge" the branch of research known as data analysis has emerged, and a considerable number of methods and software tools have been developed. However, it is not these tools alone but the intelligent application of human intuition in combination with computational power, of sound background knowledge with computer-aided modeling, and of critical reflection with convenient automatic model construction, that results in successful intelligent data analysis projects. Guide to Intelligent Data Analysis provides a hands-on instructional approach to many basic data analysis techniques, and explains how these are used to solve data analysis problems.
 
Topics and features:
 
Guides the reader through the process of data analysis, following the interdependent steps of project understanding, data understanding, data preparation, modeling, and deployment and monitoring
Equips the reader with the necessary information in order to obtain hands-on experience of the topics under discussion
Provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms
Includes numerous examples using R and KNIME, together with appendices introducing the open source software
Integrates illustrations and case-study-style examples to support pedagogical exposition
Supplies further tools and information at the associated website: http://www.idaguide.net/
This practical and systematic textbook/reference for graduate and advanced undergraduate students is also essential reading for all professionals who face data analysis problems. Moreover, it is a book to be used following one's exploration of it.
 

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Statement of Responsibility: Michael R. Berthold ; Christina Borgelt ; Frank Höppner ; Frank Klawonn
Year: 2010
Publisher: London, Springer
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Classification: Search for this systematic MA-20, BI-50
Subject type: Search for this subject type Monographien
ISBN: 978-1-4471-2572-3
ISBN (2nd): 1-4471-2572-X
Description: 1. edition, XIII, 394 S. : Ill., graph. Darst.
Tags: Datenverarbeitung; Biologie Methoden
Participating parties: Search for this character Berthold, Michael R.; Borgelt, Christian; Höppner, Frank; Klawonn, Frank
Language: Englisch
Footnote: Literaturangaben
Media group: Ausleihbestand