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Advances in machine learning and data mining for astronomy / edited by Michael J. Way ... [and three others]

Contributor(s): Material type: TextSeries: Chapman & Hall/CRC data mining and knowledge discovery seriesPublisher: Boca Raton : CRC Press / Taylor & Francis Group, [2012]Copyright date: c2012Description: xxix, 698 pages : illustrations (some color) ; 27 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781439841730
  • 143984173X
Subject(s): Genre/Form: DDC classification:
  • 522.85631 22 ADV
Summary: "This book provides a comprehensive overview of various data mining tools and techniques that are increasingly being used by researchers in the international astronomy community. It explores this new problem domain, discussing how it could lead to the development of entirely new algorithms. Leading contributors introduce data mining methods and then describe how the methods can be implemented into astronomy applications. The last section of the book discusses the Redshift Prediction Competition, which is an astronomy competition in the style of the Netflix Prize"--Provided by publisher.
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Holdings
Cover image Item type Current library Home library Collection Shelving location Call number Materials specified Vol info URL Copy number Status Notes Date due Barcode Item holds Item hold queue priority Course reserves
Book - Borrowing Central Library First floor Baccah 522.85631 ADV (Browse shelf(Opens below)) 2000088 Available 000034991
Total holds: 0

Includes bibliographical references and index.

"This book provides a comprehensive overview of various data mining tools and techniques that are increasingly being used by researchers in the international astronomy community. It explores this new problem domain, discussing how it could lead to the development of entirely new algorithms. Leading contributors introduce data mining methods and then describe how the methods can be implemented into astronomy applications. The last section of the book discusses the Redshift Prediction Competition, which is an astronomy competition in the style of the Netflix Prize"--Provided by publisher.

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