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Advances in machine learning and data mining for astronomy [electronic resource] / edited by Michael J. Way ... [et al.].

Contributor(s): Way, Michael J.
Material type: materialTypeLabelBookSeries: Chapman & Hall/CRC data mining and knowledge discovery series: Publisher: Boca Raton : CRC Press, c2012Description: xxix, 698 p. : ill.ISBN: 9781439841747 (ebook : PDF).Subject(s): Astronomy -- Data processing | Data mining | Machine learningGenre/Form: Electronic books.Additional physical formats: No titleOnline resources: Distributed by publisher. Purchase or institutional license may be required for access. Also available in print edition.
Contents:
pt. 1. Foundational issues -- pt. 2. Astronomical applications -- pt. 3. Machine learning methods.
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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"A Chapman & Hall book."

Includes bibliographical references and index.

pt. 1. Foundational issues -- pt. 2. Astronomical applications -- pt. 3. Machine learning methods.

"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.

Also available in print edition.

Mode of access: World Wide Web.

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