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Way / Scargle / Ali

Advances in Machine Learning and Data Mining for Astronomy

Medium: Buch
ISBN: 978-1-4398-4173-0
Verlag: CRC Press
Erscheinungstermin: 29.03.2012
Lieferfrist: bis zu 10 Tage

Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines, the material discussed in this text transcends traditional boundaries between various areas in the sciences and computer science.

The book’s introductory part provides context to issues in the astronomical sciences that are also important to health, social, and physical sciences, particularly probabilistic and statistical aspects of classification and cluster analysis. The next part describes a number of astrophysics case studies that leverage a range of machine learning and data mining technologies. In the last part, developers of algorithms and practitioners of machine learning and data mining show how these tools and techniques are used in astronomical applications.

With contributions from leading astronomers and computer scientists, this book is a practical guide to many of the most important developments in machine learning, data mining, and statistics. It explores how these advances can solve current and future problems in astronomy and looks at how they could lead to the creation of entirely new algorithms within the data mining community.


Produkteigenschaften


  • Artikelnummer: 9781439841730
  • Medium: Buch
  • ISBN: 978-1-4398-4173-0
  • Verlag: CRC Press
  • Erscheinungstermin: 29.03.2012
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2012
  • Serie: Chapman & Hall/CRC Data Mining and Knowledge Discovery Series
  • Produktform: Gebunden
  • Gewicht: 1456 g
  • Seiten: 744
  • Format (B x H x T): 180 x 257 x 48 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Herausgeber

Part I Foundational Issues. Part II Astronomical Applications: Source Identification. Classification. Signal Processing (Time-Series) Analysis. The Largest Data Sets. Part III Machine Learning Methods. Index.