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by Claude Sammut,Geoffrey I. Webb
Download Encyclopedia of Machine Learning fb2
Computer Science
  • Author:
    Claude Sammut,Geoffrey I. Webb
  • ISBN:
    0387307680
  • ISBN13:
    978-0387307688
  • Genre:
  • Publisher:
    Springer; 2010 edition (March 28, 2011)
  • Pages:
    1031 pages
  • Subcategory:
    Computer Science
  • Language:
  • FB2 format
    1223 kb
  • ePUB format
    1289 kb
  • DJVU format
    1213 kb
  • Rating:
    4.9
  • Votes:
    568
  • Formats:
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ISBN-13: 978-0387307688. He has published more than 150 scientific papers and is the author of the data mining software package Magnum Opus.

Topics for the Encyclopedia of Machine Learning were selected by a distinguished international .

Topics for the Encyclopedia of Machine Learning were selected by a distinguished international advisory board.

au Geoffrey I. Webb Faculty of Information Technology Clayton School of Information Technology Monash University . Box  Victoria Australia  Geoff.

Updates and informs through in-depth essays and definitions, historical background, key applications, and bibliographies. Supports quick and efficient discovery of information through extensive cross-references.

Geoffrey I. Webb Faculty of Information Technology Monash University Melbourne, VIC, Australia. Webb (ed., Encyclopedia of Machine Learning and Data Mining, DOI 1. 1. 2. (Muggleton and Bryant 2000) and HAIL (Ray et al.

Claude Sammut, Geoffrey I. Webb. Most entries in this preeminent work include useful literature references. Topics for the Encyclopedia of Machine Learning were selected by a distinguished international advisory board.

Encyclopedia of machine learning. KM Ting, C Sammut, GI Webb. Boston, MA: Springer, 2011. Learning to fly by combining reinforcement learning with behavioural cloning. EF Morales, C Sammut. Proceedings of the twenty-first international conference on Machine learning, 76, 2004. Automatic construction of reactive control systems using symbolic machine learning.

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This comprehensive encyclopedia, with over 250 entries in an A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of machine learning. Most entries in this preeminent work include useful literature references.


Topics for the Encyclopedia of Machine Learning were selected by a distinguished international advisory board. These peer-reviewed, highly-structured entries include definitions, illustrations, applications, bibliographies and links to related literature, providing the reader with a portal to more detailed information on any given topic.


The style of the entries in the Encyclopedia of Machine Learning is expository and tutorial, making the book a practical resource for machine learning experts, as well as professionals in other fields who need to access this vital information but may not have the time to work their way through an entire text on their topic of interest.


The authoritative reference is published both in print and online. The print publication includes an index of subjects and authors. The online edition supplements this index with hyperlinks as well as internal hyperlinks to related entries in the text, CrossRef citations, and links to additional significant research.