Home Revaluation Books Encyclopedia of Machine Learning and Data Mining by Sammut, Claude (Edited by)/ Webb, Geoffrey I. (Edited by) (ISBN: 9781489976857)

Encyclopedia of Machine Learning and Data Mining

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Encyclopedia of Machine Learning and Data Mining Hardback - 2017

by Sammut, Claude (Edited by)/ Webb, Geoffrey I. (Edited by)

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Springer, 2017. Hardcover. New. 2nd edition. 1333 pages. 10.00x7.25x3.25 inches.

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Title Encyclopedia of Machine Learning and Data Mining
Author Sammut, Claude (Edited by)/ Webb, Geoffrey I. (Edited by)
Binding Hardback
Condition New
Pages 1335
Volumes 2
Language ENG
Publisher Springer
Publication date 2017
Bookseller's Inventory # 2-148997685X
ISBN 9781489976857 / 148997685X
Weight 7.98 lbs (3.62 kg)
Dimensions 10.46 x 7.41 x 3.15 in (26.57 x 18.82 x 8.00 cm)
Category Computers - Data Base Management
Library of Congress subjects Data mining, Machine learning
Library of Congress Catalogue Number 2016958560
Dewey Decimal Code 006.31
Quantity available 1

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From the publisher

This authoritative, expanded and updated second edition of Encyclopedia of Machine Learning and Data Mining provides easy access to core information for those seeking entry into any aspect within the broad field of Machine Learning and Data Mining. A paramount work, its 800 entries - about 150 of them newly updated or added - are filled with valuable literature references, providing the reader with a portal to more detailed information on any given topic.Topics for the Encyclopedia of Machine Learning and Data Mining include Learning and Logic, Data Mining, Applications, Text Mining, Statistical Learning, Reinforcement Learning, Pattern Mining, Graph Mining, Relational Mining, Evolutionary Computation, Information Theory, Behavior Cloning, and many others. Topics were selected by a distinguished international advisory board. Each peer-reviewed, highly-structured entry includes a definition, key words, an illustration, applications, a bibliography, and links to related literature.The entries are expository and tutorial, making this reference a practical resource for students, academics, or professionals who employ machine learning and data mining methods in their projects. Machine learning and data mining techniques have countless applications, including data science applications, and this reference is essential for anyone seeking quick access to vital information on the topic.

About the author

Claude Sammut is a Professor of Computer Science and Engineering at the University of New South Wales, Australia, and Head of the Artificial Intelligence Research Group. He is the UNSW node Director of the ARC Centre of Excellence for Autonomous Systems and a member of the joint ARC/NH&MRC project on Thinking Systems. He is on the editorial boards of the Journal of Machine Learning Research, the Machine Learning Journal and New Generation Computing, and was the chairman of the 2007 International Conference on Machine Learning.

Geoffrey I. Webb is research professor in the faculty of Information Technology at Monash University, Melbourne, Australia. He has published more than 150 scientific papers and is the author of the data mining software package Magnum Opus. His research areas include strategies for strengthening the Nave Bayes machine learning technique, K-optimal pattern discovery, and work on Occam's razor. He is editor-in-chief of Springer's Data Mining and Knowledge Discovery journal, as well as being on the editorial board of Machine Learning.

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