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Product Description
Product Description
This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the several hundred entries in this preeminent work include useful literature references, providing the reader with a portal to more detailed information on any given topic. Topics for the "Encyclopedia of Machine Learning" 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 style of the entries in the "Encyclopedia of Machine Learning" is expository and tutorial, making the book a practical resource for high-performance computing 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.
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 Naïve 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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