Encyclopedia Of Machine Learning

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E-Book Overview

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.

E-Book Content

Encyclopedia of Machine Learning Claude Sammut, Geoffrey I. Webb (Eds.) Encyclopedia of Machine Learning With Figures and Tables 123 Editors Claude Sammut School of Computer Science and Engineering University of New South Wales Sydney Australia [email protected] Geoffrey I. Webb Faculty of Information Technology Clayton School of Information Technology Monash University P.O. Box Victoria Australia [email protected] ISBN - - - - e-ISBN - - - - Print and electronic bundle ISBN - - - - DOI . / - - - - Springer New York Library of Congress Control Number: © Springer Science+Business Media, LLC All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, Spring Street, New York, NY , USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. While the advice and information in this book are believed to be true and accurate at the date of going to press, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com) Preface The term “Machine Learning” came into wide-spread use following the first workshop by that name, held at Carnegie-Mellon University in . The papers from that workshop were published as Machine Learning: An Artificial Intelligence Approach, edited by Ryszard Michalski, Jaime Carbonell and Tom Mitchell. Machine Learning came to be identified as a research field in its own right as the workshops evolved into international conferences and