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Item Details
Title: MINIMUM ERROR ENTROPY CLASSIFICATION
By: Joaquim P. Marques De Sa, Luis Silva, Jorge M. Santos
Format: Paperback

List price: £99.99


We currently do not stock this item, please contact the publisher directly for further information.

ISBN 10: 3642437427
ISBN 13: 9783642437427
Publisher: SPRINGER-VERLAG BERLIN AND HEIDELBERG GMBH & CO. KG
Pub. date: 9 August, 2014
Edition: 2013 ed.
Series: Studies in Computational Intelligence 420
Pages: 262
Description: This book explains the minimum error entropy (MEE) concept applied to data classification machines. Discusses theoretical results, offers a clustering algorithm using a MEE-like concept, and includes tests, evaluation experiments and comparative applications.
Synopsis: This book explains the minimum error entropy (MEE) concept applied to data classification machines. Theoretical results on the inner workings of the MEE concept, in its application to solving a variety of classification problems, are presented in the wider realm of risk functionals. Researchers and practitioners also find in the book a detailed presentation of practical data classifiers using MEE. These include multi-layer perceptrons, recurrent neural networks, complexvalued neural networks, modular neural networks, and decision trees. A clustering algorithm using a MEE-like concept is also presented. Examples, tests, evaluation experiments and comparison with similar machines using classic approaches, complement the descriptions.
Illustrations: biography
Publication: Germany
Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Returns: Returnable
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