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120724s2013 gw | s |||| 0|eng d |
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|a 9783642290299
|9 978-3-642-29029-9
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|a 10.1007/978-3-642-29029-9
|2 doi
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|a Q342
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|a UYQ
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|a COM004000
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|a 006.3
|2 23
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|a Marques de S,̀ Joaquim P.
|e author.
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|a Minimum Error Entropy Classification
|c by Joaquim P. Marques de S,̀ Lus̕ M.A. Silva, Jorge M.F. Santos, Lus̕ A. Alexandre.
|h [electronic resource] /
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2013.
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|a XVIII, 262 p. 110 illus.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a text file
|b PDF
|2 rda
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|a Studies in Computational Intelligence,
|v 420
|x 1860-949X ;
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|a Introduction -- Continuous Risk Functionals -- MEE with Continuous Errors -- MEE with Discrete Errors -- EE-Inspired Risks -- Applications.
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|a 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<U+0010>layer perceptrons, recurrent neural networks, complexvalued neural networks, modular neural networks, and decision trees. A clustering algorithm using a MEE<U+0010>like concept is also presented. Examples, tests, evaluation experiments and comparison with similar machines using classic approaches, complement the descriptions.
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|a Engineering.
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|a Artificial intelligence.
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|a Engineering.
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|a Computational Intelligence.
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|a Artificial Intelligence (incl. Robotics).
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|a Statistical Physics, Dynamical Systems and Complexity.
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|a Silva, Lus̕ M.A.
|e author.
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|a Santos, Jorge M.F.
|e author.
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|a Alexandre, Lus̕ A.
|e author.
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9783642290282
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|a Studies in Computational Intelligence,
|v 420
|x 1860-949X ;
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|u https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-642-29029-9
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|a ZDB-2-ENG
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|a Engineering (Springer-11647)
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