Minimum Error Entropy Classification: 420 (Studies in Computational Intelligence) - Tapa blanda

Marques De Sá, Joaquim P.; Silva, Luís M.A.; Santos, Jorge M.F.; Alexandre, Luís A.

 
9783642437427: Minimum Error Entropy Classification: 420 (Studies in Computational Intelligence)

Sinopsis

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.

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De la contraportada

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.

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9783642290282: Minimum Error Entropy Classification: 420 (Studies in Computational Intelligence)

Edición Destacada

ISBN 10:  3642290280 ISBN 13:  9783642290282
Editorial: Springer, 2012
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