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Studies in Computational Intelligence

Minimum Error Entropy Classification

Authors: Marques de Sá, J.P., Silva, L.M.A., Santos, J.M.F., Alexandre, L.A.

  • Presents data classification methodologies based on a minimum error entropy approach
  • Includes both theoretical results and applications to real world datasets
  • Written by leading experts in the field
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eBook $109.00
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  • ISBN 978-3-642-29029-9
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Hardcover $169.99
price for USA in USD
  • ISBN 978-3-642-29028-2
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Softcover $139.99
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  • ISBN 978-3-642-43742-7
  • Free shipping for individuals worldwide
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About this book

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.

Reviews

From the reviews:

 

“The paper deals with the theoretical background and corresponding applications of minimum error entropy (MEE) to different data classifications models … . Many examples and tests are also provided to illustrate the practical application of MEE in concrete classification problems. The book is dedicated to researchers and practitioners working on machine learning algorithms interested in using MEE in data classification.” (Florin Gorunescu, zbMATH, Vol. 1280, 2014)

Table of contents (6 chapters)

  • Introduction

    Marques de Sá, Joaquim P. (et al.)

    Pages 1-11

  • Continuous Risk Functionals

    Marques de Sá, Joaquim P. (et al.)

    Pages 13-39

  • MEE with Continuous Errors

    Marques de Sá, Joaquim P. (et al.)

    Pages 41-91

  • MEE with Discrete Errors

    Marques de Sá, Joaquim P. (et al.)

    Pages 93-120

  • EE-Inspired Risks

    Marques de Sá, Joaquim P. (et al.)

    Pages 121-137

Buy this book

eBook $109.00
price for USA in USD (gross)
  • ISBN 978-3-642-29029-9
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $169.99
price for USA in USD
  • ISBN 978-3-642-29028-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $139.99
price for USA in USD
  • ISBN 978-3-642-43742-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the eBook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
Minimum Error Entropy Classification
Authors
Series Title
Studies in Computational Intelligence
Series Volume
420
Copyright
2013
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-642-29029-9
DOI
10.1007/978-3-642-29029-9
Hardcover ISBN
978-3-642-29028-2
Softcover ISBN
978-3-642-43742-7
Series ISSN
1860-949X
Edition Number
1
Number of Pages
XVIII, 262
Topics