Authors:
- 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
Part of the book series: Studies in Computational Intelligence (SCI, volume 420)
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Table of contents (6 chapters)
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Front Matter
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Back Matter
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)
Authors and Affiliations
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Divisão de Sinal e Imagem Campus FEUP, INEB-Instituto de Engenharia Biomédica Divisão de Sinal e Imagem Campus FEUP, Porto, Portugal
Joaquim P. Marques de Sá
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Campus Universitário de Santiago, Universidade de Aveiro Departamento de Matemática, Aveiro, Portugal
Luís M.A. Silva
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Dept. of Mathematics, ISEP, School of Engineering Polytechnic of Porto, Porto, Portugal
Jorge M.F. Santos
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Departamento de Informática, Universidade da Beira Interior, Covilhã, Portugal
Luís A. Alexandre
Bibliographic Information
Book Title: Minimum Error Entropy Classification
Authors: Joaquim P. Marques de Sá, Luís M.A. Silva, Jorge M.F. Santos, Luís A. Alexandre
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-642-29029-9
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2013
Hardcover ISBN: 978-3-642-29028-2Published: 25 July 2012
Softcover ISBN: 978-3-642-43742-7Published: 09 August 2014
eBook ISBN: 978-3-642-29029-9Published: 25 July 2012
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XVIII, 262
Topics: Computational Intelligence, Artificial Intelligence, Complex Systems, Statistical Physics and Dynamical Systems