Minimum Error Entropy Classification (Studies in Computational Intelligence) Hardcover - 2012 - 2013th Edition
by Marques de Sá, Joaquim P.; Silva, Luís M.A.; Santos, Jorge M.F.; Alexandre, Luís A
From the rear cover
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.
Details
- Title Minimum Error Entropy Classification (Studies in Computational Intelligence)
- Author Marques de Sá, Joaquim P.; Silva, Luís M.A.; Santos, Jorge M.F.; Alexandre, Luís A
- Binding Hardcover
- Edition number 2013th
- Edition 2013
- Pages 260
- Language ENG
- Publisher Springer
- Date 2012-07
- Features Illustrated
- ISBN 9783642290282
-
Themes
- Aspects (Academic): Science/Technology Aspects
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