Minimum Error Entropy Classification (Studies in Computational Intelligence, 420)

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

ISBN 10: 3642437427 / ISBN 13: 9783642437427

Published by Springer, 2014

In. Seller Inventory # ria9783642437427_new

Synopsis:

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.

From the Back 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.

Bibliographic Details

Title: Minimum Error Entropy Classification (...
Publisher: Springer
Publication Date: 2014
Binding: Soft cover
Condition: New