Başlık:
Minimum Error Entropy Classification
Yazar:
Marques de Sá, Joaquim P. author.
ISBN:
9783642290299
Ek Yazar:
Fiziksel Tanım:
XVIII, 262 p. online resource.
Series:
Studies in Computational Intelligence, 420
Contents:
Introduction -- Continuous Risk Functionals -- MEE with Continuous Errors -- MEE with Discrete Errors -- EE-Inspired Risks -- Applications.
Abstract:
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.
Added Corporate Author:
Electronic Access:
http://dx.doi.org/10.1007/978-3-642-29029-9