1.

Record Nr.

UNINA9910437918803321

Titolo

Minimum error entropy classification / / Joaquim P. Marques de Sa ... [et al.]

Pubbl/distr/stampa

Berlin ; ; New York, : Springer, c2013

ISBN

9783642290299

3642290299

Edizione

[1st ed. 2013.]

Descrizione fisica

1 online resource (XVIII, 262 p.)

Collana

Studies in computational intelligence, , 1860-949X ; ; 420

Altri autori (Persone)

SaJ. P. Marques de <1946->

Disciplina

006.3/1

Soggetti

Machine learning

Computational learning theory

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Bibliographic Level Mode of Issuance: Monograph

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Introduction -- Continuous Risk Functionals -- MEE with Continuous Errors -- MEE with Discrete Errors -- EE-Inspired Risks -- Applications.

Sommario/riassunto

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.