The author of the book: Joaquim P. Marques de Sá
Format files: PDF, EPUB, TXT, DOCX
The size of the: 437 KB
Edition: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Date of issue: 9 August 2014
Description of the book "Minimum Error Entropy Classification":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 PDF approaches, complement the descriptions.
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