Data & IT
Pocket
Minimum Error Entropy Classification
Joaquim P Marques De S • Lus M A Silva • Jorge M F Santos • Lus A Alexandre
1999:-
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- Inbunden 1999:-
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 multilayer perceptrons, recurrent neural networks, complexvalued neural networks, modular neural networks, and decision trees. A clustering algorithm using a MEElike concept is also presented. Examples, tests, evaluation experiments and comparison with similar machines using classic approaches, complement the descriptions.
- Format: Pocket/Paperback
- ISBN: 9783642437427
- Språk: Engelska
- Antal sidor: 262
- Utgivningsdatum: 2014-08-09
- Förlag: Springer-Verlag Berlin and Heidelberg GmbH & Co. K