Minimum Error Entropy Classification (e-bok)
Format
E-bok
Filformat
PDF med LCP-kryptering (0.0 MB)
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Språk
Engelska
Utgivningsdatum
2012-07-25
Förlag
Springer Berlin Heidelberg
ISBN
9783642290299

Minimum Error Entropy Classification E-bok

E-bok (PDF, LCP),  Engelska, 2012-07-25
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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.
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