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Record Nr. |
UNINA9910437918803321 |
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Titolo |
Minimum error entropy classification / / Joaquim P. Marques de Sa ... [et al.] |
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Pubbl/distr/stampa |
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Berlin ; ; New York, : Springer, c2013 |
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ISBN |
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Edizione |
[1st ed. 2013.] |
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Descrizione fisica |
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1 online resource (XVIII, 262 p.) |
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Collana |
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Studies in computational intelligence, , 1860-949X ; ; 420 |
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Altri autori (Persone) |
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SaJ. P. Marques de <1946-> |
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Disciplina |
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Soggetti |
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Machine learning |
Computational learning theory |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Introduction -- Continuous Risk Functionals -- MEE with Continuous Errors -- MEE with Discrete Errors -- EE-Inspired Risks -- Applications. |
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Sommario/riassunto |
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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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