Isbn: 9783642268588 - meta-learning in computational intelligence: 358 (11 risultati)

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  • Lingua: Inglese

    Editore: Springer, 2013

    3642268587 / 9783642268588

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    Condizione: New. In English.

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    Lingua: Inglese

    Editore: Springer, 2013

    3642268587 / 9783642268588

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    Taschenbuch. Condizione: Neu. Meta-Learning in Computational Intelligence | Norbert Jankowski (u. a.) | Taschenbuch | Studies in Computational Intelligence | ix | Englisch | 2013 | Springer | EAN 9783642268588 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Lingua: Inglese

    Editore: Springer, 2013

    3642268587 / 9783642268588

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    Da: Books Puddle, New York, NY, U.S.A.Books Puddle

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    EUR 292,28

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    Condizione: New. pp. 372.

  • Lingua: Inglese

    Editore: Springer, 2013

    3642268587 / 9783642268588

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    Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books

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    Paperback. Condizione: Brand New. 2011 edition. 372 pages. 9.25x6.10x0.88 inches. In Stock.

  • Lingua: Inglese

    Editore: Springer, 2013

    3642268587 / 9783642268588

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process. This is where algorithms that learn how to learnl come to rescue. Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn. This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field.

  • Lingua: Inglese

    Editore: Springer, 2013

    3642268587 / 9783642268588

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    Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand

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    EUR 182,29

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    Condizione: new. Questo è un articolo print on demand.

  • Lingua: Inglese

    Editore: Springer Berlin Heidelberg Aug 2013, 2013

    3642268587 / 9783642268588

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process. This is where algorithms that learn how to learnl come to rescue. Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn. This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field. 372 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer Berlin Heidelberg, 2013

    3642268587 / 9783642268588

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    Da: moluna, Greven, Germaniamoluna

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    EUR 197,62

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    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Recent research in Meta-learning in computational intelligence Presents new Developments and Trends in Computational Intelligence and Learning Written by leading experts in the fieldComputational Intelligence (CI) community has de.

  • Lingua: Inglese

    Editore: Springer, Springer Aug 2013, 2013

    3642268587 / 9783642268588

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    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process. This is where algorithms that learn how to learnl come to rescue. Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn. This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 372 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer, 2013

    3642268587 / 9783642268588

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    Da: Majestic Books, Hounslow, Regno UnitoMajestic Books

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    Condizione: New. Print on Demand pp. 372 1237 Illus. (76 Col.).

  • Lingua: Inglese

    Editore: Springer, 2013

    3642268587 / 9783642268588

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    Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios

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    EUR 310,01

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    Condizione: New. PRINT ON DEMAND pp. 372.