ISBN: 9783642261251 - automating the design of data mining algorithms: an evolutionary computation approach (natural computing series) (7 resultados)

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  • Idioma: Inglés

    Editorial: Springer, 2012

    3642261256 / 9783642261251

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Data mining is a very active research area with many successful real-world app- cations. It consists of a set of concepts and methods used to extract interesting or useful knowledge (or patterns) from real-world datasets, providing valuable support for decision making in industry, business, government, and science. Although there are already many types of data mining algorithms available in the literature, it is still dif cult for users to choose the best possible data mining algorithm for their particular data mining problem. In addition, data mining al- rithms have been manually designed; therefore they incorporate human biases and preferences. This book proposes a new approach to the design of data mining algorithms. - stead of relying on the slow and ad hoc process of manual algorithm design, this book proposes systematically automating the design of data mining algorithms with an evolutionary computation approach. More precisely, we propose a genetic p- gramming system (a type of evolutionary computation method that evolves c- puter programs) to automate the design of rule induction algorithms, a type of cl- si cation method that discovers a set of classi cation rules from data. We focus on genetic programming in this book because it is the paradigmatic type of machine learning method for automating the generation of programs and because it has the advantage of performing a global search in the space of candidate solutions (data mining algorithms in our case), but in principle other types of search methods for this task could be investigated in the future.…

  • Idioma: Inglés

    Editorial: Springer-Verlag New York Inc, 2012

    3642261256 / 9783642261251

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    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

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    EUR 157,23

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    Paperback. Condición: Brand New. 2010 edition. 200 pages. 9.25x6.10x0.46 inches. In Stock.

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    Idioma: Inglés

    Editorial: Springer, 2012

    3642261256 / 9783642261251

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    Librería: preigu, Osnabrück, Alemaniapreigu

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    Taschenbuch. Condición: Neu. Automating the Design of Data Mining Algorithms | An Evolutionary Computation Approach | Gisele L. Pappa (u. a.) | Taschenbuch | Natural Computing Series | xiii | Englisch | 2012 | Springer | EAN 9783642261251 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

  • Idioma: Inglés

    Editorial: Springer, 2012

    3642261256 / 9783642261251

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

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

  • Idioma: Inglés

    Editorial: Springer Berlin Heidelberg Mrz 2012, 2012

    3642261256 / 9783642261251

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    EUR 106,99

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    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Data mining is a very active research area with many successful real-world app- cations. It consists of a set of concepts and methods used to extract interesting or useful knowledge (or patterns) from real-world datasets, providing valuable support for decision making in industry, business, government, and science. Although there are already many types of data mining algorithms available in the literature, it is still dif cult for users to choose the best possible data mining algorithm for their particular data mining problem. In addition, data mining al- rithms have been manually designed; therefore they incorporate human biases and preferences. This book proposes a new approach to the design of data mining algorithms. - stead of relying on the slow and ad hoc process of manual algorithm design, this book proposes systematically automating the design of data mining algorithms with an evolutionary computation approach. More precisely, we propose a genetic p- gramming system (a type of evolutionary computation method that evolves c- puter programs) to automate the design of rule induction algorithms, a type of cl- si cation method that discovers a set of classi cation rules from data. We focus on genetic programming in this book because it is the paradigmatic type of machine learning method for automating the generation of programs and because it has the advantage of performing a global search in the space of candidate solutions (data mining algorithms in our case), but in principle other types of search methods for this task could be investigated in the future. 204 pp. Englisch.…

  • Idioma: Inglés

    Editorial: Springer Berlin Heidelberg, 2012

    3642261256 / 9783642261251

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    Librería: moluna, Greven, Alemaniamoluna

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    EUR 92,27

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    Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book proposes a different goal for evolutionary algorithms in data mining: to automate the design of a data mining algorithm, rather than just optimize its parameters.Data mining is a very active research area with many successful real-world.…

  • Idioma: Inglés

    Editorial: Springer Mär 2012, 2012

    3642261256 / 9783642261251

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    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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    EUR 106,99

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    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Data mining is a very active research area with many successful real-world app- cations. It consists of a set of concepts and methods used to extract interesting or useful knowledge (or patterns) from real-world datasets, providing valuable support for decision making in industry, business, government, and science. Although there are already many types of data mining algorithms available in the literature, it is still dif cult for users to choose the best possible data mining algorithm for their particular data mining problem. In addition, data mining al- rithms have been manually designed; therefore they incorporate human biases and preferences. This book proposes a new approach to the design of data mining algorithms. - stead of relying on the slow and ad hoc process of manual algorithm design, this book proposes systematically automating the design of data mining algorithms with an evolutionary computation approach. More precisely, we propose a genetic p- gramming system (a type of evolutionary computation method that evolves c- puter programs) to automate the design of rule induction algorithms, a type of cl- si cation method that discovers a set of classi cation rules from data. We focus on genetic programming in this book because it is the paradigmatic type of machine learning method for automating the generation of programs and because it has the advantage of performing a global search in the space of candidate solutions (data mining algorithms in our case), but in principle other types of search methods for this task could be investigated in the future.Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg 204 pp. Englisch.…