Isbn: 9783319366210 - granular computing in decision approximation: an application of rough mereology: 77 (12 risultati)

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  • Lingua: Inglese

    Editore: Springer, 2016

    3319366211 / 9783319366210

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    Condizione: New. In English.

  • Lingua: Inglese

    Editore: Springer, 2016

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    Condizione: New. pp. 452.

  • Lingua: Inglese

    Editore: Springer, 2016

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    Taschenbuch. Condizione: Neu. Granular Computing in Decision Approximation | An Application of Rough Mereology | Lech Polkowski (u. a.) | Taschenbuch | Intelligent Systems Reference Library | xv | Englisch | 2016 | Springer | EAN 9783319366210 | 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 International Publishing, 2016

    3319366211 / 9783319366210

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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 - This book presents a study in knowledge discovery in data with knowledge understood as a set of relations among objects and their properties. Relations in this case are implicative decision rules and the paradigm in which they are induced is that of computing with granules defined by rough inclusions, the latter introduced and studied within rough mereology, the fuzzified version of mereology. In this book basic classes of rough inclusions are defined and based on them methods for inducing granular structures from data are highlighted. The resulting granular structures are subjected to classifying algorithms, notably k-nearest neighbors and bayesian classifiers.Experimental results are given in detail both in tabular and visualized form for fourteen data sets from UCI data repository. A striking feature of granular classifiers obtained by this approach is that preserving the accuracy of them on original data, they reduce substantially the size of the granulated data set as well as the set of granular decision rules. This feature makes the presented approach attractive in cases where a small number of rules providing a high classification accuracy is desirable. As basic algorithms used throughout the text are explained and illustrated with hand examples, the book may also serve as a textbook.

  • Lingua: Inglese

    Editore: Springer-Verlag New York Inc, 2016

    3319366211 / 9783319366210

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    Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books

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    Paperback. Condizione: Brand New. reprint edition. 468 pages. 9.25x6.10x1.06 inches. In Stock.

  • Lingua: Inglese

    Editore: Springer, 2016

    3319366211 / 9783319366210

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    Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books

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    Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

  • Lingua: Inglese

    Editore: Springer International Publishing Okt 2016, 2016

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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 -This book presents a study in knowledge discovery in data with knowledge understood as a set of relations among objects and their properties. Relations in this case are implicative decision rules and the paradigm in which they are induced is that of computing with granules defined by rough inclusions, the latter introduced and studied within rough mereology, the fuzzified version of mereology. In this book basic classes of rough inclusions are defined and based on them methods for inducing granular structures from data are highlighted. The resulting granular structures are subjected to classifying algorithms, notably k-nearest neighbors and bayesian classifiers.Experimental results are given in detail both in tabular and visualized form for fourteen data sets from UCI data repository. A striking feature of granular classifiers obtained by this approach is that preserving the accuracy of them on original data, they reduce substantially the size of the granulated data set as well as the set of granular decision rules. This feature makes the presented approach attractive in cases where a small number of rules providing a high classification accuracy is desirable. As basic algorithms used throughout the text are explained and illustrated with hand examples, the book may also serve as a textbook. 468 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer, 2016

    3319366211 / 9783319366210

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

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

  • Lingua: Inglese

    Editore: Springer International Publishing, 2016

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    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Recent research on Granular Computing in Decision ApproximationFully develops the topic of granular computing in classifier synthesisPresents applied algorithms which are illustrated with simple hand examplesThis book presents a .

  • Lingua: Inglese

    Editore: Springer, 2016

    3319366211 / 9783319366210

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    Da: Majestic Books, Hounslow, Regno UnitoMajestic Books

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    Condizione: New. Print on Demand pp. 452.

  • Lingua: Inglese

    Editore: Springer, 2016

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    Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios

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    Condizione: New. PRINT ON DEMAND pp. 452.

  • Lingua: Inglese

    Editore: Springer, Birkhäuser Okt 2016, 2016

    3319366211 / 9783319366210

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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 -This book presents a study in knowledge discovery in data with knowledge understood as a set of relations among objects and their properties. Relations in this case are implicative decision rules and the paradigm in which they are induced is that of computing with granules defined by rough inclusions, the latter introduced and studiedwithin rough mereology, the fuzzified version of mereology. In this book basic classes of rough inclusions are defined and based on them methods for inducing granular structures from data are highlighted. The resulting granular structures are subjected to classifying algorithms, notably k¿nearest neighbors and bayesian classifiers.Experimental results are given in detail both in tabular and visualized form for fourteen data sets from UCI data repository. A striking feature of granular classifiers obtained by this approach is that preserving the accuracy of them on original data, they reducesubstantially the size of the granulated data set as well as the set of granular decision rules. This feature makes the presented approach attractive in cases where a small number of rules providing a high classification accuracy is desirable. As basic algorithms used throughout the text are explained and illustrated with hand examples, the book may also serve as a textbook.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 468 pp. Englisch.