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Synopsis
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.
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Granular Computing in Decision Approximation: An Application of Rough Mereology (Intelligent Systems Reference Library, 77, Band 77)
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Springer, 2015
ISBN 10 : 3319128795
ISBN 13 : 9783319128795
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hardcover. Etat : Gut. 467 Seiten; 9783319128795.3 Gewicht in Gramm: 1. N° de réf. du vendeur 962805
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Granular Computing in Decision Approximation
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Springer International Publishing, 2015
ISBN 10 : 3319128795
ISBN 13 : 9783319128795
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Gebunden. Etat : 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 . N° de réf. du vendeur 24353837
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Granular Computing in Decision Approximation: An Application of Rough Mereology (Intelligent Systems Reference Library, 77)
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Granular Computing in Decision Approximation : An Application of Rough Mereology
Edité par
Springer International Publishing, 2015
ISBN 10 : 3319128795
ISBN 13 : 9783319128795
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Buch. Etat : 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. N° de réf. du vendeur 9783319128795
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Granular Computing in Decision Approximation
Edité par
Springer International Publishing Apr 2015, 2015
ISBN 10 : 3319128795
ISBN 13 : 9783319128795
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Buch. Etat : 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. N° de réf. du vendeur 9783319128795
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Granular Computing in Decision Approximation : An Application of Rough Mereology
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Granular Computing in Decision Approximation: An Application of Rough Mereology (Intelligent Systems Reference Library, 77)
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Granular Computing in Decision Approximation
ISBN 10 : 3319128795
ISBN 13 : 9783319128795
Neuf
Couverture rigide
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Buch. Etat : 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 GmbH, Tiergartenstr. 17, 69121 Heidelberg 468 pp. Englisch. N° de réf. du vendeur 9783319128795
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Granular Computing in Decision Approximation : An Application of Rough Mereology
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Granular Computing in Decision Approximation: An Application of Rough Mereology (Intelligent Systems Reference Library, 77)
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