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Granular Computing in Decision Approximation: An Application of Rough Mereology (Intelligent Systems Reference Library, 77) - Hardcover
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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Review
“The book provides an extended presentation of granular computing, focusing on applications in classification/decision theory. ... the book is intended to students and researchers interested in granular computing.” (Florin Gorunescu, zbMATH 1314.68006, 2015)
"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date2015
- ISBN 10 3319128795
- ISBN 13 9783319128795
- BindingHardcover
- LanguageEnglish
- Number of pages467
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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 (Intelligent Systems Reference Library, 77)
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Granular Computing in Decision Approximation
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ISBN 10: 3319128795
ISBN 13: 9783319128795
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Buch. Condition: 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. Seller Inventory # 9783319128795
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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
Published by
Springer International Publishing, 2015
ISBN 10: 3319128795
ISBN 13: 9783319128795
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Buch. Condition: 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. Seller Inventory # 9783319128795
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Granular Computing in Decision Approximation
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ISBN 10: 3319128795
ISBN 13: 9783319128795
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Condition: 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 . Seller Inventory # 24353837
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Granular Computing in Decision Approximation: An Application of Rough Mereology
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Hardcover. Condition: Brand New. 2015 edition. 470 pages. 9.50x6.25x1.25 inches. In Stock. Seller Inventory # x-3319128795
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