Understanding Using Rough Set by Raza Muhammad (39 results)
- Hardcover
Seller: SpringBooks, Berlin, GermanySpringBooks
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- Softcover
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- Softcover
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- Softcover
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Condition: New. pp. XVI, 236 147 illus., 27 illus. in color. 2nd ed. 2019 edition NO-PA16APR2015-KAP.
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- Hardcover
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- Hardcover
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- Hardcover
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- Softcover
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More images- Softcover
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Taschenbuch. Condition: Neu. Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications | Muhammad Summair Raza (u. a.) | Taschenbuch | xvi | Englisch | 2020 | Springer | EAN 9789813291683 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen…[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
- Softcover
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- Softcover
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a comprehensive introduction to rough set-based feature selection. Rough set theory, first proposed by Zdzislaw Pawlak in 1982, continues to evolve. Concerned with the classification and analysis of imprecise or uncertain informa…tion and knowledge, it has become a prominent tool for data analysis, and enables the reader to systematically study all topics in rough set theory (RST) including preliminaries, advanced concepts, and feature selection using RST. The book is supplemented with an RST-based API library that can be used to implement several RST concepts and RST-based feature selection algorithms.The book provides an essential reference guide for students, researchers, and developers working in the areas of feature selection, knowledge discovery, and reasoning with uncertainty, especially those who are working in RST and granular computing. The primary audience of this book is the research community using rough set theory (RST) to perform feature selection (FS) on large-scale datasets in various domains. However, any community interested in feature selection such as medical, banking, and finance can also benefit from the book. This second edition also covers the dominance-based rough set approach and fuzzy rough sets. The dominance-based rough set approach (DRSA) is an extension of the conventional rough set approach and supports the preference order using the dominance principle. In turn, fuzzy rough sets are fuzzy generalizations of rough sets. An API library for the DRSA is also provided with the second edition of the book.
- Hardcover
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More images- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: Neu. Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications | Muhammad Summair Raza (u. a.) | Taschenbuch | xiii | Englisch | 2018 | Springer | EAN 9789811352782 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juerge…n[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
- Hardcover
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- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The book will provide:1) In depth explanation of rough set theory along with examples of the concepts.2) Detailed discussion on idea of feature selection.3) Details of various representative and state of the art feature selection techniques along w…ith algorithmic explanations.4) Critical review of state of the art rough set based feature selection methods covering strength and weaknesses of each.5) In depth investigation of various application areas using rough set based feature selection.6) Complete Library of Rough Set APIs along with complexity analysis and detailed manual of using APIs7) Program files of various representative Feature Selection algorithms along with explanation of each.The book will be a complete and self-sufficient source both for primary and secondary audience. Starting from basic concepts to state-of-the art implementation, it will be a constant source of help both for practitioners and researchers. Book will provide in-depth explanation of concepts supplemented with working examples to help in practical implementation. As far as practical implementation is concerned, the researcher/practitioner can fully concentrate on his/her own work without any concern towards implementation of basic RST functionality. Providing complexity analysis along with full working programs will further simplify analysis and comparison of algorithms.
- Hardcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condition: New. pp. XVI, 236 147 illus., 27 illus. in color. 2nd ed. 2019 edition NO-PA16APR2015-KAP.
- Hardcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a comprehensive introduction to rough set-based feature selection. Rough set theory, first proposed by Zdzislaw Pawlak in 1982, continues to evolve. Concerned with the classification and analysis of imprecise or uncertain information an…d knowledge, it has become a prominent tool for data analysis, and enables the reader to systematically study all topics in rough set theory (RST) including preliminaries, advanced concepts, and feature selection using RST. The book is supplemented with an RST-based API library that can be used to implement several RST concepts and RST-based feature selection algorithms.The book provides an essential reference guide for students, researchers, and developers working in the areas of feature selection, knowledge discovery, and reasoning with uncertainty, especially those who are working in RST and granular computing. The primary audience of this book is the research community using rough set theory (RST) to perform feature selection (FS) on large-scale datasets in various domains. However, any community interested in feature selection such as medical, banking, and finance can also benefit from the book. This second edition also covers the dominance-based rough set approach and fuzzy rough sets. The dominance-based rough set approach (DRSA) is an extension of the conventional rough set approach and supports the preference order using the dominance principle. In turn, fuzzy rough sets are fuzzy generalizations of rough sets. An API library for the DRSA is also provided with the second edition of the book.
- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Hardcover. Condition: Brand New. 2nd edition. 254 pages. 9.25x6.10x0.90 inches. In Stock.
- Hardcover
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- Hardcover
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- Softcover
- Print on Demand
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- Softcover
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- Hardcover
- Print on Demand
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- Softcover
- Print on Demand
Seller: moluna, Greven, Germanymoluna
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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a comprehensive introduction to rough set-based feature selectionEnables the reader to systematically study all topics in rough set theory (RST)The book provides an essential referenc…e guide for students, researchers, and developers w.
- Softcover
- Print on Demand
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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Condition: New. Print on Demand pp. XVI, 236 147 illus., 27 illus. in color.
- Softcover
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Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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Condition: New. PRINT ON DEMAND pp. XVI, 236 147 illus., 27 illus. in color.
