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Understanding Using Rough Set by Raza Muhammad (34 results)
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![Stock image for Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications [Hardcover] Raza, Muhammad Summair and Qamar, Usman for sale by SpringBooks](https://pictures.abebooks.com/isbn/9789813291652-uk-300.jpg)
Hardcover. Condition: Very Good. 2. Auflage. Unread, some shelfwear. Immediately dispatched from Germany.
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Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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£ 85.99
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Condition: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
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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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Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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£ 106.31
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Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Condition: As New. Unread book in perfect condition.
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Understanding and Using Rough Set Based Feature Selection : Concepts, Techniques and Applications
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Condition: New. pp. 208.
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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 information 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.
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Understanding and Using Rough Set Based Feature Selection : Concepts, Techniques and Applications
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
£ 130.06
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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, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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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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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 with 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.
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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 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.
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Hardcover. Condition: Brand New. 2nd edition. 254 pages. 9.25x6.10x0.90 inches. In Stock.
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Hardcover. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Condition: new. Questo è un articolo print on demand.
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Condition: new. Questo è un articolo print on demand.
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Condition: new. Questo è un articolo print on demand.
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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 reference guide for students, researchers, and developers w.
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Condition: New. Print on Demand pp. XVI, 236 147 illus., 27 illus. in color.
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Condition: New. PRINT ON DEMAND pp. XVI, 236 147 illus., 27 illus. in color.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Complete introduction of FS and RST (including background and practical applications)In-depth analysis of state-of-the-art tools and techniques (including strong and weak points and complexity analysis of each technique).
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Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications
Language: English
Published by Springer, Springer Sep 2020, 2020
ISBN 10: 9813291680 ISBN 13: 9789813291683
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 252 pp. Englisch.
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Condition: New. Print on Demand pp. 208.
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Gebunden. 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 reference guide for students, researchers, and developers w.
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Condition: New. PRINT ON DEMAND pp. 208.
