Articles liés à Mathematical Tools for Data Mining: Set Theory, Partial...
Synopsis
Data mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book. Topics include partially ordered sets, combinatorics, general topology, metric spaces, linear spaces, graph theory. To motivate the reader a significant number of applications of these mathematical tools are included ranging from association rules, clustering algorithms, classification, data constraints, logical data analysis, etc. The book is intended as a reference for researchers and graduate students. The current edition is a significant expansion of the first edition. We strived to make the book self-contained and only a general knowledge of mathematics is required. More than 700 exercises are included and they form an integral part of the material. Many exercises are in reality supplemental material and their solutions are included.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Présentation de l'éditeur
This book integrates the mathematics of data mining with its applications, offering the reader a reference to the mathematical tools required for data mining. Dedicated to the study of set-theoretical foundations of data mining, this book is focused on set theory and several closely related areas: partially ordered sets and lattice theory, metric spaces and combinatorics. The book is structured into 4 parts and presents a comprehensive discussion of the subject. Features and topics include: - Study of functions and relations, - Applications are provided throughout, - Presents graphs and hypergraphs, - Covers partially ordered sets, lattices and Boolean algebras, - Finite partially ordered sets, - Focuses on metric spaces, - Includes combinatorics, - Discusses the theory of the Vapnik-Chervonenkis dimension of collections of sets. Intended as a reference for the working data miner and researchers, a good knowledge of calculus is required to make the best use of this book, which will prove a useful reference.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
- ÉditeurSpringer London Ltd
- Date d'édition2014
- ISBN 10 1447164067
- ISBN 13 9781447164067
- ReliureRelié
- Langueanglais
- Numéro d'édition2
- Nombre de pages831
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Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing)
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Springer, 2014
ISBN 10 : 1447164067
ISBN 13 : 9781447164067
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Mathematical Tools for Data Mining
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Mathematical Tools for Data Mining
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Springer London Apr 2014, 2014
ISBN 10 : 1447164067
ISBN 13 : 9781447164067
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Data mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book. Topics include partially ordered sets, combinatorics, general topology, metric spaces, linear spaces, graph theory. To motivate the reader a significant number of applications of these mathematical tools are included ranging from association rules, clustering algorithms, classification, data constraints, logical data analysis, etc. The book is intended as a reference for researchers and graduate students. The current edition is a significant expansion of the first edition. We strived to make the book self-contained and only a general knowledge of mathematics is required. More than 700 exercises are included and they form an integral part of the material. Many exercises are in reality supplemental material and their solutions are included. 844 pp. Englisch. N° de réf. du vendeur 9781447164067
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Mathematical Tools for Data Mining
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Mathematical Tools for Data Mining
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
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Etat : New. pp. xi + 831. N° de réf. du vendeur 1897863757
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Mathematical Tools for Data Mining : Set Theory, Partial Orders, Combinatorics
Edité par
Springer London, Springer London, 2014
ISBN 10 : 1447164067
ISBN 13 : 9781447164067
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Data mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book. Topics include partially ordered sets, combinatorics, general topology, metric spaces, linear spaces, graph theory. To motivate the reader a significant number of applications of these mathematical tools are included ranging from association rules, clustering algorithms, classification, data constraints, logical data analysis, etc. The book is intended as a reference for researchers and graduate students. The current edition is a significant expansion of the first edition. We strived to make the book self-contained and only a general knowledge of mathematics is required. More than 700 exercises are included and they form an integral part of the material. Many exercises are in reality supplemental material and their solutions are included. N° de réf. du vendeur 9781447164067
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Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing)
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Mathematical Tools for Data Mining
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Focuses on mathematical topics of immediate interest to data mining and machine learningThe mathematics is illustrated by significant applications ranging from association rules, clustering algorithms, classification, data constraints, logical . N° de réf. du vendeur 4185646
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Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing)
Edité par
Springer, 2014
ISBN 10 : 1447164067
ISBN 13 : 9781447164067
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