Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing)
Simovici, Dan A., Djeraba, Chabane
ISBN 10: 1447164067 ISBN 13: 9781447164067
Verlag: Springer, 2014
Neu
Hardcover
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Beschreibung
Beschreibung:
Mathematical Tools for Data Mining Series: Advanced Information and Knowledge Processing. Num Pages: 831 pages, 93 black & white illustrations, 8 black & white tables, biography. BIC Classification: PBD; PBKS; UNF; UYA. Category: (P) Professional & Vocational. Dimension: 164 x 239 x 49. Weight in Grams: 1394. . 2014. 2nd ed. 2014. Hardcover. . . . . Books ship from the US and Ireland. Bestandsnummer des Verkäufers V9781447164067
Inhaltsangabe:
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.
Von der hinteren Coverseite:
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.
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Bibliografische Details
Titel: Mathematical Tools for Data Mining: Set ...
Verlag: Springer
Erscheinungsdatum: 2014
Einband: Hardcover
Zustand: New
Auflage: 2. Auflage
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Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing)
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Zustand: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions. Artikel-Nr. Z1-F-072-00417
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Mathematical Tools for Data Mining
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Zustand: New. pp. xi + 831 93 Illus. Artikel-Nr. 94566296
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Mathematical Tools for Data Mining : Set Theory, Partial Orders, Combinatorics
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Springer London, Springer London, 2014
ISBN 10: 1447164067
ISBN 13: 9781447164067
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Buch. Zustand: 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. Artikel-Nr. 9781447164067
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Mathematical Tools for Data Mining
Verlag:
Springer London, Springer London Apr 2014, 2014
ISBN 10: 1447164067
ISBN 13: 9781447164067
Neu
Hardcover
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Buch. Zustand: Neu. 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 844 pp. Englisch. Artikel-Nr. 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: Set Theory, Partial Orders, Combinatorics
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Hardcover. Zustand: Brand New. 2nd edition. 831 pages. 9.00x6.00x2.00 inches. In Stock. Artikel-Nr. x-1447164067
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