Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing)

Simovici, Dan A., Djeraba, Chabane

Editore: Springer, 2008
ISBN 10: 1848002009 / ISBN 13: 9781848002005
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Riassunto:

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.

Dal retro di copertina:

The maturing of the field of data mining has brought about an increased level of mathematical sophistication. Such disciplines like topology, combinatorics, partially ordered sets and their associated algebraic structures (lattices and Boolean algebras), and metric spaces are increasingly applied in data mining research. This book presents these mathematical foundations of data mining integrated with applications to provide the reader with a comprehensive reference.

Mathematics is presented in a thorough and rigorous manner offering a detailed explanation of each topic, with applications to data mining such as frequent item sets, clustering, decision trees also being discussed. More than 400 exercises are included and they form an integral part of the material. Some of the exercises are in reality supplemental material and their solutions are included. The reader is assumed to have a knowledge of elementary analysis.

Features and topics:

? 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

This wide-ranging, thoroughly detailed volume is self-contained and intended for researchers and graduate students, and will prove an invaluable reference tool.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Dati bibliografici

Titolo: Mathematical Tools for Data Mining: Set ...
Casa editrice: Springer
Data di pubblicazione: 2008
Condizione libro: very good

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Dan A. Simovici
Editore: Springer (2008)
ISBN 10: 1848002009 ISBN 13: 9781848002005
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Descrizione libro Springer, 2008. Hardcover. Condizione libro: New. 2008. This item is printed on demand. Codice libro della libreria DADAX1848002009

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Simovici, Dan A. (Author)/ Djeraba, Chaabane (Author)
Editore: Springer (2008)
ISBN 10: 1848002009 ISBN 13: 9781848002005
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Descrizione libro Springer, 2008. Hardcover. Condizione libro: Brand New. 2008 edition. 616 pages. 9.00x6.25x1.75 inches. In Stock. Codice libro della libreria 1848002009

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Dan A. Simovici
Editore: Springer (2008)
ISBN 10: 1848002009 ISBN 13: 9781848002005
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Descrizione libro Springer, 2008. Hardcover. Condizione libro: Good. 2008. Ships with Tracking Number! INTERNATIONAL WORLDWIDE Shipping available. May not contain Access Codes or Supplements. Buy with confidence, excellent customer service!. Codice libro della libreria 1848002009

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