Mathematical Tools for Data Mining / Advanced Information and Knowledge Processing (PDF)
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),...
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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.
- Autoren: Dan A. Simovici , Chaabane Djeraba
- 2008, 2008, 615 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 1848002017
- ISBN-13: 9781848002012
- Erscheinungsdatum: 15.08.2008
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Größe: 12 MB
- Ohne Kopierschutz
- Vorlesefunktion
From the reviews:
"The book is organized into four parts, with a total of 15 chapters. Each chapter … offers numerous exercises and references for further reading. … Overall, Simovici and Djeraba’s presentation of both the theoretical grounds and the practical aspects of the various data mining methodologies is good. … The book is intended for readers who have a data mining background … . It will help this audience to improve their knowledge of how different data mining strategies operate from a mathematical standpoint." (Aris Gkoulalas-Divanis, ACM Computing Reviews, February, 2009)
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