Overview
- Presents the principal techniques of data mining with particular emphasis on explaining and motivating the techniques used
- Focuses on developing an understanding of the basic algorithms and an awareness of their strengths and weaknesses
- Readers are not required to have a strong mathematical or statistical background
- Can be used as a textbook and also for self-study
- Includes supplementary material: sn.pub/extras
Part of the book series: Undergraduate Topics in Computer Science (UTICS)
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About this book
Data Mining, the automatic extraction of implicit and potentially useful information from data, is increasingly used in commercial, scientific and other application areas.
This book explains and explores the principal techniques of Data Mining: for classification, generation of association rules and clustering. It is written for readers without a strong background in mathematics or statistics and focuses on detailed examples and explanations of the algorithms given. This should prove of value to readers of all kinds, from those whose only use of data mining techniques will be via commercial packages right through to academic researchers.
This book aims to help the general reader develop the necessary understanding to use commercial data mining packages discriminatingly, as well as enabling the advanced reader to understand or contribute to future technical advances in the field. Each chapter has practical exercises to enable readers to check their progress. A full glossary of technical terms used is included.
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Table of contents (15 chapters)
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Front Matter
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Back Matter
Authors and Affiliations
Bibliographic Information
Book Title: Principles of Data Mining
Authors: Max Bramer
Series Title: Undergraduate Topics in Computer Science
DOI: https://doi.org/10.1007/978-1-84628-766-4
Publisher: Springer London
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag London 2007
eBook ISBN: 978-1-84628-766-4Published: 06 March 2007
Series ISSN: 1863-7310
Series E-ISSN: 2197-1781
Edition Number: 1
Number of Pages: X, 344
Number of Illustrations: 200 b/w illustrations
Topics: Data Structures and Information Theory, Theory of Computation, Information Storage and Retrieval, Database Management, Artificial Intelligence, Programming Techniques