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1
Posted: February 14th, 2008, 10:01am CET

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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Posted: February 27th, 2008, 8:01am CET by admin
Hardcover: 720 pages
Publisher: Lawrence Erlbaum; 1 edition (April 1, 2003)
Language: English
ISBN-10: 0805840818
ISBN-13: 978-0805840810
Created with the input of a distinguished International Board of the foremost authorities in data mining from academia and industry, The Handbook of Data Mining presents comprehensive coverage of data mining concepts and techniques. Algorithms, methodologies, management issues, and tools are all illustrated through engaging examples and real-world applications to ease understanding of the materials.
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