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R and data mining : examples and case studies

Author: Yanchang Zhao
Publisher: [S.l.] : Academic Press, ©2013.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
This book introduces using R for data mining. Data mining techniques are widely used in government agencies, banks, insurance, retail, telecom, medicine and research. Recently, there is an increasing tendency to do data mining with R, a free software environment for statistical computing and graphics. According to a poll by KDnuggets.com in early 2011, R is the 2nd popular tool for data mining work. By introducing  Read more...
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Genre/Form: Electronic books
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Yanchang Zhao
OCLC Number: 821039505
Description: 1 online resource
Responsibility: Yanchang Zhao.

Abstract:

Introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. This book provides practical methods for using  Read more...

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schema:description"This book introduces using R for data mining. Data mining techniques are widely used in government agencies, banks, insurance, retail, telecom, medicine and research. Recently, there is an increasing tendency to do data mining with R, a free software environment for statistical computing and graphics. According to a poll by KDnuggets.com in early 2011, R is the 2nd popular tool for data mining work. By introducing using R for data mining, this book will have a broad audience from both academia and industry. It targets researchers in the field of data mining, postgraduate students who are interested in data mining, and data miners and analysts from industry. For example, many universities have courses on data mining, and the proposed book will be a useful reference for students learning data mining in those courses. There are also many training courses on data mining in industry, such as training by SAS and IBM on data mining. The book will be of interest to the course learners as well. Presents an introduction into using R for data mining applications, covering most popular data mining techniques. Provides code examples and data so that readers can easily learn the techniques. Features case studies in real-world applications to help readers apply the techniques in their work."
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