Data Mining Applications with R

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Database Management, General Computing
Cover of the book Data Mining Applications with R by Yanchang Zhao, Yonghua Cen, Elsevier Science
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Author: Yanchang Zhao, Yonghua Cen ISBN: 9780124115200
Publisher: Elsevier Science Publication: November 26, 2013
Imprint: Academic Press Language: English
Author: Yanchang Zhao, Yonghua Cen
ISBN: 9780124115200
Publisher: Elsevier Science
Publication: November 26, 2013
Imprint: Academic Press
Language: English

Data Mining Applications with R is a great resource for researchers and professionals to understand the wide use of R, a free software environment for statistical computing and graphics, in solving different problems in industry. R is widely used in leveraging data mining techniques across many different industries, including government, finance, insurance, medicine, scientific research and more. This book presents 15 different real-world case studies illustrating various techniques in rapidly growing areas. It is an ideal companion for data mining researchers in academia and industry looking for ways to turn this versatile software into a powerful analytic tool.

R code, Data and color figures for the book are provided at the RDataMining.com website.

  • Helps data miners to learn to use R in their specific area of work and see how R can apply in different industries
  • Presents various case studies in real-world applications, which will help readers to apply the techniques in their work
  • Provides code examples and sample data for readers to easily learn the techniques by running the code by themselves
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Data Mining Applications with R is a great resource for researchers and professionals to understand the wide use of R, a free software environment for statistical computing and graphics, in solving different problems in industry. R is widely used in leveraging data mining techniques across many different industries, including government, finance, insurance, medicine, scientific research and more. This book presents 15 different real-world case studies illustrating various techniques in rapidly growing areas. It is an ideal companion for data mining researchers in academia and industry looking for ways to turn this versatile software into a powerful analytic tool.

R code, Data and color figures for the book are provided at the RDataMining.com website.

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