Data Mining Applications with R
ISBN-13:
9780124115118
ISBN-10:
012411511X
Edition:
1
Author:
Yanchang Zhao, Yonghua Cen
Publication date:
2013
Publisher:
Academic Press
Format:
Hardcover
514 pages
FREE US shipping
Book details
ISBN-13:
9780124115118
ISBN-10:
012411511X
Edition:
1
Author:
Yanchang Zhao, Yonghua Cen
Publication date:
2013
Publisher:
Academic Press
Format:
Hardcover
514 pages
Summary
Data Mining Applications with R (ISBN-13: 9780124115118 and ISBN-10: 012411511X), written by authors
Yanchang Zhao, Yonghua Cen, was published by Academic Press in 2013.
With an overall rating of 4.5 stars, it's a notable title among other
AI & Machine Learning
(Databases & Big Data, Programming Languages, Computer Science) books. You can easily purchase or rent Data Mining Applications with R (Hardcover) from BooksRun,
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Description
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. The book
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. The book
- 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
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