Data Mining Applications with R
- ISBN-10
- 0124115209
- ISBN-13
- 9780124115200
- Category
- Computers
- Pages
- 514
- Language
- English
- Published
- 2013-11-26
- Publisher
- Academic Press
- Authors
- Yanchang Zhao, Yonghua Cen
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. 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
Get the book
Similar books
-
R and Data Mining: Examples and Case Studies
By Yanchang ZhaoReaders will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and ...
-
Handbook of Statistical Analysis and Data Mining Applications
By Robert Nisbet, Gary Miner, Ken YaleImhoff, C., Sousa, R., 1997. The Information Ecosystem. Part 1. DM-Review, January 27. Inmon, W., Imhoff, C., Sousa, R., 1998. Corporate Information Factory. John Wiley & Sons, New York, NY. Juran, J., 1951. Quality Control Handbook.
-
Data Mining with R: Learning with Case Studies, Second Edition
By Luis TorgoProviding an extensive update to the best-selling first edition, this new edition is divided into two parts.
-
Data Mining for Business Analytics: Concepts, Techniques and Applications in Python
By Peter C. Bruce, Galit Shmueli, Nitin R. PatelThis is the sixth version of this successful text, and the first using Python.
-
Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery
By Graham WilliamsThroughout this book the reader is introduced to the basic concepts and some of the more popular algorithms of data mining.
-
Data Mining and Business Analytics with R
By Johannes LedolterIn addition, the book presents: • A thorough discussion and extensive demonstration of the theory behind the most useful data mining tools • Illustrations of how to use the outlined concepts in real-world situations • Readily ...
-
Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner
By Peter C. Bruce, Galit Shmueli, Nitin R. PatelThe book is a perfect fit for its intended audience." – Keith McCormick, Consultant and Author of SPSS Statistics For Dummies, Third Edition and SPSS Statistics for Data Analysis and Visualization "…extremely well organized, clearly ...
-
Text Mining with R: A Tidy Approach
By David Robinson, Julia SilgeChapter 7.
-
An Introduction to Statistical Learning: with Applications in R
By Daniela Witten, Trevor Hastie, Robert TibshiraniThis book presents some of the most important modeling and prediction techniques, along with relevant applications.
-
Data Science Using Python and R
By Daniel T. Larose, Chantal D. LaroseData Science Using Python and R provides exercises at the end of every chapter, totaling over 500 exercises in the book. Readers will therefore have plenty of opportunity to test their newfound data science skills and expertise.