"R and Data Mining "introduces researchers, post-graduate
students, and analysts to data mining using R, a free software
environment for statistical computing and graphics. The book
provides practical methods for using R in applications from
academia to industry to extract knowledge from vast amounts of
data. Readers 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 more.
Data mining techniques are growing in popularity in a broad
range of areas, from banking to insurance, retail, telecom,
medicine, research, and government. This book focuses on the
modeling phase of the data mining process, also addressing data
exploration and model evaluation.
With three in-depth case studies, a quick reference guide,
bibliography, and links to a wealth of online resources, "R and
Data Mining" is a valuable, practical guide to a powerful method of
Presents an introduction into using R for data mining applications,
covering most popular data mining techniquesProvides code examples
and data so that readers can easily learn the techniquesFeatures
case studies in real-world applicationsto help readers apply the
techniques in their work"
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