Data Mining Applications with R

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Academic Press, Nov 26, 2013 - Computers - 514 pages

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 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


Power Grid Data Analysis with R and Hadoop
Picturing Bayesian Classifiers A Visual Data Mining Approach to Parameters Optimization
Discovery of Emergent Issues and Controversies in Anthropology Using Text Mining Topic Modeling and Social Ne
Text Mining and Network Analysis of Digital Libraries in R
Recommender Systems in R
Response Modeling in Direct Marketing A Data MiningBased Approach for Target Selection
Caravan Insurance Customer Profile Modeling with R
Selecting Best Features for Predicting Bank Loan Default
A RealTime Property Value Index Based on Web Data
Predicting Seabed Hardness Using Random Forest in R
Supervised Classification of Images Applied to Plankton Samples Using R and Zooimage
Crime Analyses Using R
Football Mining with R
Analyzing Internet DNSSEC Traffic with R for Resolving Platform Optimization

A Choquet Integral Toolbox and Its Application in Customer Preference Analysis

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About the author (2013)

A Senior Data Mining Analyst in Australia Government since 2009.

Before joining public sector, he was an Australian Postdoctoral Fellow (Industry) in the Faculty of Engineering & Information Technology at University of Technology, Sydney, Australia. His research interests include clustering, association rules, time series, outlier detection and data mining applications and he has over forty papers published in journals and conference proceedings. He is a member of the IEEE and a member of the Institute of Analytics Professionals of Australia, and served as program committee member for more than thirty international conferences.