R and Data Mining: Examples and Case Studies

This book guides R users into data mining and helps data miners who use R in their work. It provides a how-to method using R for data mining applications from academia to industry. It

• Presents an introduction into using R for data mining applications, covering most popular data mining techniques
• Provides code examples and data so that readers can easily learn the techniques
• Features case studies in real-world applications to help readers apply the techniques in their work and studies

The R code and data for the book are provided at the RDataMining.com website.

The book  helps researchers in the field of data mining, postgraduate students who are interested in data mining, and data miners and analysts from industry. For the many universities that have courses on data mining, this book is an invaluable reference for students studying data mining and its related subjects. In addition, it is a useful resource for anyone involved in industrial training courses on data mining and analytics. The concepts in this book help readers as R becomes increasingly popular for data mining applications.

Table of Contents

Chapter 1. Introduction
Chapter 2. Data Import and Export
Chapter 3. Data Exploration
Chapter 4. Decision Trees and Random Forest
Chapter 5. Regression
Chapter 6. Clustering
Chapter 7. Outlier Detection
Chapter 8. Time Series Analysis and Mining
Chapter 9. Association Rules
Chapter 10. Text Mining
Chapter 11. Social Network Analysis
Chapter 12. Case Study I: Analysis and Forecasting of House Price Indices
Chapter 13. Case Study II: Customer Response Prediction and Profit Optimization
Chapter 14. Case Study III: Predictive Modeling of Big Data with Limited Memory
Chapter 15. Online Resources