This book guides users into R data mining and data miners who use R in their work. It provides a method of how to use R for data mining applications from academia to industry. It Presents an introduction on using R for data mining applications, including data mining techniques, the most common Provides code examples and data so that readers can easily learn the techniques Features case studies of practical applications to help readers apply the techniques in work and learning
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
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