R Data Mining

Table of Contents

1. Why to Choose R for Your Data Mining and Where to Start
2. A First Primer on Data Mining Analysing Your Bank Account Data
3. The Data Mining Process - CRISP-DM Methodology
4. Keeping the House Clean
5. How to Address a Data Mining Problem
6. Looking into Your Data Eyes
7. Our First Guess
8. A Gentle Introduction to Model Performance Evaluation
9. Don't Give up
10. Addressing the Problem from Another Perspective Through Classification Models
11. The Final Clash
12. Looking for the Culprit
13. Sharing Your Stories with Your Stakeholders through R Markdown
14. Epilogue
15. Appendix A: Dealing with Dates, Relative Paths and Functions