1. Introduction

2. Data  
2.1. The VVV ESO Public Survey  
2.2. Light Curve Extraction and Pre-processing  
2.3. Training Sets  
2.4. Measuring Classifier Performance  

3. Methods  
3.1. Period Estimation  
3.2. Harmonic Model Light Curve Fit  
3.3. Outlier and Poor Light-Curve Rejection  
3.4. Feature Extraction  
3.5. Choice of Classifier  
3.6. Choice of Aperture for Photometry  
3.7. Feature Selection  
3.8. Sensitivity to Training Set Choice  
3.9. Final Classifier  

4. Performance on Independent Datasets  
4.1. RR ab in 2MASS-GC 02 and Terzan 10  
4.2. RR ab in the Outer Bulge Area of the VVV  

5. Summary and Conclusions