1. Feature Engineering Studio Special Session September 25, 2013

2. RapidMiner 5.3 Data file and rapidminer xml file are on course webpage

3. Look at data

4. Look at process step-by-step

5. Build classifier

6. Goodness Criteria Kappa AUC (Warning!) Accuracy (Warning!) Precision Recall

7. Turn cross-validation off

8. Other types of cross-validation Student-level cross-validation Population-level cross-validation Content-level cross-validation When you use these….

9. Setting up other types of cross-validation BatchXValidation SetRole

10. CompleteFeatureGeneration

11. RemoveCorrelatedFeatures

12. Other Classification Algorithms W-J48 W-JRip W-KStar

13. Set up a Regression

14. Regression Algorithms Linear Regression W-RepTree W-M5P Neural Networks Support Vector Machines

15. Goodness Criteria Correlation RMSE/MAD

16. Many other things RapidMiner can do… These are just two types of common prediction models

17. For a broader overview of prediction modeling… Come to next week’s special session

18. Questions? Concerns?