1. Feature Engineering Studio Special Session
February 25, 2015

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 (warning!)
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 April 1 special session

18. Questions? Concerns?