1. Core Methods in Educational Data Mining HUDK4050 Fall 2014

2. Assignment 2C

3. What tools did you use? Packages (i.e. Excel) Features of Packages (i.e. Pivot Tables)

4. Let’s go back to the list of features from the last class As I read features off If you used this feature (or something very similar), raise your hand

5. For the features that got used Did it end up in your final model? In what direction? Does this match the class’s overall intuition?

6. Who created a feature not discussed in Monday’s class? What feature? Did it improve your model?

7. Let’s… Go through how you created features – Actually do it… Re-create it in real-time, or show us your code… We’ll have multiple volunteers – One feature per customer, please…

8. Was feature engineering beneficial?

9. Other questions or comments about assignment?

10. Textbook

11. Automated Feature Generation What are the advantages of automated feature generation, as compared to feature engineering? What are the disadvantages?

12. Automated Feature Selection What are the advantages of automated feature selection, as compared to having a domain expert decide? (as in Sao Pedro paper from Monday) What are the disadvantages?

13. A connection to make

14. Correlation filtering Eliminating collinearity in statistics In this case, increasing interpretability and reducing over-fitting go together – At least to some positive degree

15. Outer-loop forward selection What are the advantages and disadvantages to doing this?

16. Knowledge Engineering What is knowledge engineering?

17. Knowledge Engineering What is the difference between knowledge engineering and EDM?

18. Knowledge Engineering What is the difference between good knowledge engineering and bad knowledge engineering?

19. Knowledge Engineering What is the difference between (good) knowledge engineering and EDM? What are the advantages and disadvantages of each?

20. How can they be integrated?

21. FCBF: What Variables will be kept? (Cutoff = 0.65) What variables emerge from this table? GHIJKL Predicted G.7.8.4.3.72 H.8.7.6.5.38 I.8.3.4.82 J.8.1.75 K.5.65 L.42

22. Other questions, comments, concerns about textbook?

23. If you enjoyed today’s class… Next fall, I’ll be offering a Feature Engineering Design Studio course… Learn the feature engineering process in detail Create a model important to your research Submit a journal paper

24. And now for something completely different…

25. Assignment B3 Bayesian Knowledge Tracing Any questions?

26. Next Class Wednesday, October 8 Feature Engineering – How Baker, R.S. (2014) Big Data and Education. Ch. 3, V4, V5. vlookup Tutorial 1 vlookup Tutorial 2 Pivot Table Tutorial 1 Pivot Table Tutorial 2

27. The End