1. Feature Engineering Studio April 13, 2015

2. Friend Features Who managed to find a friend with relevant background expertise?

3. Friend Features What features did your friends suggest? What did they discard?

4. Cross-validated goodness Each of you please list – Your full model’s cross-validated goodness – Your friend model’s cross-validated goodness What can we conclude, if anything?

5. A different approach than Sao Pedro et al. 2013 Anyone want to summarize that paper’s approach? What are the benefits of that paper’s approach? Are there any major downsides?

6. Questions? Comments?

7. Wednesday’s assignment Assignment 9 Feature Adaptation “This One’s For Nikolai Ivonavich Lobachevsky”

8. Nikolai Ivonovich Lobachevsky (by Tom Lehrer) “I will never forget the day I first met the great Lobachevsky. In one word he told me the secret of success in mathematics:”

9. Nikolai Ivonovich Lobachevsky (by Tom Lehrer) “I will never forget the day I first met the great Lobachevsky. In one word he told me the secret of success in mathematics: Plagiarize!”

10. Nikolai Ivonovich Lobachevsky (by Tom Lehrer) “I will never forget the day I first met the great Lobachevsky. In one word he told me the secret of success in mathematics: Plagiarize!” “Only be sure to always call it – please – research.”

11. To be clear… Plagiarism: bad

12. To be clear… Plagiarism: bad Borrowing ideas (and citing them): good

13. To be clear… Plagiarism: bad Borrowing ideas (and citing them): good We all clear?

14. Assignment 9 You need to find a previous paper that uses one or more features that can be potentially translated to your current analysis Find the paper Try at least one feature in your own data set

15. Assignment 9 Please be ready to discuss in class next Monday

16. Assignment 9 Be ready to discuss – The paper you drew inspiration from – Give a full citation and show us pictures of as many authors as you can find – The construct being predicted in this paper – The context/data set in this paper – The feature you decided to adapt – The feature you ended up creating – Differences between the original paper’s feature and your feature – The goodness of your feature in your data set

17. What if you can’t find a paper?

18. You can find a paper

19. What if you can’t find a paper? You can find a paper Try google scholar

20. What if you can’t find a paper? You can find a paper Try google scholar Email me – but only after you have spent at least 2 hours searching the web

21. Questions? Comments?

22. Upcoming Classes April 15: Feature Adaptation April 20: Poster Presentations April 22: No class

23. New Special Session Python May 4 During regular class time Run by Stefan and Yijun

24. Thank you!