Statistics 315B: (Winter 2009)

 Modern Applied Statistics: Elements of Statistical Learning II

TIME:  Mon. & Wed.  3:15 - 4:30pm

 Location: Gates B3

Instructor: Jerome H. Friedman

Logistics:

• Class web page: http://www.stanford.edu/class/stats315b
• Office hour:  TBA, 134 Sequoia Hall.
• TAs: Gen Nowak (gnowak at stanford.edu, OH : TBA) & Nick Johnson (234 Sequoia, nickaj at stanford.edu, OH : TBA)
• Text: Elements of Statistical Learning. Hastie, Tibshirani & Friedman. Springer.
• Homework:
  • traditional.
  • (journal) reading assignments (with/without questions).
  • computing assignments (apply / implement methods using R - discuss results).
• Midterm: no.
• Final: likely - not sure what form.

Topics:

• Classification & regression trees (CART)    (Ch. 9)
• Multivariate adaptive regression splines (MARS)  (Ch. 9)
• Bagging  (Ch. 8)
• Boosting and additive trees (MART)  (Ch. 10)
• Neural networks  (Ch. 11)
• Prototype & near-neighbor methods  (Ch. 13)