Statistics 315B: (Spring 2017)

 Modern Applied Statistics: Elements of Statistical Learning II

TIME:  Tues. & Thur.  1:30 - 2:50pm

 Location: Gates B01

Instructor: Jerome H. Friedman

Logistics:

• Class web page: http://coursework.stanford.edu/portal/site/Sp16-STATS-315B-01
• Office hour:  Thursday 3 - 4pm, 134 Sequoia Hall.
• TAs:  Rakesh Kumar Achanta,  Claire Louise Donnat, Leying Guan, Kris Sankaran, Matteo Sesia, Xiaoying Tian,  Jeha Yang, Qian Zhao.
• Text: Elements of Statistical Learning. Hastie, Tibshirani & Friedman. Springer.
• Homework:
  • traditional.
  • computing assignments (implement methods using R - discuss results).
• Midterm: no.
• Final: take home.

Topics:

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