Statistics 315B: (Winter 2008)
Modern Applied Statistics: Elements of Statistical
Learning II
TIME: Tues. & Thurs.
4:15 - 5:30pm
Location: McCullough 115
Instructor: Jerome H. Friedman
Logistics:
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Class web page:
http://www.stanford.edu/class/stats315b
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Office hour: Wed. 4:15pm - 5:15pm, 134 Sequoia Hall.
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TAs: Zhen Wei (108 Sequoia, zhenwei@stanford.edu) & Nick Johnson
(234 Sequoia, nickaj@stanford.edu)
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Text: Elements of Statistical Learning. Hastie, Tibshirani
& Friedman. Springer.
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Homework:
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traditional.
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(journal) reading assignments (with/without questions).
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computing assignments (apply / implement methods using R - discuss
results).
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Midterm: no.
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Final: likely - not sure what form.
Topics:
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Classification & regression trees (CART)
(Ch. 9)
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Multivariate adaptive regression splines (MARS) (Ch.
9)
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Bagging (Ch.
8)
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Boosting and additive trees (MART) (Ch.
10)
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Neural networks (Ch. 11)
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Prototype & near-neighbor methods (Ch. 13)
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