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:
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Class web page:
http://coursework.stanford.edu/portal/site/Sp16-STATS-315B-01
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Office hour: Thursday 3 - 4pm, 134 Sequoia Hall.
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TAs:
Rakesh Kumar Achanta, Claire Louise Donnat, Leying Guan,
Kris Sankaran, Matteo Sesia, Xiaoying Tian, Jeha Yang, Qian Zhao.
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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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computing assignments (implement methods using R - discuss results).
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Midterm: no.
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Final: take home.
Topics:
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Introduction
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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 & Random Forests (Ch.
8)
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Boosting and additive trees (GBM) (Ch.
10)
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Neural networks (Ch. 11)
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Prototype & near-neighbor methods (Ch. 13)