Date |
Reading (before class) |
Homework |
Topic/Content |
Presentation |
1/9/24 |
none |
none |
Syllabus, introduction |
Intro.pdf |
1/11/24 |
HTF Ch. 1 and Ch. 2.1, 2.2, and 2.3 |
Homework 1 |
Least-squares, nearest-neighbors |
lecture-1.pdf mixture-data-lin-knn.R ESL.mixture.rda |
1/16/24 |
HTF Ch. 2.4 |
none |
Class cancelled due to poor weather conditions |
|
1/18/24 |
HTF Ch. 2.4 |
none |
Decision theory |
lecture-2.pdf |
1/23/24 |
none |
none |
Loss functions in practice |
lecture-2a.pdf prostate-data-lin.R prostate.csv |
1/25/24 |
HTF Ch. 2.7, 2.8, and 2.9 |
Homework 2 |
Structured regression |
lecture-3.pdf ex-1.R ex-2.R ex-3.R |
1/30/24 |
HTF Ch. 3.1, 3.2, 3.3, 3.4 |
none |
Linear methods, subset selection, ridge, and lasso |
lecture-4a.pdf linear-regression-examples.R lecture-5.pdf lasso-example.R |
2/1/24 |
none |
none |
Linear methods, subset selection, ridge, and lasso (cont.) |
lecture-5.pdf lasso-example.R Suggested supplemental reading: HTF Ch. 3.6, 3.7, 3.8, and 3.9. Suggested supplemental exercises: Ex. 3.12, 3.18 |
2/6/24 |
HTF Ch. 3.5 and 3.6 |
none |
Linear methods: principal components regression |
lecture-6.pdf pca-regression-example.R |
2/8/24 |
HTF Ch. 4.1, 4.2, and 4.3 |
none |
Linear methods: Linear discriminant analysis |
lecture-8.pdf simple-LDA-3D.R |
2/13/24 |
HTF Ch. 5.1 and 5.2 |
Homework 3 |
Basis expansions: piecewise polynomials & splines |
lecture-11.pdf splines-example.R mixture-data-complete.R |
2/15/24 |
HTF Ch. 6.1-6.5 |
none |
Kernel methods |
lecture-13.pdf mixture-data-knn-local-kde.R kernel-methods-examples-mcycle.R |
2/20/24 |
HTF Ch. 7.1, 7.2, 7.3, 7.4 |
none |
Model assessment: Cp, AIC, BIC |
lecture-14.pdf effective-df-aic-bic-mcycle.R |
2/22/24 |
HTF Ch. 7.10 |
none |
Cross validation |
lecture-15.pdf kNN-CV.R Income2.csv |
2/27/24 |
HTF Ch. 9.2 |
Homework 4 |
Classification and Regression Trees |
lecture-21.pdf mixture-data-rpart.R |
2/29/24 |
HTF Ch. 8.7, 8.8, 8.9 |
none |
Bagging |
lecture-18.pdf mixture-data-rpart-bagging.R nonlinear-bagging.html |
3/5/24 |
HTF Ch. 11.1, 11.2, 11.3, 11.4, 11.5 |
none |
Introduction to Neural networks |
lecture-31.pdf nnet.R |
3/7/24 |
HTF Ch. 11.1, 11.2, 11.3, 11.4, 11.5 |
none |
Introduction to Neural networks (cont.) |
lecture-31.pdf nnet.R |
3/19/24 |
HTF Ch. 11.1, 11.2, 11.3, 11.4, 11.5 |
none |
Introduction to Neural networks (cont.) |
lecture-31.pdf nnet.R |
3/21/24 |
HTF Ch. 15.1, 15.2 |
none |
Random Forest (distribute midterm) |
lecture-25.pdf random-forest-example.R |
3/26/24 |
HTF Ch. 10.1 |
none |
Boosting and AdaBoost.M1 |
lecture-22.pdf boosting-trees.R |
3/28/24 |
HTF Ch. 10.2-10.9 |
|
Boosting and AdaBoost.M1 (part 2) |
lecture-23.pdf |