36-350: Data Mining (Fall 2003)

Lectures: Monday and Wednesday, 10:30-11:20, CFA 211
Computer labs: Friday, 10:30-11:20, Baker 140F
Instructor: Tom Minka, Statistics Dept
Teaching Assistant: Fang Chen
Syllabus Revision policy R home page Data Mining links 2003 Car data

8/25Searching for information by similarityhw1
8/27Multi-dimensional scaling
8/29Lab 1 mining.zip lab1_docs.rda lab1.r politics3.txt
9/3Searching for images by similarityhw2
9/5Lab 2 mining.zip lab2_imgs.rda lab2.r
9/8Information content of wordshw3
9/10Interactions and "20 questions"
9/12Lab 3 mining.zip lab3_docs.zip lab3.r
9/15Partitioning data into clustershw4
9/17Partitioning images and video
9/19Lab 4 mining.zip lab2_imgs.rda lab4_img.rda lab4.r
9/22PCA projection of Carshw5
9/24Interpreting PCA projection
9/26Lab 5 mining.zip lab5.r
9/28Visualizing subgroups with informative projectionshw6
10/1Parallel-coordinate plots
10/3Lab 6 mining.zip lab6.r
10/6Trend lines, slice plots, regression projectionhw7
10/8Contour plots
10/10Lab 7 mining.zip lab7.r
10/13Regression treeshw8
10/15More with trees
10/20Linear regression for marketing researchhw9
10/22Selecting variables for linear regression
10/24Lab 9 mining.zip lab9.r lab9.rda
10/27Adding interaction terms to a linear modelhw10
10/29Assessing the quality of a regression model
10/31Lab 10 mining.zip lab10.r lab9.rda
11/3Categorical predictors and response tableshw11(greyscale version)
11/5Contingency tables
11/7Lab 11 mining.zip lab11.r crash-head.rda
11/10Classification treeshw12
11/12Tree pruning
11/14Lab 12 mining.zip lab12.r Credit.rda data description
11/17Logistic regressionhw13
11/19Quadratic expansion
11/21Lab 13 mining.zip lab12.r Credit.rda data description
11/24Modeling time-series data
12/1Time-series of purchaseshw14
12/3Final review
12/5Lab 14 mining.zip lab14.r uspop.rda

Tom Minka