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Statistical Computing Hung Chen hchen@math.ntu.edu.tw Department of Mathematics National Taiwan University 18th February 2004 Meet at NW 405 On Wednesday from 9:10 to 12.

STA 414/2104: Statistical Methods for Machine Learning and Data Mining STA 414/2104: Statistical Methods for Machine Learning and Data Mining (Jan-Apr 2006) Note: There was a typo in my script for computing final marks, correction of which has changed some people's marks. Fortunately, none of the changes are drastic. My apologies for this! All course work has been marked and can now be picked up. You can phone 978-4970 to see if I'm in my office first. Instructor:, Office: SS6016A, Phone: (416) 978-4970, Email: Office hours: Mondays 2:30-3:30 and Wednesdays 11:30-12:30, in SS6016A. Lectures: Tuesdays, Thursdays, and Fridays, 1:10pm to 2:00pm, in SS 2111.

The first lecture is January 10; the last is April 13. There are no classes during Reading Week, from February 20 to 24. Assessment: For graduate students (in STA 2104): Two tests: 10% each Three assignments: 17% each Project: 29% For undergraduate students (in STA 414): Either the same as for the graduate students, or: Two tests: 10% each Four assignments: 20% each Undergraduates who wish to do three assignments and a project must begin the project at the same time as the graduate students, but may later switch to doing four assignments if they wish. However, they can't hand in both a project and the fourth assignment.

The assignments are to be done by each student individually. Any discussion of the assignments with other students should be about general issues only, and should not involve giving or receiving written or typed notes. Projects may be done individually or in groups of two (possibly more than two, with special permission). More will be expected of a group project than an individual project.

Course Text: Hastie, Tibshirani, and Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer. The contains errata, datasets, and other information. Computing: The assignments (and possibly project) will involve writing small programs. I recommend that you write these in either R or Matlab, though other languages are also possible. If you don't have a home computer (or don't want to use it), you can get an account on the. If you're an undergraduate registered in STA 414, you should be able to get an account by clicking on 'Request an Account' in the upper left of the main CQUEST page.

If you're a graduate student in STA 2104 without other computing access, you need to fill out a form you can get from me to get a CQUEST account. If you have a home computer, you can download R for free from. There should be compiled versions for Windows and Linux, as well as source that can be compiled for Unix/Linux systems. The download comes with documentation, including. Another option for home use is Matlab, which costs money, or Octave, a free Matlab look-alike, available from. I have only limited experience with Octave, however, and it appears to be less well-supported than R.

Here are some and some that may be useful. What to read in the text: Chapter 1 Chapter 2 Chapter 3 (except 3.4.6) Chapter 4 (except 4.2) Chapter 5 (except 5.8 and 5.9) Chapter 7 (except 7.8 and 7.11) Chapter 14 (sections 14.1 to 14.3) Other useful references:. Slides for my NIPS.2004 tutorial on Bayesian methods for machine learning, in. Assignments: Assignment 1:,.

Data to test on:,. Here are some and some that may be useful.

Elements Of Statistical Computing Pdf Writer Free

Here is the solution (in R):,. Assignment 2:,. Here is the data:,. Here are some and some that may be useful. Clarification: The assignment handout doesn't specify exactly how to do the principal component computation. You should subtract the mean (on training cases) from each of the 200 variables, but do not standardize by dividing by the standard deviation. (Of course, you can try it with standardization too if you're interested.) Here is the solution (in R):,.

Assignment 3:,. Data to test on:, Here are some and some that may be useful. Here is the solution (in R):,.

Assignment 4:,. Data to test on:, You are also supposed to test on the data for Assignment 3, available above. Here are some for this assignment.

Elements Of Statistical Computing Pdf Writer Online

Here is the solution (in R):,. Tests: Test 1 was held during class on Tuesday, February 28. It covered material presented in lectures through February 17, or in the textbook Chapter 1, Chapter 2, Chapter 3 (except 3.4.6), and Chapter 4 (except 4.2 and 4.5). Test 2 was held during class on Friday, April 7. Projects: Here is some more, including some suggested topics. Projects are due on April 24.

Lecture slides: Tuesday Thursday Friday Week 1 Week 2 No slides (R tutorial) Week 3 No slides (R tutorial) Week 4 No slides (R tutorial) Week 5 Week 6 Week 7 No slides (Test) Week 8 Week 9 No slides Week 10 Week 11 No slides No slides Week 12 No slides (Test) Week 13 No slides Example R programs: An implementation of 1-NN:, You can also find lots of example R programs in the.