Data Mining: Concepts and Algorithms
Soft. Eng. and Comp. Sci. 4TF3 and 6TF3, Term 2,
Course Outline: postscript
file or pdf
Last change: Dec. 13, 2005
- Dr. Jiming Peng,
ITB 107, ext: 27746
- Email: firstname.lastname@example.org
Office hour: Thursday 14:00PM-15:00PM or by appointment
- Huarong Chen, ITB 208,
- Email: email@example.com
- Office hour: Wednesday 2:30PM-3:30PM or by appointment
Lectures: Monday, Wednesday and Thursday: 10:30 - 11:20 AM at BSB/318.
- The midterm is open book.
- Two students find a bug in the third assignment, Question 3.3. The problem should be
stated as `Use the INDUCT algorithm to extract a set of classification rules'.
- The midterm exam has been scheduled on Wed March 22, 19:00-21:00, T13/123.
- The second assignment has been posted.
- The class has been moved to ABB-270.
- TA will give a turorial of Weka at the lecture time on next Monday (Jan.
30) in ITB 239.
- Please send your name, student' ID and email address to the instructor
and TA so that we
can send the new revised lecture notes to you via email directly.
- TA will not be available at the first week. Please contact him via email
if you have any questions.
Textbooks and References
- Data Mining,
Concepts and Techniques, by J. Han, M. Kamber, Morgan Kaugmann
Publishers, 2001, ISBN 1-55860-489-8
- D. Hand, H. Mannila and P. Smyth, Principles of Data Mining, The MIT Press, 2001. ISBN 0-262-08290
Learning, by Tom M.
Mitchell, published by McBraw-Hill, 1997, ISBN 0-07-042807-7
Check Peng Du's
web page for more online resource on data mining.
Data file of weka for experiment
A tutorial of Weka Experimenter
- lecture 1: What is data mining? (pdf
- lecture 2: Preprocessing Data (revised version)
(pdf or doc)
- lecture 3: Presentational Structure (pdf
- lecture 4: Simple learning algorithms (revised) (pdf
- lecture 5: Evaluating the learning process (revised)
- lecture 6: Advanced learning algorithms, part I: Extending decision
tree and covering algorithms (revised)
- lecture 6: Advanced learning algorithms, part II: Support Vector
Machines and Clustering (revised)
- lecture 7: Miscellaneous Topics
- Assignment 1.(pdf
- Assignment 2. (pdf
- Assignment 3. (pdf
- Assignment 4. (pdf
- A sample of examination questions pdf
- The instruction for the course project.
"Students are reminded that they should read and comply with the Statements
on Academic Ethics and the Senate Resolutions on Academic Dishonesty as found
in the Senate Policy Statements distributed at registrations and available in
the Senate Office."
Revised by Huarong Chen