CSE 591 DATA MINING

(January 20 - May 4, Spring 2004)

I hear, I forget; I see, I remember; I do, I understand. - Proverb

Your suggestions are most welcome. Please send email to hliu@asu.edu
Qualified and interested graduate students are welcome to join our data mining group to conduct state-of-the-art research. 

OUTLINE

  1. Introduction to Data Mining
  2. Data, data preparation, and data Preprocessing (Feature Selection, Discretization, Sampling)
  3. A Brief Review of Probability and Entropy
  4. Classification Methods
  5. Performance Evaluation (Measures, Comparison)
  6. Clustering Methods
  7. Association Rules
  8. Some Applications

ASSIGNMENTS

  1. There is a credit for class participation and discussion (See the home page)
  2. Assgnments 1 and 2 are stated in the first set of slides
  3. Class presentation, Papers, Schedule
  4. Project proposal presentation (Project Categories)
  5. Project progress report (Due on 3/23 Tue, brief presentation on 3/25 Thur)
  6. Project presentation (Due on 4/15 Thur [please submit the URL links to Jigar], Schedule)
  7. Project final report (Due on 4/29 Thur) and demo
Invited talk 1 on Feature Selection and Its Applications on Genomic Data by Lei Yu, March 9, Tuesday.

Invited talk 2 on Subspace Clustering Methods by Lance Parsons, May 4, Tuesday.

More on Class Presentation and Project

EXAM

LINKS

Prepared by Huan Liu on Jan.. 20, 2004
Last updated: April 6, 2004