CSE 572 DATA MINING

(January 18 - May 3, Spring 2005)

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

We will hear, see and do in this class in the form of lectures, invited talks, discussions, research paper reading assignment, a project, and presentation, in addition to homework, quizzes, and exam(s).

Your suggestions are most welcome. Please send email to hliu at asu.edu

OUTLINE

  1. Introduction to Data Mining
  2. Data, data preparation, and data Preprocessing (feature selection, discretization, sampling, instance selection)
  3. A Brief Review of Probability and Entropy
  4. Classification Methods (ensemble methods, skewed data, cost-sensitive classification)
  5. Performance Evaluation (Measures, Comparison)
  6. Clustering Methods (subspace clustering, CLIQUE)
  7. Association Rules
  8. Some Applications (steganography and steganalysis, streaming data extraction, gene selection)

ASSIGNMENTS (To be updated)

  1. There is a credit (10%) for class participation and discussion (See the home page)
  2. Assignments 1 and 2 are stated in the first set of slides
  3. Research paper reading assignment, and selected presentations (All students are  divided into two batches: one month apart between the two; first batch will include those students who have basic data mining training; the due date for them is one month into the semester (2/17/05); and the 2nd batch will have the reading assignment due two months into the semester (3/17/05). All selected papers should be approved by the instructor.)
  4. Project proposal (If we have proposal presentations, there will be 2 minutes each to share your ideas about what you're going to do) (Project Categories)
  5. Project progress report
  6. Project presentation  [please submit the URL links to TA], Schedule)
  7. Project final report and demo
More on Paper Reading Assignment, Project and its Due Dates

EXAMS

LINKS

Prepared by Huan Liu on Dec. 17, 2004
Last updated: Dec. 17, 2004