Data Mining
CSE-4412
Winter 2008
York University

Semester: Winter 2008
Course/Sect#: CSE-4412
Time: Tue 1pm-2:30pm
Thu 1pm-2:30pm
Location: FS 320
Instructor: Aijun An
Office: CSB 2048
Office Hours: Thursday 2:40-4pm
or by appointment
Phone #: 416-736-2100 x44298
e-mail: aan@cs.yorku.ca

Welcome to the Data Mining course, CSE-4412, for Winter 2008. Materials, instructions, and notices for the course will accumulate here over the semester.

Message Board

April 28, 2008
Grades are posted. You can check yours by using "courseInfo 4412 2007-08 W".
April 13, 2008
Please be reminded that the final exam will take place at 9:30am-12pm on Wednesday April 16 in VH 3009.
April 1, 2008
The location for project presentations is Lumbers 354, which is a seminar room.
March 31, 2008
Tuesday April 1's class is moved to Friday April 4 at 2:30pm-4pm for project presentations. Location is to be announced.
March 13, 2008
Project is posted. Please see the link below in the Assignments and Project section.
March 8, 2008
Solutions to Midterm questions are posted. Please see here.
March 4, 2008
An FAQ page for Assignment #2 is created. Please see here.
February 26, 2008
Assignment #2 is posted. See the link below in the Assignments and Project section.
February 19, 2008
Solutions to A1 questions are posted. Please see solutions to Q2, Q4, Q5 and Q6 and solution to Q3.
Also, click here to download the solutions to the sample test questions.
February 11, 2008
Please be reminded that the midterm test will be held on Thursday February 21 at the class time in ACE 007. Please note that the room is different from our regular lecture room. Click here to download some sample questions.
January 16, 2008
Assigment #1 is posted. See the link below in the Assignments and Project section.
January 2, 2008
This web page is set up. Welcome to the course!

Description

Data mining or knowledge discovery from databases (KDD) is one of the most active areas of research in databases. It is at the intersection of database systems, statistics, AI/machine learning, and data visualization. In this course, we will introduce the concepts of data mining and present data mining algorithms and applications. Topics include association rule mining, sequential pattern mining, classification models, clustering, and Web mining.

Prerequisites

  • Required: an introductory course on database systems.
  • Preferred: basic concepts in probability and statistics.

Materials

  • Textbook
  • Reference Books
    • Pang-Ning Tan, Michael Steinbach, Vipin Kumar, Introduction to Data Mining, Addison Wesley, 2006.
    • Ian H. Witten and Eibe Frank, Data Mining -- Practical Machine Learning Tools and Techniques (Second Edition), Morgan Kaufmann, 2005.
    • Margaret H. Dunham, Data Mining -- Introductory and Advanced Topics, Prentice Hall, 2003.
    • Some conference/journal papers (will be posted over the semester).

Grading Scheme

  • Assignments (25%)
  • Midterm (20%) (Thursday February 21 at the class time, place: ACE 007)
  • Project (20%)
  • Final exam (35%) (Wednesday April 16 at 9:30am - 12pm in VH 3009)

Lectures

Assignments and Project

Useful On-line Information
Academic Honesty