Data Mining
CSE-4412
Fall 2013
York University

Semester: Fall 2013
Course/Sect#: CSE-4412
Time: Tue 1:00pm-2:30pm
Thu 1:00pm-2:30pm
Location: CB 120
Instructor: Aijun An
Office: CSE 2048
Office Hours: Tuesdays and Thursdays 2:40-3:30pm
Phone #: 416-736-2100 x44298
e-mail: aan@cse.yorku.ca

Welcome to the Data Mining course, CSE-4412, for Fall 2013. Materials, instructions, and notices for the course will accumulate here over the semester.

Message Board

December 24, 2013
Grades are posted. You can check yours by using ePost.
December 10, 2013
Please be reminded that the final exam will take place at 9:30am-12:00pm on Wednesday December 11. The location is ACE 008.
November 20, 2013
Project is posted. Please see the link below in the Assignments and Project section.
November 12, 2013
An FAQ page for Assignment #3 is created. Please see here.
November 7, 2013
Assignment #3 is posted. Please see the link below in the Assignments and Project section.
November 4, 2013
Solutions to Assignment #2 are posted. Please see here.
November 1, 2013
Please be reminded that the midterm test will be held on Tuesday November 5 at the class time in CB 120. For sample test questions, click here. The username and password are the same as the ones used for accessing the lecture notes.
October 22, 2013
Assignment #2 is posted. Please see the link below in the Assignments and Project section.
September 20, 2013
Assigment #1 is posted. Please see the link below in the Assignments and Project section. The access to the assignment is password-protected. The username and password are the same as the ones you use for downloading the lecture notes.
September 9, 2013
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 text mining.

Prerequisites

  • Required: a course on data structures and 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.
    • S.M. Weiss and N. Indurkhya, Predictive Data Mining, Morgan Kaufmann, 1998.
    • 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%)
  • Project (20%)
  • Final exam (35%)

Lectures

Assignments and Project

  • Assignment 1 (8%) (Due Tuesday October 8 in class)
  • Assignment 2 (6%) (Due Monday November 4 by 2pm in CSE4412 Assignment dropbox or submit a pdf file online here
  • Assignment 3 (11%) (Due Tuesday November 19 by noon).
  • Project (20%) (Due Friday December 6 at 5pm)
Useful On-line Information
Academic Honesty