George Mason University

Department of Computer Science

CS 484: Data Mining

Spring 2017

Professor Jessica Lin

Course Description

Basic principles and methods for data analysis and knowledge discovery. Emphasizes developing basic skills for modeling and prediction and performance evaluation. Topics include system design; data quality, preprocessing, and association; event classification; clustering; biometrics; business intelligence; and mining complex types of data.

Class Time and Location

Thursday, 4:30-7:10 pm
Planetary Hall 122


Dr. Jessica Lin
Office: Engineering Building 4419
Phone: 703-993-4693
Email: jessica [AT] cs [DOT] gmu [DOT] edu
Office Hours: Wednesday & Thursday 3-4pm

          Grade of C or better in CS 310 and STAT 344

Course Outcomes

Assignments: 25%
Project: 20%
Midterm: 25%
Final: 30%


There will be one midterm exam and a final exam covering lectures and readings (both will be in class, closed book). The final exam is comprehensive. Exams must be taken at the scheduled time and place, unless prior arrangement has been made with the instructor. Missed exams cannot be made up.


          Required: Introduction to Data Mining by Pang-Ning Tan, Michael Steinbach, and Vipin Kumar



Honor Code Statement

The GMU Honor Code is in effect at all times. In addition, the CS Department has further honor code policies regarding programming projects, which are detailed here. Any deviation from the GMU or the CS department Honor Code is considered an Honor Code violation. All assignments for this class are individual unless otherwise specified.

Learning Disability Accommodation

If you have a documented learning disability or other condition which may affect academic performance, make sure this documentation is on file with the Office of Disability Services and then discuss with the professor about accommodations.

Course Website