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
Sandbridge Hall 107
Dr. Jessica Lin
Office: Engineering Building 4419
Email: jessica [AT] gmu [DOT] edu
Office Hours: Tuesday/Thursday 10:30-11:30am
Office Hours: TBA
There will be one exam covering lectures and readings (in class, closed book). The exam must be taken at the scheduled time and place, unless prior arrangement has been made with the instructor. Missed exam cannot be made up.
There will be one team project in the semester. The project grade
consists of project proposal (including project pitch, 5% total of
overall course grade), presentation (10%), and project report and code
to Data Mining by Pang-Ning Tan, Michael Steinbach, and Vipin
Kumar (click on the link for the companion website)
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.
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.