CS 422 Data Mining

Prerequisites: MATH 213 or MATH 112 or PSY 211 or ECMG 212, and Level III Mathematics Placement, and CS 200 or CS 219; or Permission of Instructor

Introduces basic principles and methods for data analysis and knowledge discovery to computer science students. Topics include preprocessing, association, classification, and anomaly detection. Students develop basic skills for modeling and performance evaluation.

Credits

3.0

Cross Listed Courses

Double-numbered course; offered with graduate-level CS 522

Offered

Fall Semester