CSC 451 Pattern Recognition
This course provides a broad introduction to pattern recognition. Topics include: Bayesian decision theory, density estimation, linear classifiers, nearest neighbor rules, decision trees, artificial neural networks, dimensionality reduction, feature extraction and feature selection, clustering. The course is directed towards advanced undergraduate and beginning graduate students. If students do not meet requisite requirements, permission of the instructor is required.
Cross Listed Courses
CSC 451 & CSC 551