George Mason University
George Mason University Mason
George Mason University

CS 688: Pattern Recognition

Course Information from University Catalog

Not Repeatable


Explores statistical pattern recognition and neural networks. Pattern recognition topics include Bayesian classification and decision theory, density (parametric and nonparametric) estimation, linear and nonlinear discriminant analysis, dimensionality reduction, feature extraction and selection, mixture models and EM, and vector quantization and clustering. Neural networks topics include feed-forward networks and back-propagation, self-organization feature maps, and radial basis functions. Emphasizes experimental design, applications, and performance evaluation.

Hours of Lecture or Seminar per week: 3

Credits: 3

Prerequisites:

CS 580.

1 Course Sections Scheduled for Fall 2017

1 Course Sections Scheduled for Fall 2016

Expertise