Designation: Elective Course
Course Level: Graduate
Prerequisite(s) by Topic:
Prerequisite: Consent of the Instructor
Introduction to pattern recognition, feature extraction, and classification. Bayesian decision theory, maximum likelihood and Bayesian parameter estimation, Nonparametric pattern classification techniques, density estimation. Pattern Classification using linear discriminant functions. Unsupervised machine learning, clustering, vector quantization, K-means. Various methods of pattern recognition, extraction methods, statistical classification, various classifiers and case studies.