Pattern Recognition (COMPE 467) Course Details

Course Name: Pattern Recognition
Code: COMPE 467
Pre-requisite Course(s):
Objective: The objective of the course is to make student familiar with general approaches such as Bayes classification, discriminant functions, decision trees, nearest neighbor rule, neural networks for pattern recognition.
Content: Bayes’ decision theory. Classifiers, discriminant functions and decision surfaces. Estimation of parameters. Hidden Markov Models. Nearest neighbor methods. Linear discriminant functions. Neural networks. Decision trees. Hierarchical clustering. Self organizing feature maps.
Term: Spring
Theory: 3
Application: 0
Laboratory: 0
Credit: 3
Web:
ECTS Course File: Course File
Course File:
ECTS: 5