LECTURE 20: LINEAR DISCRIMINANT ANALYSIS

• Objectives:
  
  
  • Review maximum likelihood classification
    
    
  • Appreciate the importance of weighted distance measures
    
    
  • Introduce the concept of discrimination
    
    
  • Understand under what conditions linear discriminant analysis is useful

This material can be found in most pattern recognition textbooks. This is the book we recommend:

R.O. Duda, P.E. Hart, and D.G. Stork, Pattern Classification (Second Edition), Wiley Interscience, New York, New York, USA, ISBN: 0-471-05669-3, 2000.

and use in our pattern recognition course. The material in this lecture follows this textbook closely:

J. Deller, et. al., Discrete-Time Processing of Speech Signals, MacMillan Publishing Co., ISBN: 0-7803-5386-2, 2000.

Each of these sources contain references to the seminal publications in this area, including our all-time favorite:

K. Fukunga, Introduction to Statistical Pattern Recognition, MacMillan Publishing Company, San Diego, California, USA, ISBN: 0-1226-9851-7, 1990.