The textbook is: Richard O. Duda, Peter E. Hart, and David Stork. Pattern Classification New York, NY: John Wiley and Sons, 2001 (ISBN 0-471-05669-3). All references in the outline are to this text. Please note that the schedule is tentative. Changes will be indicated in italics .
A course outline follows. The Sections of the text listed under the readings headings should be read before the corresponding class. Note that February 26 is the last day to withdraw without failure. Chapters 1-4 form the core of the course. I plan to cover chapter 5 in good detail, several topics from chapter 6 (especially the relationship of backpropagation to the Bayes discriminant), and some topics from the other chapters. I will assign additional readings on some topics (certainly on hidden Markov models). The final exam is scheduled for Tuesday, May 8, at 9am (the regularly scheduled exam time).
Number | Topic | Readings |
---|---|---|
1 | Introduction | Chapter 1 |
2-6 | Bayesian Decison Theory | Chapter 2 |
7-11 | Maximum Likelihood and Bayesian Parameter Estimation | Chapter 3 |
12-16 | Nonparametric Techniques | Chapter 4 |
17-20 | Linear Discriminant Functions | Chapter 5 |
20-22 | Multilayer Neural Networks | Chapter 6 |
23-28 | Selected Additional Topics in Pattern Recognition and Classification and Exams | Chapters 7-10 |