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*[[ECE662_topic3_discussions|Central Limit Theorem illustrations]] | *[[ECE662_topic3_discussions|Central Limit Theorem illustrations]] | ||
*[[ECE662_hw1_discussions|Hw1: Discuss the first hw here.]] | *[[ECE662_hw1_discussions|Hw1: Discuss the first hw here.]] | ||
| + | *[[EE662Sp10Semimetric|Distance Functions Where Triangle Inequality Doesn't Hold]] | ||
==Feedback == | ==Feedback == | ||
Revision as of 13:31, 25 March 2010
Contents
ECE662: "Satistical Pattern Recognition and Decision Making Processes", Spring 2010
Message Area:
I believe the peer review system is working. You can go ahead and review the first homework.
Rhea is now on Facebook.
General Course Information
- Instructor: Prof. Boutin a.k.a. Prof. Mimi
- Office: MSEE342
- Email: mboutin at purdue dot you know where
- Class meets Tu,Th 12-13:15 in EE115
- Office hours are listed here
- Syllabus
- Course Outline
- Class cancellation: Jan 19, Jan 21, Feb 23, Feb 25
- Make up classes: to be announced. Please list the times when you cannot meet here
Discussions and Students' perspectives
- Introduction and Expectations
- Is Bayes truly the best?
- Central Limit Theorem illustrations
- Hw1: Discuss the first hw here.
- Distance Functions Where Triangle Inequality Doesn't Hold
Feedback
Homework
References
- "Introduction to Statistical Pattern Recognition" by K. Fukunaga_OldKiwi (This is the main reference)
- "Pattern Classification" by Duda, Hart, and Stork_OldKiwi
- "Pattern Recognition: A Statistical Approach" by P.A. Devijver and J.V. Kittler_OldKiwi
- "Pattern Recognition and Neural Networks" by Brian Ripley_OldKiwi
- "Introduction to Data Mining" by P-N Tan, M. Steinbach and V. Kumar_OldKiwi
