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Rhea is now on [http://www.facebook.com/pages/West-Lafayette-IN/Rhea/88771959948 Facebook]. | Rhea is now on [http://www.facebook.com/pages/West-Lafayette-IN/Rhea/88771959948 Facebook]. | ||
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*[[EE662Sp10Semimetric|Distance Functions Where Triangle Inequality Doesn't Hold]] | *[[EE662Sp10Semimetric|Distance Functions Where Triangle Inequality Doesn't Hold]] | ||
*[[EE662Sp10AbstarctAlgebra|Group Theory Background for 3-25-10 and 3-30-10 Lectures]] | *[[EE662Sp10AbstarctAlgebra|Group Theory Background for 3-25-10 and 3-30-10 Lectures]] | ||
| + | *[[ECE662_hw2_discussions|Hw2: Discuss the first hw here.]] | ||
| + | *[[ECE662_hw3_discussions|Hw3: Discuss the first hw here.]] | ||
==Feedback == | ==Feedback == | ||
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* [[hw0_ECE662Spring2010|HW0 - getting ready]] | * [[hw0_ECE662Spring2010|HW0 - getting ready]] | ||
*[[hw1_ECE662Spring2010|HW1- Bayes rule for normally distributed features]] | *[[hw1_ECE662Spring2010|HW1- Bayes rule for normally distributed features]] | ||
| + | *[[hw2_ECE662Spring2010|HW2- Bayes rule using parametric density estimation]] | ||
| + | *[[hw3_ECE662Spring2010|HW3- Bayes rule using non-parametric density estimation]] | ||
==References== | ==References== | ||
Revision as of 10:37, 2 April 2010
Contents
ECE662: "Satistical Pattern Recognition and Decision Making Processes", Spring 2010
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
- Group Theory Background for 3-25-10 and 3-30-10 Lectures
- Hw2: Discuss the first hw here.
- Hw3: Discuss the first hw here.
Feedback
Homework
- HW0 - getting ready
- HW1- Bayes rule for normally distributed features
- HW2- Bayes rule using parametric density estimation
- HW3- Bayes rule using non-parametric density estimation
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
