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*[[Parametric_Estimators_OldKiwi|About Parametric Estimators]] | *[[Parametric_Estimators_OldKiwi|About Parametric Estimators]] | ||
*[[Bayes_Rate_Fallacy:_Bayes_Rules_under_Severe_Class_Imbalance|Bayes rule under severe class imbalance]] | *[[Bayes_Rate_Fallacy:_Bayes_Rules_under_Severe_Class_Imbalance|Bayes rule under severe class imbalance]] | ||
| + | *[[Fisher_discriminant_under_nonlinear_data|Fisher linear discriminant can be used for non-linearly separable data too!]] | ||
| + | |||
== Semester/Instructor specific pages == | == Semester/Instructor specific pages == | ||
Revision as of 08:59, 16 April 2010
Contents
ECE 662: Statistical Pattern Recognition and Decision Making Processes
Click here to view a list of all pages in the ECE662 category.
Textbooks
"Introduction to Statistical Pattern Recognition" by K. Fukunaga_OldKiwi
Peer Legacy
Share advice with future students regarding ECE662 on this page.
Main Course Topics
- About Pattern Recognition
- Bayes_Decision_Theory
- Discriminant Functions
- Fisher Linear Discriminant
- Bayesian Decision Theory for Normally Distributed Features
- Feature Extraction
- Density Estimation
- Linear classifiers
- Artificial Neural Networks
- Support Vector Machines
- Clustering
- Decision Trees
Interesting pages in the ECE662 category
- About Parametric Estimators
- Bayes rule under severe class imbalance
- Fisher linear discriminant can be used for non-linearly separable data too!
Semester/Instructor specific pages
Other References
- "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
Related Courses
Please help complete this section: which course relates to ECE662?
