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| + | '''Support Vector Machines''' <br /> | ||
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| − | A [ | + | A [http://www.projectrhea.org/learning/slectures.php slecture] by student Tao Jiang |
| − | Partly based on the [ | + | Partly based on the [[2014_Spring_ECE_662_Boutin_Statistical_Pattern_recognition_slectures| ECE662 Spring 2014 lecture]] material of [[User:Mboutin| Prof. Mireille Boutin]] |
| + | </center> | ||
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Contents | Contents | ||
| − | # Basic | + | # Basic ideas of SVM |
# Slack Variables | # Slack Variables | ||
# How to solve SVM (Quadratic Programming Problem) | # How to solve SVM (Quadratic Programming Problem) | ||
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</center> | </center> | ||
References: | References: | ||
| − | * [ | + | * [[2014_Spring_ECE_662_Boutin| ECE662 Spring 2014 lecture]] material of [[User:Mboutin| Prof. Mireille Boutin]] |
* Bishop's "Pattern Recognition and Machine Learning" Book | * Bishop's "Pattern Recognition and Machine Learning" Book | ||
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Latest revision as of 09:56, 22 January 2015
Support Vector Machines
A slecture by student Tao Jiang
Partly based on the ECE662 Spring 2014 lecture material of Prof. Mireille Boutin
Contents
- Basic ideas of SVM
- Slack Variables
- How to solve SVM (Quadratic Programming Problem)
- Multi-classification
- Choosing Parameters
Link to Video on Youtube
References:
- ECE662 Spring 2014 lecture material of Prof. Mireille Boutin
- Bishop's "Pattern Recognition and Machine Learning" Book
Questions and comments
If you have any questions, comments, etc. please post them on this page.
