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In Lecture 4, we introduced two methods for finding decision hypersurfaces, namely: 1) supervised learning, and 2) unsupervised learning. We then introduced Bayes rule for making decisions. This rule is the basis for this course.  
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In Lecture 4, we introduced two methods for finding decision hypersurfaces, namely: 1) supervised learning, and 2) unsupervised learning. We then introduced [[Bayes_Decision_Theory|Bayes rule]] for making decisions. (This rule is the basis for this course.) We focused our discussion on the case where the features are discrete. 
  
  

Latest revision as of 10:41, 13 April 2010


Details of Lecture 4, ECE662 Spring 2010

In Lecture 4, we introduced two methods for finding decision hypersurfaces, namely: 1) supervised learning, and 2) unsupervised learning. We then introduced Bayes rule for making decisions. (This rule is the basis for this course.) We focused our discussion on the case where the features are discrete.


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Alumni Liaison

Ph.D. on Applied Mathematics in Aug 2007. Involved on applications of image super-resolution to electron microscopy

Francisco Blanco-Silva