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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 rule for making decisions. (This rule is the basis for this course.) We focused our discussion on the case where the features are discrete. 
  
  

Revision as of 07:11, 12 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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Correspondence Chess Grandmaster and Purdue Alumni

Prof. Dan Fleetwood