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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. | + | 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 11:41, 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.
Previous: Lecture 3
Next: Lecture 5
