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Week09

Page history last edited by PBworks 9 years, 8 months ago

 Lectures:  

 

Expectation-Maximization Algorithm

        ExpectationMaximization.pdf   (from Ethem Alpaydin)      

               Notes  look at pages 1 - 3 (from Andrew Ng) 

 

Gaussian Discriminant Analysis

             Notes look at pages 2 - 6 (from Andrew Ng) 

            http://www.cosmolearning.com/video-lectures/learning-algorithms-generative-gaussian-discriminant-analysis-digression/ 

 

 

Reference Material:

           1)   Andrew Ng's notes above 

           2)  Our text book Section 9.2.2 Clustering Using Mixture Models

           3) Maximum Likelihood by Andrew Moore

 

 

Examples:

          NaiveBayesMore.R   ExpectMax.R  

 

Data Files:

          Iris Data 

 

 

Homework: 

          HW #8 on Chapter 9  Data Sets on Irvine's Web Site

 

                    Challenge Problem Data Set:   Synthetic Control Data

                                             Paper to read:  R. J. Alcock and Y. Manolopoulous

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