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Elements of Statistical Learning

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    Downloadable PDF.  Make sure you have the 2nd edition, corrected 10th printing.

    Meeting Time: 12:30 Mondays

    I didn't enter dates after the end of August since our meeting time will depend on our fall schedules, but feel free to sign up for topics you are interested in

    Schedule

    Who Date Topic  
    MG 2 June 1. Introduction slides
    MG 9 June 2. Overview of Supervised Learning slides
    SfW  16 June 3. Linear Methods for Regression  
    XS   23 June 4. Linear Methods for Classification  
    YY 30 June 5. Basis Expansions and Regularization  
    JW 7 July 6. Kernel Smoothing Methods  
      14 July postponed  
    YY 21 July 7. Model Assessment and Selection  
    BJ 28 July 8. Model Inference and Averaging slides
      4 August postponed  
    KP  11 August 9. Additive Models, Trees, and Related Methods  
      18 August 10. Boosting and Additive Trees  
    JW  25 August 11. Neural Networks  
      1 Sept Labor Day   
    JJH 9 Oct  12. Support Vector Machines and Flexible Discriminants  
        13. Prototype Methods and Nearest-Neighbors  
        14. Unsupervised Learning   
    KP    15. Random Forests  
        16. Ensemble Learning  
    BJ 30 Oct 17. Undirected Graphical Models slides
        18. High-Dimensional Problems  
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    Files 4

    FileSizeDateAttached by 
     chap17ugm.pdf
    No description
    677.06 kB13:41, 30 Oct 2014bjiangActions
     chap8Slides.pdf
    ESLchap8
    599.22 kB13:51, 28 Jul 2014bjiangActions
     esl1_intro.pptx
    MG - ESL Introduction
    1009.21 kB15:07, 4 Jun 2014gribskovActions
     esl1_intro2.pdf
    the rest of chapter 2
    904.18 kB10:36, 9 Jun 2014gribskovActions
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