July Meetup - GBM package: Generalized Boosted Regression Models

GBM package: Generalized Boosted Regression Models

Mark Landry

In this talk Mark will explore the GBM package in R, including the fundamentals, hyperparameters, methods, and characteristics, as well as a demonstration. The predictive algorithm behind five top 20 Kaggle finishes, GBM offers competitive accuracy, a wide variety of loss functions, relative speed, and robustness to unprepared input data.

BEER and PIZZA will be provided so come and get to know your fellow Austin UseRs.

Thanks to Revolution Analytics (http://www.revolutionanalytics.com/) and Bazaarvoice (http://www.bazaarvoice.com/) for their sponsorship!

Thanks to Infochimps (http://www.infochimps.com/) for hosting us!

 

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  • Bill S

    That was an outstanding presentation. Thanks for uploading the materials.

    1 · July 28

  • Mark L.

    Thanks, Lincoln and Amir.

    Here is a link to the presentation: http://www.slideshare.net/mark_...­

    In case anybody just wanted to see the code:
    https://github.com/mlandry22/kag...­

    2 · July 27

  • Lincoln

    This was a very good quick overview of the strengths and weaknesses of using various algorithms, G.B.M. was a clear winner in many respects. Mark was a very good speaker with an exhaustive knowledge base.

    July 25

  • Lincoln

    This was a very good quick overview of the strengths and weaknesses of using various algorithms, G.B.M. was a clear winner in many respects. Mark was a very good speaker with an exhaustive knowledge base.

    July 25

  • Amir S.

    Thanks for the talk yesterday, Mark! Could you upload your slides & code somewhere, please?

    2 · July 25

  • Fernando M.

    Environmental data analyst excited to learn something new.

    July 24

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