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Super Learner

Please join us for the April 2016 installment of our monthly meetup series!

This month's meetup will again be hosted at Ann Arbor SPARK, who will also be providing pizza for the group.

An introduction to SuperLearner, a loss-based ensemble prediction algorithm.

This presentation provides a brief introduction to SuperLearner package, an ensemble prediction algorithm developed by Eric Polley at the National Cancer Institute. SuperLearner allows the use many algorithms to generate an ideal prediction function that is a weighted average of all the algorithms considered. The SuperLearner package permits the integration of dozens of prespecified potential algorithms found in other R packages as well as 'wrappers' that provide the user with the ability to include their own algorithms.

Presenter bio: 

Scott Grey is a senior statistician in the University of Michigan's Division of Cardiology where he analyzes data from registries of percutaneous interventions. He received his Masters and PhD from Case Western Reserve University.

This presentation is an "informal part two" to another presentation from Scott, "Integrating machine learning into causal inference: the Targeted Maximum Likelihood Estimation approach" offered by the Ann Arbor ASA Chapter on Tuesday, April 12:

You do not need to attend that event to understand this one, but we suggest attending both if possible.

Join us at HopCat afterward for the usual food and drinks!!

Join or login to comment.

  • Daniel K.

    During the presentation there was a question that referenced an ML approach that involved using cross-validated predictions to augment the feature set, and then feeding this into another layer of learners, and so on. I'd like to learn more. Is there a reference or even name for this approach? From googling around, "Cascade Classifiers" seem related, or maybe this is just a special case of a neural network approach?

    April 20

    • Daniel K.

      Thanks for the info and link! Were you the one the brought it up at the meetup?

      April 20

    • Alex K.

      Yea, I definitely mentioned it, as well as using RF as an ensembling algorithm.

      1 · April 20

  • Simeone

    Hi all. Did you update the website with the slides of the last talk (SuperLearner)?
    Thank you

    April 19

    • Ellis V.

      We'll have the slides on the site tonight. Scott was fixing a merge conflict that affected the slides.

      April 19

    • Simeone

      Thank you. yes, I found slides for his 2 talks through the ASA meetup as well.

      April 20

  • Parker

    Really wish I could make this, but other responsibilities getting in the way. If there are slides afterward, I wouldn't mind snagging a copy.

    April 7

    • Michelle B.

      Hi Parker, check our website after the event http://annarborruserg...­ . You can find slides from all previous events there as well.

      April 9

    • Ellis V.

      Hey Parker, I _finally_ got the website updated with the slides. The code is also hosted on the group's and Scott's github pages.

      April 20

  • Simeone

    Great !!

    1 · April 15

  • Natasha

    Is there any chance to connect remotely?

    April 14

    • Michelle B.

      Hi Natasha, unfortunately there is not. However, we we always post slides to our github. See the link below in my reply to Parker

      April 14

  • Barry D.

    Scott, can you contact me? It looks like the order of the presentations will have to be reversed.

    April 4

Our Sponsors

  • Ann Arbor SPARK

    SPARK provides space and food for the meetup

  • R Consortium

    The RC RUGS program provides financial support for R User Groups.

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