A Tutorial and Talk at useR! 2014 [Important Update]


Max Kuhn


May 7, 2014

See the update below

I’ll be doing a morning tutorial at useR! at the end of June in Los Angeles. I’ve done this same presentation at the last few conferences and this will probably be the last time for this specific workshop.

The tutorial outline is:

I’m also giving a talk called “Adaptive Resampling in a Parallel World”:

Many predictive models require parameter tuning. For example, a classification tree requires the user to specify the depth of the tree. This type of “meta parameter” or “tuning parameter” cannot be estimated directly from the training data. Resampling (e.g. cross-validation or the bootstrap) is a common method for finding reasonable values of these parameters (Kuhn and Johnson, 2013) . Suppose B resamples are used with M candidate values of the tuning parameters. This can quickly increase the computational complexity of the task. Some of the M models could be disregarded early in the resampling process due to poor performance. Maron and Moore (1997) and Shen el at (2011) describe methods to adaptively filter which models are evaluated during resampling and reducing the total number of model fits. However, model parameter tuning is an “embarrassingly parallel” task; model fits can be calculated across multiple cores or machines to reduce the total training time. With the availability of parallel processing is it still advantageous to adaptively resample?

This talk will briefly describe adaptive resampling methods and characterize their effectiveness using parallel processing via simulations.

The conference website has updated their website to say:

This year there is no separate registration process or extra fee for attending tutorials.

UPDATE! Since this is the case, I won’t be giving out the book to all the attendees as I originally intended. However, the conference does supply tutorial presenters with a stipend so I will be using that to purchase about a dozen copies that I will randomly distribute to whoever attends.

Sorry for the confusion… (This article was originally posted at http://appliedpredictivemodeling.com)