Ruben, Thanks for bringing attention to this very interesting article.
The Kaggle competition model is aimed at identifying a "single" best prediction machine. I am curious as to whether the Kaggle model described in the article can be extended to an ensemble "uber-learner", where one can combine the individual prediction models in Kaggle to obtain a more powerful predictor. I know that Chris Volinsky and others have used this ensemble learner idea in winning their Netflix competition. Is this a practically feasible idea that can be implemented within the Kaggle system so that at the end of the competition an uber-learner (that is better than the best individual prediction) is automatically developed? Also, would there be challenges associated with the interpretability and portability of the resulting uber-learner? I would love to hear thoughts from the R prediction experts. Thanks & Best, Ravi. ------------------------------------------------------- Ravi Varadhan, Ph.D. Assistant Professor, Division of Geriatric Medicine and Gerontology School of Medicine Johns Hopkins University Ph. (410) 502-2619 email: rvarad...@jhmi.edu -----Original Message----- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Rubén Roa Sent: Wednesday, March 23, 2011 12:10 PM To: r-help@r-project.org Subject: [R] R helps win competitions DeaR ComRades, This is a quote from a News article in Science's 11-February issue, about competitions to model data: "For Chris Raimondi, a search-engine expert based in Baltimore, Maryland, and winner of the HIV-treatment competition, the Kaggle contest motivated him to hone his skills in a newly learned computer language called R, which he used to encode the winning data model. Raimondi also enjoys the competitive aspect of Kaggle challenges: "It was nice to be able to compare yourself with others; ... it became kind of addictive. ... I spent more time on this than I should." If you are interested read the full article here: http://www.sciencemag.org/content/331/6018/698.full Rubén ____________________________________________________________________________ ________ Dr. Rubén Roa-Ureta AZTI - Tecnalia / Marine Research Unit Txatxarramendi Ugartea z/g 48395 Sukarrieta (Bizkaia) SPAIN ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
