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Methods Inf Med 2019; 58(01): 060
DOI: 10.1055/s-0038-1669389
Addendum
Georg Thieme Verlag KG Stuttgart · New York

Addendum to: Approaches to Regularized Regression – A Comparison between Gradient Boosting and the Lasso

Authors

  • Tobias Hepp

    1   Institut für Medizininformatik, Biometrie und Epidemiologie, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany

  • Matthias Schmid

    2   Institut für medizinische Biometrie, Informatik und Epidemiologie, Rheinische Friedrich-Wilhelms-Universität Bonn, Germany

  • Olaf Gefeller

    1   Institut für Medizininformatik, Biometrie und Epidemiologie, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany

  • Elisabeth Waldmann

    1   Institut für Medizininformatik, Biometrie und Epidemiologie, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany

  • Andreas Mayr

    1   Institut für Medizininformatik, Biometrie und Epidemiologie, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
    2   Institut für medizinische Biometrie, Informatik und Epidemiologie, Rheinische Friedrich-Wilhelms-Universität Bonn, Germany
Further Information

Publication History

Publication Date:
11 January 2019 (online)

 
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Corrected by:

Approaches to Regularized Regression – A Comparison between Gradient Boosting and the LassoMethods Inf Med 2016; 55(05): 422-430
DOI: 10.3414/ME16-01-0033

    The following note should be added to the Original Article by Hepp et al. “Approaches to Regularized Regression – A Comparison between Gradient Boosting and the Lasso” (Methods Inf Med 2016; 55: 422–430):

    Tobias Hepp performed the present work in partial fulfilment of the requirements for obtaining the degree ‘Dr. rer. biol. hum.’ at the University of Erlangen-Nuremberg.


     

    No conflict of interest has been declared by the author(s).

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