An Update on Statistical Boosting in Biomedicine
Joint Authors
Hepp, Tobias
Mayr, Andreas
Gefeller, Olaf
Hofner, Benjamin
Waldmann, Elisabeth
Meyer, Sebastian
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-08-02
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Statistical boosting algorithms have triggered a lot of research during the last decade.
They combine a powerful machine learning approach with classical statistical modelling, offering various practical advantages like automated variable selection and implicit regularization of effect estimates.
They are extremely flexible, as the underlying base-learners (regression functions defining the type of effect for the explanatory variables) can be combined with any kind of loss function (target function to be optimized, defining the type of regression setting).
In this review article, we highlight the most recent methodological developments on statistical boosting regarding variable selection, functional regression, and advanced time-to-event modelling.
Additionally, we provide a short overview on relevant applications of statistical boosting in biomedicine.
American Psychological Association (APA)
Mayr, Andreas& Hofner, Benjamin& Waldmann, Elisabeth& Hepp, Tobias& Meyer, Sebastian& Gefeller, Olaf. 2017. An Update on Statistical Boosting in Biomedicine. Computational and Mathematical Methods in Medicine،Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1142220
Modern Language Association (MLA)
Mayr, Andreas…[et al.]. An Update on Statistical Boosting in Biomedicine. Computational and Mathematical Methods in Medicine No. 2017 (2017), pp.1-12.
https://search.emarefa.net/detail/BIM-1142220
American Medical Association (AMA)
Mayr, Andreas& Hofner, Benjamin& Waldmann, Elisabeth& Hepp, Tobias& Meyer, Sebastian& Gefeller, Olaf. An Update on Statistical Boosting in Biomedicine. Computational and Mathematical Methods in Medicine. 2017. Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1142220
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142220